Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n\\n def _warn_for_persistence_only_flags(self, **kw: Any) ->None:\\n for k, v in kw.items():\\n if v != self._persistence_only[k]:\\n util.warn(\\n 'Setting %s on relationship() while also setting viewonly=True does not make sense, as a viewonly=True relationship does not perform persistence operations. This configuration may raise an error in a future release.'\\n % (k,))\\n\\n def instrument_class(self, mapper: Mapper[Any]) ->None:\\n attributes.register_descriptor(mapper.class_, self.key, comparator=\\n self.comparator_factory(self, mapper), parententity=mapper, doc\\n =self.doc)\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n\\n def _lazy_none_clause(self, reverse_direction: bool=False, adapt_source:\\n Optional[_CoreAdapterProto]=None) ->ColumnElement[bool]:\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n criterion = adapt_criterion_to_null(criterion, bind_to_col)\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n\\n def _add_reverse_property(self, key: str) ->None:\\n other = self.mapper.get_property(key, _configure_mappers=False)\\n if not isinstance(other, RelationshipProperty):\\n raise sa_exc.InvalidRequestError(\\n \\\"back_populates on relationship '%s' refers to attribute '%s' that is not a relationship. The back_populates parameter should refer to the name of a relationship on the target class.\\\"\\n % (self, other))\\n self._check_sync_backref(self, other)\\n self._check_sync_backref(other, self)\\n self._reverse_property.add(other)\\n other._reverse_property.add(self)\\n other._setup_entity()\\n if not other.mapper.common_parent(self.parent):\\n raise sa_exc.ArgumentError(\\n 'reverse_property %r on relationship %s references relationship %s, which does not reference mapper %s'\\n % (key, self, other, self.parent))\\n if other._configure_started and self.direction in (ONETOMANY, MANYTOONE\\n ) and self.direction == other.direction:\\n raise sa_exc.ArgumentError(\\n '%s and back-reference %s are both of the same direction %r. Did you mean to set remote_side on the many-to-one side ?'\\n % (other, self, self.direction))\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n\\n @util.memoized_property\\n @util.preload_module('sqlalchemy.orm.clsregistry')\\n def _clsregistry_resolvers(self) ->Tuple[Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]], Callable[[str, bool],\\n _class_resolver]]:\\n _resolver = util.preloaded.orm_clsregistry._resolver\\n return _resolver(self.parent.class_, self)\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n\\n def _warn_for_persistence_only_flags(self, **kw: Any) ->None:\\n for k, v in kw.items():\\n if v != self._persistence_only[k]:\\n util.warn(\\n 'Setting %s on relationship() while also setting viewonly=True does not make sense, as a viewonly=True relationship does not perform persistence operations. This configuration may raise an error in a future release.'\\n % (k,))\\n\\n def instrument_class(self, mapper: Mapper[Any]) ->None:\\n attributes.register_descriptor(mapper.class_, self.key, comparator=\\n self.comparator_factory(self, mapper), parententity=mapper, doc\\n =self.doc)\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n\\n def _lazy_none_clause(self, reverse_direction: bool=False, adapt_source:\\n Optional[_CoreAdapterProto]=None) ->ColumnElement[bool]:\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n criterion = adapt_criterion_to_null(criterion, bind_to_col)\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n\\n @util.memoized_property\\n @util.preload_module('sqlalchemy.orm.clsregistry')\\n def _clsregistry_resolvers(self) ->Tuple[Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]], Callable[[str, bool],\\n _class_resolver]]:\\n _resolver = util.preloaded.orm_clsregistry._resolver\\n return _resolver(self.parent.class_, self)\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n\\n def instrument_class(self, mapper: Mapper[Any]) ->None:\\n attributes.register_descriptor(mapper.class_, self.key, comparator=\\n self.comparator_factory(self, mapper), parententity=mapper, doc\\n =self.doc)\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n\\n def _lazy_none_clause(self, reverse_direction: bool=False, adapt_source:\\n Optional[_CoreAdapterProto]=None) ->ColumnElement[bool]:\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n criterion = adapt_criterion_to_null(criterion, bind_to_col)\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n\\n @util.memoized_property\\n @util.preload_module('sqlalchemy.orm.clsregistry')\\n def _clsregistry_resolvers(self) ->Tuple[Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]], Callable[[str, bool],\\n _class_resolver]]:\\n _resolver = util.preloaded.orm_clsregistry._resolver\\n return _resolver(self.parent.class_, self)\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n\\n def _lazy_none_clause(self, reverse_direction: bool=False, adapt_source:\\n Optional[_CoreAdapterProto]=None) ->ColumnElement[bool]:\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n criterion = adapt_criterion_to_null(criterion, bind_to_col)\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n\\n @util.memoized_property\\n @util.preload_module('sqlalchemy.orm.clsregistry')\\n def _clsregistry_resolvers(self) ->Tuple[Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]], Callable[[str, bool],\\n _class_resolver]]:\\n _resolver = util.preloaded.orm_clsregistry._resolver\\n return _resolver(self.parent.class_, self)\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n\\n def _lazy_none_clause(self, reverse_direction: bool=False, adapt_source:\\n Optional[_CoreAdapterProto]=None) ->ColumnElement[bool]:\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n criterion = adapt_criterion_to_null(criterion, bind_to_col)\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n\\n def _check_cascade_settings(self, cascade: CascadeOptions) ->None:\\n if cascade.delete_orphan and not self.single_parent and (self.\\n direction is MANYTOMANY or self.direction is MANYTOONE):\\n raise sa_exc.ArgumentError(\\n 'For %(direction)s relationship %(rel)s, delete-orphan cascade is normally configured only on the \\\"one\\\" side of a one-to-many relationship, and not on the \\\"many\\\" side of a many-to-one or many-to-many relationship. To force this relationship to allow a particular \\\"%(relatedcls)s\\\" object to be referred towards by only a single \\\"%(clsname)s\\\" object at a time via the %(rel)s relationship, which would allow delete-orphan cascade to take place in this direction, set the single_parent=True flag.'\\n % {'rel': self, 'direction': 'many-to-one' if self.\\n direction is MANYTOONE else 'many-to-many', 'clsname': self\\n .parent.class_.__name__, 'relatedcls': self.mapper.class_.\\n __name__}, code='bbf0')\\n if self.passive_deletes == 'all' and ('delete' in cascade or \\n 'delete-orphan' in cascade):\\n raise sa_exc.ArgumentError(\\n \\\"On %s, can't set passive_deletes='all' in conjunction with 'delete' or 'delete-orphan' cascade\\\"\\n % self)\\n if cascade.delete_orphan:\\n self.mapper.primary_mapper()._delete_orphans.append((self.key,\\n self.parent.class_))\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n\\n def _columns_are_mapped(self, *cols: ColumnElement[Any]) ->bool:\\n \\\"\\\"\\\"Return True if all columns in the given collection are\\n mapped by the tables referenced by this :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n secondary = self._init_args.secondary.resolved\\n for c in cols:\\n if secondary is not None and secondary.c.contains_column(c):\\n continue\\n if not self.parent.persist_selectable.c.contains_column(c\\n ) and not self.target.c.contains_column(c):\\n return False\\n return True\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n\\n def declarative_scan(self, decl_scan: _ClassScanMapperConfig, registry:\\n _RegistryType, cls: Type[Any], originating_module: Optional[str],\\n key: str, mapped_container: Optional[Type[Mapped[Any]]], annotation:\\n Optional[_AnnotationScanType], extracted_mapped_annotation:\\n Optional[_AnnotationScanType], is_dataclass_field: bool) ->None:\\n argument = extracted_mapped_annotation\\n if extracted_mapped_annotation is None:\\n if self.argument is None:\\n self._raise_for_required(key, cls)\\n else:\\n return\\n argument = extracted_mapped_annotation\\n assert originating_module is not None\\n is_write_only = mapped_container is not None and issubclass(\\n mapped_container, WriteOnlyMapped)\\n if is_write_only:\\n self.lazy = 'write_only'\\n self.strategy_key = ('lazy', self.lazy),\\n is_dynamic = mapped_container is not None and issubclass(\\n mapped_container, DynamicMapped)\\n if is_dynamic:\\n self.lazy = 'dynamic'\\n self.strategy_key = ('lazy', self.lazy),\\n argument = de_optionalize_union_types(argument)\\n if hasattr(argument, '__origin__'):\\n arg_origin = argument.__origin__\\n if isinstance(arg_origin, type) and issubclass(arg_origin, abc.\\n Collection):\\n if self.collection_class is None:\\n if _py_inspect.isabstract(arg_origin):\\n raise sa_exc.ArgumentError(\\n f\\\"Collection annotation type {arg_origin} cannot be instantiated; please provide an explicit 'collection_class' parameter (e.g. list, set, etc.) to the relationship() function to accompany this annotation\\\"\\n )\\n self.collection_class = arg_origin\\n elif not is_write_only and not is_dynamic:\\n self.uselist = False\\n if argument.__args__:\\n if isinstance(arg_origin, type) and issubclass(arg_origin,\\n typing.Mapping):\\n type_arg = argument.__args__[-1]\\n else:\\n type_arg = argument.__args__[0]\\n if hasattr(type_arg, '__forward_arg__'):\\n str_argument = type_arg.__forward_arg__\\n argument = resolve_name_to_real_class_name(str_argument,\\n originating_module)\\n else:\\n argument = type_arg\\n else:\\n raise sa_exc.ArgumentError(\\n f'Generic alias {argument} requires an argument')\\n elif hasattr(argument, '__forward_arg__'):\\n argument = argument.__forward_arg__\\n argument = resolve_name_to_real_class_name(argument,\\n originating_module)\\n if (self.collection_class is None and not is_write_only and not\\n is_dynamic):\\n self.uselist = False\\n if self.argument is None:\\n self.argument = cast('_RelationshipArgumentType[_T]', argument)\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n\\n @util.preload_module('sqlalchemy.orm.dependency')\\n def _post_init(self) ->None:\\n dependency = util.preloaded.orm_dependency\\n if self.uselist is None:\\n self.uselist = self.direction is not MANYTOONE\\n if not self.viewonly:\\n self._dependency_processor = (dependency.DependencyProcessor.\\n from_relationship(self))\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n\\n @util.memoized_property\\n def _use_get(self) ->bool:\\n \\\"\\\"\\\"memoize the 'use_get' attribute of this RelationshipLoader's\\n lazyloader.\\\"\\\"\\\"\\n strategy = self._lazy_strategy\\n return strategy.use_get\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n\\n def merge(self, session: Session, source_state: InstanceState[Any],\\n source_dict: _InstanceDict, dest_state: InstanceState[Any],\\n dest_dict: _InstanceDict, load: bool, _recursive: Dict[Any, object],\\n _resolve_conflict_map: Dict[_IdentityKeyType[Any], object]) ->None:\\n if load:\\n for r in self._reverse_property:\\n if (source_state, r) in _recursive:\\n return\\n if 'merge' not in self._cascade:\\n return\\n if self.key not in source_dict:\\n return\\n if self.uselist:\\n impl = source_state.get_impl(self.key)\\n assert is_has_collection_adapter(impl)\\n instances_iterable = impl.get_collection(source_state, source_dict)\\n assert not instances_iterable.empty if impl.collection else True\\n if load:\\n dest_state.get_impl(self.key).get(dest_state, dest_dict,\\n passive=PassiveFlag.PASSIVE_MERGE)\\n dest_list = []\\n for current in instances_iterable:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n if obj is not None:\\n dest_list.append(obj)\\n if not load:\\n coll = attributes.init_state_collection(dest_state,\\n dest_dict, self.key)\\n for c in dest_list:\\n coll.append_without_event(c)\\n else:\\n dest_impl = dest_state.get_impl(self.key)\\n assert is_has_collection_adapter(dest_impl)\\n dest_impl.set(dest_state, dest_dict, dest_list, _adapt=\\n False, passive=PassiveFlag.PASSIVE_MERGE)\\n else:\\n current = source_dict[self.key]\\n if current is not None:\\n current_state = attributes.instance_state(current)\\n current_dict = attributes.instance_dict(current)\\n _recursive[current_state, self] = True\\n obj = session._merge(current_state, current_dict, load=load,\\n _recursive=_recursive, _resolve_conflict_map=\\n _resolve_conflict_map)\\n else:\\n obj = None\\n if not load:\\n dest_dict[self.key] = obj\\n else:\\n dest_state.get_impl(self.key).set(dest_state, dest_dict,\\n obj, None)\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n\\n @property\\n def _clsregistry_resolve_name(self) ->Callable[[str], Callable[[],\\n Union[Type[Any], Table, _ModNS]]]:\\n return self._clsregistry_resolvers[0]\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n\\n @util.memoized_property\\n def mapper(self) ->Mapper[_T]:\\n \\\"\\\"\\\"Return the targeted :class:`_orm.Mapper` for this\\n :class:`.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n return self.entity.mapper\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n\\n @property\\n def _effective_sync_backref(self) ->bool:\\n if self.viewonly:\\n return False\\n else:\\n return self.sync_backref is not False\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n\\n def _create_joins(self, source_polymorphic: bool=False,\\n source_selectable: Optional[FromClause]=None, dest_selectable:\\n Optional[FromClause]=None, of_type_entity: Optional[\\n _InternalEntityType[Any]]=None, alias_secondary: bool=False,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()) ->Tuple[\\n ColumnElement[bool], Optional[ColumnElement[bool]], FromClause,\\n FromClause, Optional[FromClause], Optional[ClauseAdapter]]:\\n aliased = False\\n if alias_secondary and self.secondary is not None:\\n aliased = True\\n if source_selectable is None:\\n if source_polymorphic and self.parent.with_polymorphic:\\n source_selectable = self.parent._with_polymorphic_selectable\\n if of_type_entity:\\n dest_mapper = of_type_entity.mapper\\n if dest_selectable is None:\\n dest_selectable = of_type_entity.selectable\\n aliased = True\\n else:\\n dest_mapper = self.mapper\\n if dest_selectable is None:\\n dest_selectable = self.entity.selectable\\n if self.mapper.with_polymorphic:\\n aliased = True\\n if self._is_self_referential and source_selectable is None:\\n dest_selectable = dest_selectable._anonymous_fromclause()\\n aliased = True\\n elif dest_selectable is not self.mapper._with_polymorphic_selectable or self.mapper.with_polymorphic:\\n aliased = True\\n single_crit = dest_mapper._single_table_criterion\\n aliased = aliased or source_selectable is not None and (\\n source_selectable is not self.parent.\\n _with_polymorphic_selectable or source_selectable._is_subquery)\\n (primaryjoin, secondaryjoin, secondary, target_adapter, dest_selectable\\n ) = (self._join_condition.join_targets(source_selectable,\\n dest_selectable, aliased, single_crit, extra_criteria))\\n if source_selectable is None:\\n source_selectable = self.parent.local_table\\n if dest_selectable is None:\\n dest_selectable = self.entity.local_table\\n return (primaryjoin, secondaryjoin, source_selectable,\\n dest_selectable, secondary, target_adapter)\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n\\n @staticmethod\\n def _check_sync_backref(rel_a: RelationshipProperty[Any], rel_b:\\n RelationshipProperty[Any]) ->None:\\n if rel_a.viewonly and rel_b.sync_backref:\\n raise sa_exc.InvalidRequestError(\\n 'Relationship %s cannot specify sync_backref=True since %s includes viewonly=True.'\\n % (rel_b, rel_a))\\n if (rel_a.viewonly and not rel_b.viewonly and rel_b.sync_backref is not\\n False):\\n rel_b.sync_backref = False\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n\\n def _optimized_compare(self, state: Any, value_is_parent: bool=False,\\n adapt_source: Optional[_CoreAdapterProto]=None, alias_secondary:\\n bool=True) ->ColumnElement[bool]:\\n if state is not None:\\n try:\\n state = inspect(state)\\n except sa_exc.NoInspectionAvailable:\\n state = None\\n if state is None or not getattr(state, 'is_instance', False):\\n raise sa_exc.ArgumentError(\\n 'Mapped instance expected for relationship comparison to object. Classes, queries and other SQL elements are not accepted in this context; for comparison with a subquery, use %s.has(**criteria).'\\n % self)\\n reverse_direction = not value_is_parent\\n if state is None:\\n return self._lazy_none_clause(reverse_direction, adapt_source=\\n adapt_source)\\n if not reverse_direction:\\n criterion, bind_to_col = (self._lazy_strategy._lazywhere, self.\\n _lazy_strategy._bind_to_col)\\n else:\\n criterion, bind_to_col = (self._lazy_strategy._rev_lazywhere,\\n self._lazy_strategy._rev_bind_to_col)\\n if reverse_direction:\\n mapper = self.mapper\\n else:\\n mapper = self.parent\\n dict_ = attributes.instance_dict(state.obj())\\n\\n def visit_bindparam(bindparam: BindParameter[Any]) ->None:\\n if bindparam._identifying_key in bind_to_col:\\n bindparam.callable = self._get_attr_w_warn_on_none(mapper,\\n state, dict_, bind_to_col[bindparam._identifying_key])\\n if self.secondary is not None and alias_secondary:\\n criterion = ClauseAdapter(self.secondary._anonymous_fromclause()\\n ).traverse(criterion)\\n criterion = visitors.cloned_traverse(criterion, {}, {'bindparam':\\n visit_bindparam})\\n if adapt_source:\\n criterion = adapt_source(criterion)\\n return criterion\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _is_self_referential(self) ->bool:\\n return self.mapper.common_parent(self.parent)\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n\\n def do_init(self) ->None:\\n self._check_conflicts()\\n self._process_dependent_arguments()\\n self._setup_entity()\\n self._setup_registry_dependencies()\\n self._setup_join_conditions()\\n self._check_cascade_settings(self._cascade)\\n self._post_init()\\n self._generate_backref()\\n self._join_condition._warn_for_conflicting_sync_targets()\\n super().do_init()\\n self._lazy_strategy = cast('LazyLoader', self._get_strategy(((\\n 'lazy', 'select'),)))\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def entity(self) ->_InternalEntityType[_T]:\\n \\\"\\\"\\\"Return the target mapped entity, which is an inspect() of the\\n class or aliased class that is referred towards.\\n\\n \\\"\\\"\\\"\\n self.parent._check_configure()\\n return self.entity\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n\\n def _with_parent(self, instance: object, alias_secondary: bool=True,\\n from_entity: Optional[_EntityType[Any]]=None) ->ColumnElement[bool]:\\n assert instance is not None\\n adapt_source: Optional[_CoreAdapterProto] = None\\n if from_entity is not None:\\n insp: Optional[_InternalEntityType[Any]] = inspect(from_entity)\\n assert insp is not None\\n if insp_is_aliased_class(insp):\\n adapt_source = insp._adapter.adapt_clause\\n return self._optimized_compare(instance, value_is_parent=True,\\n adapt_source=adapt_source, alias_secondary=alias_secondary)\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n\\n def __init__(self, argument: Optional[_RelationshipArgumentType[_T]]=\\n None, secondary: Optional[_RelationshipSecondaryArgument]=None, *,\\n uselist: Optional[bool]=None, collection_class: Optional[Union[Type\\n [Collection[Any]], Callable[[], Collection[Any]]]]=None,\\n primaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n secondaryjoin: Optional[_RelationshipJoinConditionArgument]=None,\\n back_populates: Optional[str]=None, order_by: _ORMOrderByArgument=\\n False, backref: Optional[ORMBackrefArgument]=None, overlaps:\\n Optional[str]=None, post_update: bool=False, cascade: str=\\n 'save-update, merge', viewonly: bool=False, attribute_options:\\n Optional[_AttributeOptions]=None, lazy: _LazyLoadArgumentType=\\n 'select', passive_deletes: Union[Literal['all'], bool]=False,\\n passive_updates: bool=True, active_history: bool=False,\\n enable_typechecks: bool=True, foreign_keys: Optional[\\n _ORMColCollectionArgument]=None, remote_side: Optional[\\n _ORMColCollectionArgument]=None, join_depth: Optional[int]=None,\\n comparator_factory: Optional[Type[RelationshipProperty.Comparator[\\n Any]]]=None, single_parent: bool=False, innerjoin: bool=False,\\n distinct_target_key: Optional[bool]=None, load_on_pending: bool=\\n False, query_class: Optional[Type[Query[Any]]]=None, info: Optional\\n [_InfoType]=None, omit_join: Literal[None, False]=None,\\n sync_backref: Optional[bool]=None, doc: Optional[str]=None,\\n bake_queries: Literal[True]=True, cascade_backrefs: Literal[False]=\\n False, _local_remote_pairs: Optional[_ColumnPairs]=None,\\n _legacy_inactive_history_style: bool=False):\\n super().__init__(attribute_options=attribute_options)\\n self.uselist = uselist\\n self.argument = argument\\n self._init_args = _RelationshipArgs(_RelationshipArg('secondary',\\n secondary, None), _RelationshipArg('primaryjoin', primaryjoin,\\n None), _RelationshipArg('secondaryjoin', secondaryjoin, None),\\n _RelationshipArg('order_by', order_by, None), _RelationshipArg(\\n 'foreign_keys', foreign_keys, None), _RelationshipArg(\\n 'remote_side', remote_side, None))\\n self.post_update = post_update\\n self.viewonly = viewonly\\n if viewonly:\\n self._warn_for_persistence_only_flags(passive_deletes=\\n passive_deletes, passive_updates=passive_updates,\\n enable_typechecks=enable_typechecks, active_history=\\n active_history, cascade_backrefs=cascade_backrefs)\\n if viewonly and sync_backref:\\n raise sa_exc.ArgumentError(\\n 'sync_backref and viewonly cannot both be True')\\n self.sync_backref = sync_backref\\n self.lazy = lazy\\n self.single_parent = single_parent\\n self.collection_class = collection_class\\n self.passive_deletes = passive_deletes\\n if cascade_backrefs:\\n raise sa_exc.ArgumentError(\\n \\\"The 'cascade_backrefs' parameter passed to relationship() may only be set to False.\\\"\\n )\\n self.passive_updates = passive_updates\\n self.enable_typechecks = enable_typechecks\\n self.query_class = query_class\\n self.innerjoin = innerjoin\\n self.distinct_target_key = distinct_target_key\\n self.doc = doc\\n self.active_history = active_history\\n self._legacy_inactive_history_style = _legacy_inactive_history_style\\n self.join_depth = join_depth\\n if omit_join:\\n util.warn(\\n 'setting omit_join to True is not supported; selectin loading of this relationship may not work correctly if this flag is set explicitly. omit_join optimization is automatically detected for conditions under which it is supported.'\\n )\\n self.omit_join = omit_join\\n self.local_remote_pairs = _local_remote_pairs\\n self.load_on_pending = load_on_pending\\n self.comparator_factory = (comparator_factory or\\n RelationshipProperty.Comparator)\\n util.set_creation_order(self)\\n if info is not None:\\n self.info.update(info)\\n self.strategy_key = ('lazy', self.lazy),\\n self._reverse_property: Set[RelationshipProperty[Any]] = set()\\n if overlaps:\\n self._overlaps = set(re.split('\\\\\\\\s*,\\\\\\\\s*', overlaps))\\n else:\\n self._overlaps = ()\\n self.cascade = cascade\\n self.back_populates = back_populates\\n if self.back_populates:\\n if backref:\\n raise sa_exc.ArgumentError(\\n 'backref and back_populates keyword arguments are mutually exclusive'\\n )\\n self.backref = None\\n else:\\n self.backref = backref\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n\\n @util.preload_module('sqlalchemy.orm.mapper')\\n def _setup_entity(self, __argument: Any=None) ->None:\\n if 'entity' in self.__dict__:\\n return\\n mapperlib = util.preloaded.orm_mapper\\n if __argument:\\n argument = __argument\\n else:\\n argument = self.argument\\n resolved_argument: _ExternalEntityType[Any]\\n if isinstance(argument, str):\\n resolved_argument = cast('_ExternalEntityType[Any]', self.\\n _clsregistry_resolve_name(argument)())\\n elif callable(argument) and not isinstance(argument, (type,\\n mapperlib.Mapper)):\\n resolved_argument = argument()\\n else:\\n resolved_argument = argument\\n entity: _InternalEntityType[Any]\\n if isinstance(resolved_argument, type):\\n entity = class_mapper(resolved_argument, configure=False)\\n else:\\n try:\\n entity = inspect(resolved_argument)\\n except sa_exc.NoInspectionAvailable:\\n entity = None\\n if not hasattr(entity, 'mapper'):\\n raise sa_exc.ArgumentError(\\n \\\"relationship '%s' expects a class or a mapper argument (received: %s)\\\"\\n % (self.key, type(resolved_argument)))\\n self.entity = entity\\n self.target = self.entity.persist_selectable\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n\\n @property\\n def _clsregistry_resolve_arg(self) ->Callable[[str, bool], _class_resolver\\n ]:\\n return self._clsregistry_resolvers[1]\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n\\n def _value_as_iterable(self, state: InstanceState[_O], dict_:\\n _InstanceDict, key: str, passive: PassiveFlag=PassiveFlag.PASSIVE_OFF\\n ) ->Sequence[Tuple[InstanceState[_O], _O]]:\\n \\\"\\\"\\\"Return a list of tuples (state, obj) for the given\\n key.\\n\\n returns an empty list if the value is None/empty/PASSIVE_NO_RESULT\\n \\\"\\\"\\\"\\n impl = state.manager[key].impl\\n x = impl.get(state, dict_, passive=passive)\\n if x is LoaderCallableStatus.PASSIVE_NO_RESULT or x is None:\\n return []\\n elif is_has_collection_adapter(impl):\\n return [(attributes.instance_state(o), o) for o in impl.\\n get_collection(state, dict_, x, passive=passive)]\\n else:\\n return [(attributes.instance_state(x), x)]\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n\\n def _generate_backref(self) ->None:\\n \\\"\\\"\\\"Interpret the 'backref' instruction to create a\\n :func:`_orm.relationship` complementary to this one.\\\"\\\"\\\"\\n if self.parent.non_primary:\\n return\\n if self.backref is not None and not self.back_populates:\\n kwargs: Dict[str, Any]\\n if isinstance(self.backref, str):\\n backref_key, kwargs = self.backref, {}\\n else:\\n backref_key, kwargs = self.backref\\n mapper = self.mapper.primary_mapper()\\n if not mapper.concrete:\\n check = set(mapper.iterate_to_root()).union(mapper.\\n self_and_descendants)\\n for m in check:\\n if m.has_property(backref_key) and not m.concrete:\\n raise sa_exc.ArgumentError(\\n \\\"Error creating backref '%s' on relationship '%s': property of that name exists on mapper '%s'\\\"\\n % (backref_key, self, m))\\n if self.secondary is not None:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n secondaryjoin_minus_local)\\n sj = kwargs.pop('secondaryjoin', self._join_condition.\\n primaryjoin_minus_local)\\n else:\\n pj = kwargs.pop('primaryjoin', self._join_condition.\\n primaryjoin_reverse_remote)\\n sj = kwargs.pop('secondaryjoin', None)\\n if sj:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't assign 'secondaryjoin' on a backref against a non-secondary relationship.\\\"\\n )\\n foreign_keys = kwargs.pop('foreign_keys', self.\\n _user_defined_foreign_keys)\\n parent = self.parent.primary_mapper()\\n kwargs.setdefault('viewonly', self.viewonly)\\n kwargs.setdefault('post_update', self.post_update)\\n kwargs.setdefault('passive_updates', self.passive_updates)\\n kwargs.setdefault('sync_backref', self.sync_backref)\\n self.back_populates = backref_key\\n relationship = RelationshipProperty(parent, self.secondary,\\n primaryjoin=pj, secondaryjoin=sj, foreign_keys=foreign_keys,\\n back_populates=self.key, **kwargs)\\n mapper._configure_property(backref_key, relationship,\\n warn_for_existing=True)\\n if self.back_populates:\\n self._add_reverse_property(self.back_populates)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n\\n @cascade.setter\\n def cascade(self, cascade: Union[str, CascadeOptions]) ->None:\\n self._set_cascade(cascade)\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n <function token>\\n\\n def _set_cascade(self, cascade_arg: Union[str, CascadeOptions]) ->None:\\n cascade = CascadeOptions(cascade_arg)\\n if self.viewonly:\\n cascade = CascadeOptions(cascade.intersection(CascadeOptions.\\n _viewonly_cascades))\\n if 'mapper' in self.__dict__:\\n self._check_cascade_settings(cascade)\\n self._cascade = cascade\\n if self._dependency_processor:\\n self._dependency_processor.cascade = cascade\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n\\n def _setup_join_conditions(self) ->None:\\n self._join_condition = jc = JoinCondition(parent_persist_selectable\\n =self.parent.persist_selectable, child_persist_selectable=self.\\n entity.persist_selectable, parent_local_selectable=self.parent.\\n local_table, child_local_selectable=self.entity.local_table,\\n primaryjoin=self._init_args.primaryjoin.resolved, secondary=\\n self._init_args.secondary.resolved, secondaryjoin=self.\\n _init_args.secondaryjoin.resolved, parent_equivalents=self.\\n parent._equivalent_columns, child_equivalents=self.mapper.\\n _equivalent_columns, consider_as_foreign_keys=self.\\n _user_defined_foreign_keys, local_remote_pairs=self.\\n local_remote_pairs, remote_side=self.remote_side,\\n self_referential=self._is_self_referential, prop=self,\\n support_sync=not self.viewonly, can_be_synced_fn=self.\\n _columns_are_mapped)\\n self.primaryjoin = jc.primaryjoin\\n self.secondaryjoin = jc.secondaryjoin\\n self.secondary = jc.secondary\\n self.direction = jc.direction\\n self.local_remote_pairs = jc.local_remote_pairs\\n self.remote_side = jc.remote_columns\\n self.local_columns = jc.local_columns\\n self.synchronize_pairs = jc.synchronize_pairs\\n self._calculated_foreign_keys = jc.foreign_key_columns\\n self.secondary_synchronize_pairs = jc.secondary_synchronize_pairs\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_conflicts(self) ->None:\\n \\\"\\\"\\\"Test that this relationship is legal, warn about\\n inheritance conflicts.\\\"\\\"\\\"\\n if self.parent.non_primary and not class_mapper(self.parent.class_,\\n configure=False).has_property(self.key):\\n raise sa_exc.ArgumentError(\\n \\\"Attempting to assign a new relationship '%s' to a non-primary mapper on class '%s'. New relationships can only be added to the primary mapper, i.e. the very first mapper created for class '%s' \\\"\\n % (self.key, self.parent.class_.__name__, self.parent.\\n class_.__name__))\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @property\\n def cascade(self) ->CascadeOptions:\\n \\\"\\\"\\\"Return the current cascade setting for this\\n :class:`.RelationshipProperty`.\\n \\\"\\\"\\\"\\n return self._cascade\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def __str__(self) ->str:\\n return str(self.parent.class_.__name__) + '.' + self.key\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _process_dependent_arguments(self) ->None:\\n \\\"\\\"\\\"Convert incoming configuration arguments to their\\n proper form.\\n\\n Callables are resolved, ORM annotations removed.\\n\\n \\\"\\\"\\\"\\n init_args = self._init_args\\n for attr in ('order_by', 'primaryjoin', 'secondaryjoin',\\n 'secondary', 'foreign_keys', 'remote_side'):\\n rel_arg = getattr(init_args, attr)\\n rel_arg._resolve_against_registry(self._clsregistry_resolvers[1])\\n for attr in ('primaryjoin', 'secondaryjoin'):\\n rel_arg = getattr(init_args, attr)\\n val = rel_arg.resolved\\n if val is not None:\\n rel_arg.resolved = _orm_deannotate(coercions.expect(roles.\\n ColumnArgumentRole, val, argname=attr))\\n secondary = init_args.secondary.resolved\\n if secondary is not None and _is_mapped_class(secondary):\\n raise sa_exc.ArgumentError(\\n \\\"secondary argument %s passed to to relationship() %s must be a Table object or other FROM clause; can't send a mapped class directly as rows in 'secondary' are persisted independently of a class that is mapped to that same table.\\\"\\n % (secondary, self))\\n if (init_args.order_by.resolved is not False and init_args.order_by\\n .resolved is not None):\\n self.order_by = tuple(coercions.expect(roles.ColumnArgumentRole,\\n x, argname='order_by') for x in util.to_list(init_args.\\n order_by.resolved))\\n else:\\n self.order_by = False\\n self._user_defined_foreign_keys = util.column_set(coercions.expect(\\n roles.ColumnArgumentRole, x, argname='foreign_keys') for x in\\n util.to_column_set(init_args.foreign_keys.resolved))\\n self.remote_side = util.column_set(coercions.expect(roles.\\n ColumnArgumentRole, x, argname='remote_side') for x in util.\\n to_column_set(init_args.remote_side.resolved))\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _persists_for(self, mapper: Mapper[Any]) ->bool:\\n \\\"\\\"\\\"Return True if this property will persist values on behalf\\n of the given mapper.\\n\\n \\\"\\\"\\\"\\n return self.key in mapper.relationships and mapper.relationships[self\\n .key] is self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def cascade_iterator(self, type_: str, state: InstanceState[Any], dict_:\\n _InstanceDict, visited_states: Set[InstanceState[Any]], halt_on:\\n Optional[Callable[[InstanceState[Any]], bool]]=None) ->Iterator[Tuple\\n [Any, Mapper[Any], InstanceState[Any], _InstanceDict]]:\\n if type_ != 'delete' or self.passive_deletes:\\n passive = PassiveFlag.PASSIVE_NO_INITIALIZE\\n else:\\n passive = PassiveFlag.PASSIVE_OFF | PassiveFlag.NO_RAISE\\n if type_ == 'save-update':\\n tuples = state.manager[self.key].impl.get_all_pending(state, dict_)\\n else:\\n tuples = self._value_as_iterable(state, dict_, self.key,\\n passive=passive)\\n skip_pending = (type_ == 'refresh-expire' and 'delete-orphan' not in\\n self._cascade)\\n for instance_state, c in tuples:\\n if instance_state in visited_states:\\n continue\\n if c is None:\\n continue\\n assert instance_state is not None\\n instance_dict = attributes.instance_dict(c)\\n if halt_on and halt_on(instance_state):\\n continue\\n if skip_pending and not instance_state.key:\\n continue\\n instance_mapper = instance_state.manager.mapper\\n if not instance_mapper.isa(self.mapper.class_manager.mapper):\\n raise AssertionError(\\n \\\"Attribute '%s' on class '%s' doesn't handle objects of type '%s'\\\"\\n % (self.key, self.parent.class_, c.__class__))\\n visited_states.add(instance_state)\\n yield c, instance_mapper, instance_state, instance_dict\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\n@log.class_logger\\nclass RelationshipProperty(_IntrospectsAnnotations, StrategizedProperty[_T],\\n log.Identified):\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n <docstring token>\\n <assignment token>\\n <assignment token>\\n _overlaps: Sequence[str]\\n _lazy_strategy: LazyLoader\\n <assignment token>\\n _dependency_processor: Optional[DependencyProcessor] = None\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n _join_condition: JoinCondition\\n order_by: Union[Literal[False], Tuple[ColumnElement[Any], ...]]\\n _user_defined_foreign_keys: Set[ColumnElement[Any]]\\n _calculated_foreign_keys: Set[ColumnElement[Any]]\\n remote_side: Set[ColumnElement[Any]]\\n local_columns: Set[ColumnElement[Any]]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: Optional[_ColumnPairs]\\n local_remote_pairs: Optional[_ColumnPairs]\\n direction: RelationshipDirection\\n _init_args: _RelationshipArgs\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n class Comparator(util.MemoizedSlots, PropComparator[_PT]):\\n \\\"\\\"\\\"Produce boolean, comparison, and other operators for\\n :class:`.RelationshipProperty` attributes.\\n\\n See the documentation for :class:`.PropComparator` for a brief\\n overview of ORM level operator definition.\\n\\n .. seealso::\\n\\n :class:`.PropComparator`\\n\\n :class:`.ColumnProperty.Comparator`\\n\\n :class:`.ColumnOperators`\\n\\n :ref:`types_operators`\\n\\n :attr:`.TypeEngine.comparator_factory`\\n\\n \\\"\\\"\\\"\\n __slots__ = ('entity', 'mapper', 'property', '_of_type',\\n '_extra_criteria')\\n prop: RODescriptorReference[RelationshipProperty[_PT]]\\n _of_type: Optional[_EntityType[_PT]]\\n\\n def __init__(self, prop: RelationshipProperty[_PT], parentmapper:\\n _InternalEntityType[Any], adapt_to_entity: Optional[AliasedInsp\\n [Any]]=None, of_type: Optional[_EntityType[_PT]]=None,\\n extra_criteria: Tuple[ColumnElement[bool], ...]=()):\\n \\\"\\\"\\\"Construction of :class:`.RelationshipProperty.Comparator`\\n is internal to the ORM's attribute mechanics.\\n\\n \\\"\\\"\\\"\\n self.prop = prop\\n self._parententity = parentmapper\\n self._adapt_to_entity = adapt_to_entity\\n if of_type:\\n self._of_type = of_type\\n else:\\n self._of_type = None\\n self._extra_criteria = extra_criteria\\n\\n def adapt_to_entity(self, adapt_to_entity: AliasedInsp[Any]\\n ) ->RelationshipProperty.Comparator[Any]:\\n return self.__class__(self.prop, self._parententity,\\n adapt_to_entity=adapt_to_entity, of_type=self._of_type)\\n entity: _InternalEntityType[_PT]\\n \\\"\\\"\\\"The target entity referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is either a :class:`_orm.Mapper` or :class:`.AliasedInsp`\\n object.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n mapper: Mapper[_PT]\\n \\\"\\\"\\\"The target :class:`_orm.Mapper` referred to by this\\n :class:`.RelationshipProperty.Comparator`.\\n\\n This is the \\\"target\\\" or \\\"remote\\\" side of the\\n :func:`_orm.relationship`.\\n\\n \\\"\\\"\\\"\\n\\n def _memoized_attr_entity(self) ->_InternalEntityType[_PT]:\\n if self._of_type:\\n return inspect(self._of_type)\\n else:\\n return self.prop.entity\\n\\n def _memoized_attr_mapper(self) ->Mapper[_PT]:\\n return self.entity.mapper\\n\\n def _source_selectable(self) ->FromClause:\\n if self._adapt_to_entity:\\n return self._adapt_to_entity.selectable\\n else:\\n return self.property.parent._with_polymorphic_selectable\\n\\n def __clause_element__(self) ->ColumnElement[bool]:\\n adapt_from = self._source_selectable()\\n if self._of_type:\\n of_type_entity = inspect(self._of_type)\\n else:\\n of_type_entity = None\\n pj, sj, source, dest, secondary, target_adapter = (self.prop.\\n _create_joins(source_selectable=adapt_from,\\n source_polymorphic=True, of_type_entity=of_type_entity,\\n alias_secondary=True, extra_criteria=self._extra_criteria))\\n if sj is not None:\\n return pj & sj\\n else:\\n return pj\\n\\n def of_type(self, class_: _EntityType[Any]) ->PropComparator[_PT]:\\n \\\"\\\"\\\"Redefine this object in terms of a polymorphic subclass.\\n\\n See :meth:`.PropComparator.of_type` for an example.\\n\\n\\n \\\"\\\"\\\"\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=class_, extra_criteria=self._extra_criteria)\\n\\n def and_(self, *criteria: _ColumnExpressionArgument[bool]\\n ) ->PropComparator[Any]:\\n \\\"\\\"\\\"Add AND criteria.\\n\\n See :meth:`.PropComparator.and_` for an example.\\n\\n .. versionadded:: 1.4\\n\\n \\\"\\\"\\\"\\n exprs = tuple(coercions.expect(roles.WhereHavingRole, clause) for\\n clause in util.coerce_generator_arg(criteria))\\n return RelationshipProperty.Comparator(self.prop, self.\\n _parententity, adapt_to_entity=self._adapt_to_entity,\\n of_type=self._of_type, extra_criteria=self._extra_criteria +\\n exprs)\\n\\n def in_(self, other: Any) ->NoReturn:\\n \\\"\\\"\\\"Produce an IN clause - this is not implemented\\n for :func:`_orm.relationship`-based attributes at this time.\\n\\n \\\"\\\"\\\"\\n raise NotImplementedError(\\n 'in_() not yet supported for relationships. For a simple many-to-one, use in_() against the set of foreign key values.'\\n )\\n __hash__ = None\\n\\n def __eq__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``==`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop == <some object>\\n\\n this will typically produce a\\n clause such as::\\n\\n mytable.related_id == <some id>\\n\\n Where ``<some id>`` is the primary key of the given\\n object.\\n\\n The ``==`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use :meth:`~.Relationship.Comparator.contains`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce a NOT EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction in [ONETOMANY, MANYTOMANY]:\\n return ~self._criterion_exists()\\n else:\\n return _orm_annotate(self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.property._optimized_compare(other,\\n adapt_source=self.adapter))\\n\\n def _criterion_exists(self, criterion: Optional[\\n _ColumnExpressionArgument[bool]]=None, **kwargs: Any) ->Exists:\\n where_criteria = coercions.expect(roles.WhereHavingRole, criterion\\n ) if criterion is not None else None\\n if getattr(self, '_of_type', None):\\n info: Optional[_InternalEntityType[Any]] = inspect(self.\\n _of_type)\\n assert info is not None\\n target_mapper, to_selectable, is_aliased_class = (info.\\n mapper, info.selectable, info.is_aliased_class)\\n if self.property._is_self_referential and not is_aliased_class:\\n to_selectable = to_selectable._anonymous_fromclause()\\n single_crit = target_mapper._single_table_criterion\\n if single_crit is not None:\\n if where_criteria is not None:\\n where_criteria = single_crit & where_criteria\\n else:\\n where_criteria = single_crit\\n else:\\n is_aliased_class = False\\n to_selectable = None\\n if self.adapter:\\n source_selectable = self._source_selectable()\\n else:\\n source_selectable = None\\n pj, sj, source, dest, secondary, target_adapter = (self.\\n property._create_joins(dest_selectable=to_selectable,\\n source_selectable=source_selectable))\\n for k in kwargs:\\n crit = getattr(self.property.mapper.class_, k) == kwargs[k]\\n if where_criteria is None:\\n where_criteria = crit\\n else:\\n where_criteria = where_criteria & crit\\n if sj is not None:\\n j = _orm_annotate(pj) & sj\\n else:\\n j = _orm_annotate(pj, exclude=self.property.remote_side)\\n if (where_criteria is not None and target_adapter and not\\n is_aliased_class):\\n where_criteria = target_adapter.traverse(where_criteria)\\n if where_criteria is not None:\\n where_criteria = where_criteria._annotate({\\n 'no_replacement_traverse': True})\\n crit = j & sql.True_._ifnone(where_criteria)\\n if secondary is not None:\\n ex = sql.exists(1).where(crit).select_from(dest, secondary\\n ).correlate_except(dest, secondary)\\n else:\\n ex = sql.exists(1).where(crit).select_from(dest\\n ).correlate_except(dest)\\n return ex\\n\\n def any(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a collection against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.any(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE related.my_id=my_table.id\\n AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.any` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.any` is particularly\\n useful for testing for empty collections::\\n\\n session.query(MyClass).filter(\\n ~MyClass.somereference.any()\\n )\\n\\n will produce::\\n\\n SELECT * FROM my_table WHERE\\n NOT (EXISTS (SELECT 1 FROM related WHERE\\n related.my_id=my_table.id))\\n\\n :meth:`~.Relationship.Comparator.any` is only\\n valid for collections, i.e. a :func:`_orm.relationship`\\n that has ``uselist=True``. For scalar references,\\n use :meth:`~.Relationship.Comparator.has`.\\n\\n \\\"\\\"\\\"\\n if not self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'any()' not implemented for scalar attributes. Use has().\\\"\\n )\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def has(self, criterion: Optional[_ColumnExpressionArgument[bool]]=\\n None, **kwargs: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Produce an expression that tests a scalar reference against\\n particular criterion, using EXISTS.\\n\\n An expression like::\\n\\n session.query(MyClass).filter(\\n MyClass.somereference.has(SomeRelated.x==2)\\n )\\n\\n\\n Will produce a query like::\\n\\n SELECT * FROM my_table WHERE\\n EXISTS (SELECT 1 FROM related WHERE\\n related.id==my_table.related_id AND related.x=2)\\n\\n Because :meth:`~.Relationship.Comparator.has` uses\\n a correlated subquery, its performance is not nearly as\\n good when compared against large target tables as that of\\n using a join.\\n\\n :meth:`~.Relationship.Comparator.has` is only\\n valid for scalar references, i.e. a :func:`_orm.relationship`\\n that has ``uselist=False``. For collection references,\\n use :meth:`~.Relationship.Comparator.any`.\\n\\n \\\"\\\"\\\"\\n if self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'has()' not implemented for collections. Use any().\\\")\\n return self._criterion_exists(criterion, **kwargs)\\n\\n def contains(self, other: _ColumnExpressionArgument[Any], **kwargs: Any\\n ) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return a simple expression that tests a collection for\\n containment of a particular item.\\n\\n :meth:`~.Relationship.Comparator.contains` is\\n only valid for a collection, i.e. a\\n :func:`_orm.relationship` that implements\\n one-to-many or many-to-many with ``uselist=True``.\\n\\n When used in a simple one-to-many context, an\\n expression like::\\n\\n MyClass.contains(other)\\n\\n Produces a clause like::\\n\\n mytable.id == <some id>\\n\\n Where ``<some id>`` is the value of the foreign key\\n attribute on ``other`` which refers to the primary\\n key of its parent object. From this it follows that\\n :meth:`~.Relationship.Comparator.contains` is\\n very useful when used with simple one-to-many\\n operations.\\n\\n For many-to-many operations, the behavior of\\n :meth:`~.Relationship.Comparator.contains`\\n has more caveats. The association table will be\\n rendered in the statement, producing an \\\"implicit\\\"\\n join, that is, includes multiple tables in the FROM\\n clause which are equated in the WHERE clause::\\n\\n query(MyClass).filter(MyClass.contains(other))\\n\\n Produces a query like::\\n\\n SELECT * FROM my_table, my_association_table AS\\n my_association_table_1 WHERE\\n my_table.id = my_association_table_1.parent_id\\n AND my_association_table_1.child_id = <some id>\\n\\n Where ``<some id>`` would be the primary key of\\n ``other``. From the above, it is clear that\\n :meth:`~.Relationship.Comparator.contains`\\n will **not** work with many-to-many collections when\\n used in queries that move beyond simple AND\\n conjunctions, such as multiple\\n :meth:`~.Relationship.Comparator.contains`\\n expressions joined by OR. In such cases subqueries or\\n explicit \\\"outer joins\\\" will need to be used instead.\\n See :meth:`~.Relationship.Comparator.any` for\\n a less-performant alternative using EXISTS, or refer\\n to :meth:`_query.Query.outerjoin`\\n as well as :ref:`orm_queryguide_joins`\\n for more details on constructing outer joins.\\n\\n kwargs may be ignored by this operator but are required for API\\n conformance.\\n \\\"\\\"\\\"\\n if not self.prop.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"'contains' not implemented for scalar attributes. Use ==\\\"\\n )\\n clause = self.prop._optimized_compare(other, adapt_source=self.\\n adapter)\\n if self.prop.secondaryjoin is not None:\\n clause.negation_clause = self.__negated_contains_or_equals(\\n other)\\n return clause\\n\\n def __negated_contains_or_equals(self, other: Any) ->ColumnElement[bool\\n ]:\\n if self.prop.direction == MANYTOONE:\\n state = attributes.instance_state(other)\\n\\n def state_bindparam(local_col: ColumnElement[Any], state:\\n InstanceState[Any], remote_col: ColumnElement[Any]\\n ) ->BindParameter[Any]:\\n dict_ = state.dict\\n return sql.bindparam(local_col.key, type_=local_col.\\n type, unique=True, callable_=self.prop.\\n _get_attr_w_warn_on_none(self.prop.mapper, state,\\n dict_, remote_col))\\n\\n def adapt(col: _CE) ->_CE:\\n if self.adapter:\\n return self.adapter(col)\\n else:\\n return col\\n if self.property._use_get:\\n return sql.and_(*[sql.or_(adapt(x) != state_bindparam(\\n adapt(x), state, y), adapt(x) == None) for x, y in\\n self.property.local_remote_pairs])\\n criterion = sql.and_(*[(x == y) for x, y in zip(self.property.\\n mapper.primary_key, self.property.mapper.\\n primary_key_from_instance(other))])\\n return ~self._criterion_exists(criterion)\\n\\n def __ne__(self, other: Any) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Implement the ``!=`` operator.\\n\\n In a many-to-one context, such as::\\n\\n MyClass.some_prop != <some object>\\n\\n This will typically produce a clause such as::\\n\\n mytable.related_id != <some id>\\n\\n Where ``<some id>`` is the primary key of the\\n given object.\\n\\n The ``!=`` operator provides partial functionality for non-\\n many-to-one comparisons:\\n\\n * Comparisons against collections are not supported.\\n Use\\n :meth:`~.Relationship.Comparator.contains`\\n in conjunction with :func:`_expression.not_`.\\n * Compared to a scalar one-to-many, will produce a\\n clause that compares the target columns in the parent to\\n the given target.\\n * Compared to a scalar many-to-many, an alias\\n of the association table will be rendered as\\n well, forming a natural join that is part of the\\n main body of the query. This will not work for\\n queries that go beyond simple AND conjunctions of\\n comparisons, such as those which use OR. Use\\n explicit joins, outerjoins, or\\n :meth:`~.Relationship.Comparator.has` in\\n conjunction with :func:`_expression.not_` for\\n more comprehensive non-many-to-one scalar\\n membership tests.\\n * Comparisons against ``None`` given in a one-to-many\\n or many-to-many context produce an EXISTS clause.\\n\\n \\\"\\\"\\\"\\n if other is None or isinstance(other, expression.Null):\\n if self.property.direction == MANYTOONE:\\n return _orm_annotate(~self.property._optimized_compare(\\n None, adapt_source=self.adapter))\\n else:\\n return self._criterion_exists()\\n elif self.property.uselist:\\n raise sa_exc.InvalidRequestError(\\n \\\"Can't compare a collection to an object or collection; use contains() to test for membership.\\\"\\n )\\n else:\\n return _orm_annotate(self.__negated_contains_or_equals(other))\\n\\n def _memoized_attr_property(self) ->RelationshipProperty[_PT]:\\n self.prop.parent._check_configure()\\n return self.prop\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n\\n @util.memoized_property\\n def _has_foreign_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'foreign')\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n\\n def _annotate_remote_secondary(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when 'secondary' is present.\\n\\n \\\"\\\"\\\"\\n assert self.secondary is not None\\n fixed_secondary = self.secondary\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if fixed_secondary.c.contains_column(element):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n assert self.secondaryjoin is not None\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, repl)\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n\\n def _determine_joins(self) ->None:\\n \\\"\\\"\\\"Determine the 'primaryjoin' and 'secondaryjoin' attributes,\\n if not passed to the constructor already.\\n\\n This is based on analysis of the foreign key relationships\\n between the parent and target mapped selectables.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None and self.secondary is None:\\n raise sa_exc.ArgumentError(\\n 'Property %s specified with secondary join condition but no secondary argument'\\n % self.prop)\\n try:\\n consider_as_foreign_keys = self.consider_as_foreign_keys or None\\n if self.secondary is not None:\\n if self.secondaryjoin is None:\\n self.secondaryjoin = join_condition(self.\\n child_persist_selectable, self.secondary, a_subset=\\n self.child_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n if self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.secondary, a_subset\\n =self.parent_local_selectable,\\n consider_as_foreign_keys=consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n elif self.primaryjoin_initial is None:\\n self.primaryjoin = join_condition(self.\\n parent_persist_selectable, self.\\n child_persist_selectable, a_subset=self.\\n parent_local_selectable, consider_as_foreign_keys=\\n consider_as_foreign_keys)\\n else:\\n self.primaryjoin = self.primaryjoin_initial\\n except sa_exc.NoForeignKeysError as nfe:\\n if self.secondary is not None:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables via secondary table '%s'. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify 'primaryjoin' and 'secondaryjoin' expressions.\\\"\\n % (self.prop, self.secondary)) from nfe\\n else:\\n raise sa_exc.NoForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are no foreign keys linking these tables. Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.\\\"\\n % self.prop) from nfe\\n except sa_exc.AmbiguousForeignKeysError as afe:\\n if self.secondary is not None:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables via secondary table '%s'. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference from the secondary table to each of the parent and child tables.\\\"\\n % (self.prop, self.secondary)) from afe\\n else:\\n raise sa_exc.AmbiguousForeignKeysError(\\n \\\"Could not determine join condition between parent/child tables on relationship %s - there are multiple foreign key paths linking the tables. Specify the 'foreign_keys' argument, providing a list of those columns which should be counted as containing a foreign key reference to the parent table.\\\"\\n % self.prop) from afe\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n\\n @property\\n def secondaryjoin_minus_local(self) ->ColumnElement[bool]:\\n assert self.secondaryjoin is not None\\n return _deep_deannotate(self.secondaryjoin, values=('local', 'remote'))\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n\\n def _annotate_remote_with_overlap(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables have some set of\\n tables in common, though is not a fully self-referential\\n relationship.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n binary.left, binary.right = proc_left_right(binary.left, binary\\n .right)\\n binary.right, binary.left = proc_left_right(binary.right,\\n binary.left)\\n check_entities = (self.prop is not None and self.prop.mapper is not\\n self.prop.parent)\\n\\n def proc_left_right(left: ColumnElement[Any], right: ColumnElement[Any]\\n ) ->Tuple[ColumnElement[Any], ColumnElement[Any]]:\\n if isinstance(left, expression.ColumnClause) and isinstance(right,\\n expression.ColumnClause):\\n if self.child_persist_selectable.c.contains_column(right\\n ) and self.parent_persist_selectable.c.contains_column(left\\n ):\\n right = right._annotate({'remote': True})\\n elif check_entities and right._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n right = right._annotate({'remote': True})\\n elif check_entities and left._annotations.get('parentmapper'\\n ) is self.prop.mapper:\\n left = left._annotate({'remote': True})\\n else:\\n self._warn_non_column_elements()\\n return left, right\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n\\n def _log_joins(self) ->None:\\n log = self.prop.logger\\n log.info('%s setup primary join %s', self.prop, self.primaryjoin)\\n log.info('%s setup secondary join %s', self.prop, self.secondaryjoin)\\n log.info('%s synchronize pairs [%s]', self.prop, ','.join(\\n '(%s => %s)' % (l, r) for l, r in self.synchronize_pairs))\\n log.info('%s secondary synchronize pairs [%s]', self.prop, ','.join\\n ('(%s => %s)' % (l, r) for l, r in self.\\n secondary_synchronize_pairs or []))\\n log.info('%s local/remote pairs [%s]', self.prop, ','.join(\\n '(%s / %s)' % (l, r) for l, r in self.local_remote_pairs))\\n log.info('%s remote columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.remote_columns))\\n log.info('%s local columns [%s]', self.prop, ','.join('%s' % col for\\n col in self.local_columns))\\n log.info('%s relationship direction %s', self.prop, self.direction)\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n\\n def _gather_columns_with_annotation(self, clause: ColumnElement[Any], *\\n annotation: Iterable[str]) ->Set[ColumnElement[Any]]:\\n annotation_set = set(annotation)\\n return {cast(ColumnElement[Any], col) for col in visitors.iterate(\\n clause, {}) if annotation_set.issubset(col._annotations)}\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n\\n @util.memoized_property\\n def foreign_key_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('foreign')\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n\\n def _check_remote_side(self) ->None:\\n if not self.local_remote_pairs:\\n raise sa_exc.ArgumentError(\\n 'Relationship %s could not determine any unambiguous local/remote column pairs based on join condition and remote_side arguments. Consider using the remote() annotation to accurately mark those elements of the join condition that are on the remote side of the relationship.'\\n % (self.prop,))\\n else:\\n not_target = util.column_set(self.parent_persist_selectable.c\\n ).difference(self.child_persist_selectable.c)\\n for _, rmt in self.local_remote_pairs:\\n if rmt in not_target:\\n util.warn(\\n \\\"Expression %s is marked as 'remote', but these column(s) are local to the local side. The remote() annotation is needed only for a self-referential relationship where both sides of the relationship refer to the same tables.\\\"\\n % (rmt,))\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n\\n def _annotate_local(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'local' annotations.\\n\\n This annotates all column elements found\\n simultaneously in the parent table\\n and the join condition that don't have a\\n 'remote' annotation set up from\\n _annotate_remote() or user-defined.\\n\\n \\\"\\\"\\\"\\n if self._has_annotation(self.primaryjoin, 'local'):\\n return\\n if self._local_remote_pairs:\\n local_side = util.column_set([l for l, r in self.\\n _local_remote_pairs])\\n else:\\n local_side = util.column_set(self.parent_persist_selectable.c)\\n\\n def locals_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' not in element._annotations and element in local_side:\\n return element._annotate({'local': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, locals_)\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n\\n def _refers_to_parent_table(self) ->bool:\\n \\\"\\\"\\\"Return True if the join condition contains column\\n comparisons where both columns are in both tables.\\n\\n \\\"\\\"\\\"\\n pt = self.parent_persist_selectable\\n mt = self.child_persist_selectable\\n result = False\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n nonlocal result\\n c, f = binary.left, binary.right\\n if isinstance(c, expression.ColumnClause) and isinstance(f,\\n expression.ColumnClause) and pt.is_derived_from(c.table\\n ) and pt.is_derived_from(f.table) and mt.is_derived_from(c.\\n table) and mt.is_derived_from(f.table):\\n result = True\\n visitors.traverse(self.primaryjoin, {}, {'binary': visit_binary})\\n return result\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n\\n def _warn_for_conflicting_sync_targets(self) ->None:\\n if not self.support_sync:\\n return\\n for from_, to_ in ([(from_, to_) for from_, to_ in self.\\n synchronize_pairs] + [(from_, to_) for from_, to_ in self.\\n secondary_synchronize_pairs]):\\n if to_ not in self._track_overlapping_sync_targets:\\n self._track_overlapping_sync_targets[to_\\n ] = weakref.WeakKeyDictionary({self.prop: from_})\\n else:\\n other_props = []\\n prop_to_from = self._track_overlapping_sync_targets[to_]\\n for pr, fr_ in prop_to_from.items():\\n if (not pr.mapper._dispose_called and pr not in self.\\n prop._reverse_property and pr.key not in self.prop.\\n _overlaps and self.prop.key not in pr._overlaps and\\n '__*' not in self.prop._overlaps and '__*' not in\\n pr._overlaps and not self.prop.parent.is_sibling(pr\\n .parent) and not self.prop.mapper.is_sibling(pr.\\n mapper) and not self.prop.parent.is_sibling(pr.\\n mapper) and not self.prop.mapper.is_sibling(pr.\\n parent) and (self.prop.key != pr.key or not self.\\n prop.parent.common_parent(pr.parent))):\\n other_props.append((pr, fr_))\\n if other_props:\\n util.warn(\\n 'relationship \\\\'%s\\\\' will copy column %s to column %s, which conflicts with relationship(s): %s. If this is not the intention, consider if these relationships should be linked with back_populates, or if viewonly=True should be applied to one or more if they are read-only. For the less common case that foreign key constraints are partially overlapping, the orm.foreign() annotation can be used to isolate the columns that should be written towards. To silence this warning, add the parameter \\\\'overlaps=\\\"%s\\\"\\\\' to the \\\\'%s\\\\' relationship.'\\n % (self.prop, from_, to_, ', '.join(sorted(\\n \\\"'%s' (copies %s to %s)\\\" % (pr, fr_, to_) for pr,\\n fr_ in other_props)), ','.join(sorted(pr.key for pr,\\n fr in other_props)), self.prop), code='qzyx')\\n self._track_overlapping_sync_targets[to_][self.prop] = from_\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n\\n def _gather_join_annotations(self, annotation: str) ->Set[ColumnElement\\n [Any]]:\\n s = set(self._gather_columns_with_annotation(self.primaryjoin,\\n annotation))\\n if self.secondaryjoin is not None:\\n s.update(self._gather_columns_with_annotation(self.\\n secondaryjoin, annotation))\\n return {x._deannotate() for x in s}\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n\\n def _annotate_parentmapper(self) ->None:\\n\\n def parentmappers_(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.mapper})\\n elif 'local' in element._annotations:\\n return element._annotate({'parentmapper': self.prop.parent})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, parentmappers_)\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n\\n def _annotate_selfref(self, fn: Callable[[ColumnElement[Any]], bool],\\n remote_side_given: bool) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the relationship is detected as self-referential.\\n\\n \\\"\\\"\\\"\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n equated = binary.left.compare(binary.right)\\n if isinstance(binary.left, expression.ColumnClause) and isinstance(\\n binary.right, expression.ColumnClause):\\n if fn(binary.left):\\n binary.left = binary.left._annotate({'remote': True})\\n if fn(binary.right) and not equated:\\n binary.right = binary.right._annotate({'remote': True})\\n elif not remote_side_given:\\n self._warn_non_column_elements()\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n\\n def _has_annotation(self, clause: ClauseElement, annotation: str) ->bool:\\n for col in visitors.iterate(clause, {}):\\n if annotation in col._annotations:\\n return True\\n else:\\n return False\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n\\n def _deannotate_pairs(self, collection: _ColumnPairIterable\\n ) ->_MutableColumnPairs:\\n \\\"\\\"\\\"provide deannotation for the various lists of\\n pairs, so that using them in hashes doesn't incur\\n high-overhead __eq__() comparisons against\\n original columns mapped.\\n\\n \\\"\\\"\\\"\\n return [(x._deannotate(), y._deannotate()) for x, y in collection]\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n\\n def _annotate_remote_distinct_selectables(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the parent/child tables are entirely\\n separate.\\n\\n \\\"\\\"\\\"\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if self.child_persist_selectable.c.contains_column(element) and (\\n not self.parent_local_selectable.c.contains_column(element) or\\n self.child_local_selectable.c.contains_column(element)):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, repl)\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def _has_remote_annotations(self) ->bool:\\n return self._has_annotation(self.primaryjoin, 'remote')\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n\\n def _warn_non_column_elements(self) ->None:\\n util.warn(\\n 'Non-simple column elements in primary join condition for property %s - consider using remote() annotations to mark the remote side.'\\n % self.prop)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n\\n def _annotate_from_fk_list(self) ->None:\\n\\n def check_fk(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in self.consider_as_foreign_keys:\\n return element._annotate({'foreign': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.primaryjoin,\\n {}, check_fk)\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.replacement_traverse(self.\\n secondaryjoin, {}, check_fk)\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n\\n def _tables_overlap(self) ->bool:\\n \\\"\\\"\\\"Return True if parent/child tables have some overlap.\\\"\\\"\\\"\\n return selectables_overlap(self.parent_persist_selectable, self.\\n child_persist_selectable)\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n\\n def __init__(self, parent_persist_selectable: FromClause,\\n child_persist_selectable: FromClause, parent_local_selectable:\\n FromClause, child_local_selectable: FromClause, *, primaryjoin:\\n Optional[ColumnElement[bool]]=None, secondary: Optional[FromClause]\\n =None, secondaryjoin: Optional[ColumnElement[bool]]=None,\\n parent_equivalents: Optional[_EquivalentColumnMap]=None,\\n child_equivalents: Optional[_EquivalentColumnMap]=None,\\n consider_as_foreign_keys: Any=None, local_remote_pairs: Optional[\\n _ColumnPairs]=None, remote_side: Any=None, self_referential: Any=\\n False, prop: RelationshipProperty[Any], support_sync: bool=True,\\n can_be_synced_fn: Callable[..., bool]=lambda *c: True):\\n self.parent_persist_selectable = parent_persist_selectable\\n self.parent_local_selectable = parent_local_selectable\\n self.child_persist_selectable = child_persist_selectable\\n self.child_local_selectable = child_local_selectable\\n self.parent_equivalents = parent_equivalents\\n self.child_equivalents = child_equivalents\\n self.primaryjoin_initial = primaryjoin\\n self.secondaryjoin = secondaryjoin\\n self.secondary = secondary\\n self.consider_as_foreign_keys = consider_as_foreign_keys\\n self._local_remote_pairs = local_remote_pairs\\n self._remote_side = remote_side\\n self.prop = prop\\n self.self_referential = self_referential\\n self.support_sync = support_sync\\n self.can_be_synced_fn = can_be_synced_fn\\n self._determine_joins()\\n assert self.primaryjoin is not None\\n self._sanitize_joins()\\n self._annotate_fks()\\n self._annotate_remote()\\n self._annotate_local()\\n self._annotate_parentmapper()\\n self._setup_pairs()\\n self._check_foreign_cols(self.primaryjoin, True)\\n if self.secondaryjoin is not None:\\n self._check_foreign_cols(self.secondaryjoin, False)\\n self._determine_direction()\\n self._check_remote_side()\\n self._log_joins()\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n\\n def _annotate_present_fks(self) ->None:\\n if self.secondary is not None:\\n secondarycols = util.column_set(self.secondary.c)\\n else:\\n secondarycols = set()\\n\\n def is_foreign(a: ColumnElement[Any], b: ColumnElement[Any]\\n ) ->Optional[ColumnElement[Any]]:\\n if isinstance(a, schema.Column) and isinstance(b, schema.Column):\\n if a.references(b):\\n return a\\n elif b.references(a):\\n return b\\n if secondarycols:\\n if a in secondarycols and b not in secondarycols:\\n return a\\n elif b in secondarycols and a not in secondarycols:\\n return b\\n return None\\n\\n def visit_binary(binary: BinaryExpression[Any]) ->None:\\n if not isinstance(binary.left, sql.ColumnElement\\n ) or not isinstance(binary.right, sql.ColumnElement):\\n return\\n if ('foreign' not in binary.left._annotations and 'foreign' not in\\n binary.right._annotations):\\n col = is_foreign(binary.left, binary.right)\\n if col is not None:\\n if col.compare(binary.left):\\n binary.left = binary.left._annotate({'foreign': True})\\n elif col.compare(binary.right):\\n binary.right = binary.right._annotate({'foreign': True}\\n )\\n self.primaryjoin = visitors.cloned_traverse(self.primaryjoin, {}, {\\n 'binary': visit_binary})\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = visitors.cloned_traverse(self.\\n secondaryjoin, {}, {'binary': visit_binary})\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n\\n @property\\n def primaryjoin_minus_local(self) ->ColumnElement[bool]:\\n return _deep_deannotate(self.primaryjoin, values=('local', 'remote'))\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n\\n def _determine_direction(self) ->None:\\n \\\"\\\"\\\"Determine if this relationship is one to many, many to one,\\n many to many.\\n\\n \\\"\\\"\\\"\\n if self.secondaryjoin is not None:\\n self.direction = MANYTOMANY\\n else:\\n parentcols = util.column_set(self.parent_persist_selectable.c)\\n targetcols = util.column_set(self.child_persist_selectable.c)\\n onetomany_fk = targetcols.intersection(self.foreign_key_columns)\\n manytoone_fk = parentcols.intersection(self.foreign_key_columns)\\n if onetomany_fk and manytoone_fk:\\n onetomany_local = self._gather_columns_with_annotation(self\\n .primaryjoin, 'remote', 'foreign')\\n manytoone_local = {c for c in self.\\n _gather_columns_with_annotation(self.primaryjoin,\\n 'foreign') if 'remote' not in c._annotations}\\n if onetomany_local and manytoone_local:\\n self_equated = self.remote_columns.intersection(self.\\n local_columns)\\n onetomany_local = onetomany_local.difference(self_equated)\\n manytoone_local = manytoone_local.difference(self_equated)\\n if onetomany_local and not manytoone_local:\\n self.direction = ONETOMANY\\n elif manytoone_local and not onetomany_local:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns within the join condition are present in both the parent and the child's mapped tables. Ensure that only those columns referring to a parent column are marked as foreign, either via the foreign() annotation or via the foreign_keys argument.\\\"\\n % self.prop)\\n elif onetomany_fk:\\n self.direction = ONETOMANY\\n elif manytoone_fk:\\n self.direction = MANYTOONE\\n else:\\n raise sa_exc.ArgumentError(\\n \\\"Can't determine relationship direction for relationship '%s' - foreign key columns are present in neither the parent nor the child's mapped tables\\\"\\n % self.prop)\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n\\n def _annotate_remote_from_args(self) ->None:\\n \\\"\\\"\\\"annotate 'remote' in primaryjoin, secondaryjoin\\n when the 'remote_side' or '_local_remote_pairs'\\n arguments are used.\\n\\n \\\"\\\"\\\"\\n if self._local_remote_pairs:\\n if self._remote_side:\\n raise sa_exc.ArgumentError(\\n 'remote_side argument is redundant against more detailed _local_remote_side argument.'\\n )\\n remote_side = [r for l, r in self._local_remote_pairs]\\n else:\\n remote_side = self._remote_side\\n if self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: col in remote_side, True)\\n else:\\n\\n def repl(element: _CE, **kw: Any) ->Optional[_CE]:\\n if element in set(remote_side):\\n return element._annotate({'remote': True})\\n return None\\n self.primaryjoin = visitors.replacement_traverse(self.\\n primaryjoin, {}, repl)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n\\n @util.memoized_property\\n def local_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('local')\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n\\n def _setup_pairs(self) ->None:\\n sync_pairs: _MutableColumnPairs = []\\n lrp: util.OrderedSet[Tuple[ColumnElement[Any], ColumnElement[Any]]\\n ] = util.OrderedSet([])\\n secondary_sync_pairs: _MutableColumnPairs = []\\n\\n def go(joincond: ColumnElement[bool], collection: _MutableColumnPairs\\n ) ->None:\\n\\n def visit_binary(binary: BinaryExpression[Any], left:\\n ColumnElement[Any], right: ColumnElement[Any]) ->None:\\n if ('remote' in right._annotations and 'remote' not in left\\n ._annotations and self.can_be_synced_fn(left)):\\n lrp.add((left, right))\\n elif 'remote' in left._annotations and 'remote' not in right._annotations and self.can_be_synced_fn(\\n right):\\n lrp.add((right, left))\\n if binary.operator is operators.eq and self.can_be_synced_fn(\\n left, right):\\n if 'foreign' in right._annotations:\\n collection.append((left, right))\\n elif 'foreign' in left._annotations:\\n collection.append((right, left))\\n visit_binary_product(visit_binary, joincond)\\n for joincond, collection in [(self.primaryjoin, sync_pairs), (self.\\n secondaryjoin, secondary_sync_pairs)]:\\n if joincond is None:\\n continue\\n go(joincond, collection)\\n self.local_remote_pairs = self._deannotate_pairs(lrp)\\n self.synchronize_pairs = self._deannotate_pairs(sync_pairs)\\n self.secondary_synchronize_pairs = self._deannotate_pairs(\\n secondary_sync_pairs)\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n\\n def _sanitize_joins(self) ->None:\\n \\\"\\\"\\\"remove the parententity annotation from our join conditions which\\n can leak in here based on some declarative patterns and maybe others.\\n\\n \\\"parentmapper\\\" is relied upon both by the ORM evaluator as well as\\n the use case in _join_fixture_inh_selfref_w_entity\\n that relies upon it being present, see :ticket:`3364`.\\n\\n \\\"\\\"\\\"\\n self.primaryjoin = _deep_deannotate(self.primaryjoin, values=(\\n 'parententity', 'proxy_key'))\\n if self.secondaryjoin is not None:\\n self.secondaryjoin = _deep_deannotate(self.secondaryjoin,\\n values=('parententity', 'proxy_key'))\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n\\n @util.memoized_property\\n def remote_columns(self) ->Set[ColumnElement[Any]]:\\n return self._gather_join_annotations('remote')\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_remote(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'remote' annotations marking columns\\n considered as part of the 'remote' side.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n return\\n if self.secondary is not None:\\n self._annotate_remote_secondary()\\n elif self._local_remote_pairs or self._remote_side:\\n self._annotate_remote_from_args()\\n elif self._refers_to_parent_table():\\n self._annotate_selfref(lambda col: 'foreign' in col.\\n _annotations, False)\\n elif self._tables_overlap():\\n self._annotate_remote_with_overlap()\\n else:\\n self._annotate_remote_distinct_selectables()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def join_targets(self, source_selectable: Optional[FromClause],\\n dest_selectable: FromClause, aliased: bool, single_crit: Optional[\\n ColumnElement[bool]]=None, extra_criteria: Tuple[ColumnElement[bool\\n ], ...]=()) ->Tuple[ColumnElement[bool], Optional[ColumnElement[\\n bool]], Optional[FromClause], Optional[ClauseAdapter], FromClause]:\\n \\\"\\\"\\\"Given a source and destination selectable, create a\\n join between them.\\n\\n This takes into account aliasing the join clause\\n to reference the appropriate corresponding columns\\n in the target objects, as well as the extra child\\n criterion, equivalent column sets, etc.\\n\\n \\\"\\\"\\\"\\n dest_selectable = _shallow_annotate(dest_selectable, {\\n 'no_replacement_traverse': True})\\n primaryjoin, secondaryjoin, secondary = (self.primaryjoin, self.\\n secondaryjoin, self.secondary)\\n if single_crit is not None:\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & single_crit\\n else:\\n primaryjoin = primaryjoin & single_crit\\n if extra_criteria:\\n\\n def mark_unrelated_columns_as_ok_to_adapt(elem:\\n SupportsAnnotations, annotations: _AnnotationDict\\n ) ->SupportsAnnotations:\\n \\\"\\\"\\\"note unrelated columns in the \\\"extra criteria\\\" as OK\\n to adapt, even though they are not part of our \\\"local\\\"\\n or \\\"remote\\\" side.\\n\\n see #9779 for this case\\n\\n \\\"\\\"\\\"\\n parentmapper_for_element = elem._annotations.get('parentmapper'\\n , None)\\n if (parentmapper_for_element is not self.prop.parent and \\n parentmapper_for_element is not self.prop.mapper):\\n return _safe_annotate(elem, annotations)\\n else:\\n return elem\\n extra_criteria = tuple(_deep_annotate(elem, {\\n 'ok_to_adapt_in_join_condition': True}, annotate_callable=\\n mark_unrelated_columns_as_ok_to_adapt) for elem in\\n extra_criteria)\\n if secondaryjoin is not None:\\n secondaryjoin = secondaryjoin & sql.and_(*extra_criteria)\\n else:\\n primaryjoin = primaryjoin & sql.and_(*extra_criteria)\\n if aliased:\\n if secondary is not None:\\n secondary = secondary._anonymous_fromclause(flat=True)\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn=\\n _ColInAnnotations('local'))\\n secondary_aliasizer = ClauseAdapter(dest_selectable,\\n equivalents=self.child_equivalents).chain(primary_aliasizer\\n )\\n if source_selectable is not None:\\n primary_aliasizer = ClauseAdapter(secondary, exclude_fn\\n =_ColInAnnotations('local')).chain(ClauseAdapter(\\n source_selectable, equivalents=self.parent_equivalents)\\n )\\n secondaryjoin = secondary_aliasizer.traverse(secondaryjoin)\\n else:\\n primary_aliasizer = ClauseAdapter(dest_selectable,\\n exclude_fn=_ColInAnnotations('local'), equivalents=self\\n .child_equivalents)\\n if source_selectable is not None:\\n primary_aliasizer.chain(ClauseAdapter(source_selectable,\\n exclude_fn=_ColInAnnotations('remote'), equivalents\\n =self.parent_equivalents))\\n secondary_aliasizer = None\\n primaryjoin = primary_aliasizer.traverse(primaryjoin)\\n target_adapter = secondary_aliasizer or primary_aliasizer\\n target_adapter.exclude_fn = None\\n else:\\n target_adapter = None\\n return (primaryjoin, secondaryjoin, secondary, target_adapter,\\n dest_selectable)\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def _check_foreign_cols(self, join_condition: ColumnElement[bool],\\n primary: bool) ->None:\\n \\\"\\\"\\\"Check the foreign key columns collected and emit error\\n messages.\\\"\\\"\\\"\\n can_sync = False\\n foreign_cols = self._gather_columns_with_annotation(join_condition,\\n 'foreign')\\n has_foreign = bool(foreign_cols)\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n if (self.support_sync and can_sync or not self.support_sync and\\n has_foreign):\\n return\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions involving locally mapped foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n \\\" Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation. To allow comparison operators other than '==', the relationship can be marked as viewonly=True.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns for %s join condition '%s' on relationship %s.\\\"\\n % (primary and 'primary' or 'secondary', join_condition,\\n self.prop))\\n err += (\\n ' Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or are annotated in the join condition with the foreign() annotation.'\\n )\\n raise sa_exc.ArgumentError(err)\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n\\n def _annotate_fks(self) ->None:\\n \\\"\\\"\\\"Annotate the primaryjoin and secondaryjoin\\n structures with 'foreign' annotations marking columns\\n considered as foreign.\\n\\n \\\"\\\"\\\"\\n if self._has_foreign_annotations:\\n return\\n if self.consider_as_foreign_keys:\\n self._annotate_from_fk_list()\\n else:\\n self._annotate_present_fks()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @util.memoized_property\\n def primaryjoin_reverse_remote(self) ->ColumnElement[bool]:\\n \\\"\\\"\\\"Return the primaryjoin condition suitable for the\\n \\\"reverse\\\" direction.\\n\\n If the primaryjoin was delivered here with pre-existing\\n \\\"remote\\\" annotations, the local/remote annotations\\n are reversed. Otherwise, the local/remote annotations\\n are removed.\\n\\n \\\"\\\"\\\"\\n if self._has_remote_annotations:\\n\\n def replace(element: _CE, **kw: Any) ->Optional[_CE]:\\n if 'remote' in element._annotations:\\n v = dict(element._annotations)\\n del v['remote']\\n v['local'] = True\\n return element._with_annotations(v)\\n elif 'local' in element._annotations:\\n v = dict(element._annotations)\\n del v['local']\\n v['remote'] = True\\n return element._with_annotations(v)\\n return None\\n return visitors.replacement_traverse(self.primaryjoin, {}, replace)\\n elif self._has_foreign_annotations:\\n return _deep_deannotate(self.primaryjoin, values=('local',\\n 'remote'))\\n else:\\n return _deep_deannotate(self.primaryjoin)\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def create_lazy_clause(self, reverse_direction: bool=False) ->Tuple[\\n ColumnElement[bool], Dict[str, ColumnElement[Any]], Dict[\\n ColumnElement[Any], ColumnElement[Any]]]:\\n binds: Dict[ColumnElement[Any], BindParameter[Any]] = {}\\n equated_columns: Dict[ColumnElement[Any], ColumnElement[Any]] = {}\\n has_secondary = self.secondaryjoin is not None\\n if has_secondary:\\n lookup = collections.defaultdict(list)\\n for l, r in self.local_remote_pairs:\\n lookup[l].append((l, r))\\n equated_columns[r] = l\\n elif not reverse_direction:\\n for l, r in self.local_remote_pairs:\\n equated_columns[r] = l\\n else:\\n for l, r in self.local_remote_pairs:\\n equated_columns[l] = r\\n\\n def col_to_bind(element: ColumnElement[Any], **kw: Any) ->Optional[\\n BindParameter[Any]]:\\n if (not reverse_direction and 'local' in element._annotations or\\n reverse_direction and (has_secondary and element in lookup or\\n not has_secondary and 'remote' in element._annotations)):\\n if element not in binds:\\n binds[element] = sql.bindparam(None, None, type_=\\n element.type, unique=True)\\n return binds[element]\\n return None\\n lazywhere = self.primaryjoin\\n if self.secondaryjoin is None or not reverse_direction:\\n lazywhere = visitors.replacement_traverse(lazywhere, {},\\n col_to_bind)\\n if self.secondaryjoin is not None:\\n secondaryjoin = self.secondaryjoin\\n if reverse_direction:\\n secondaryjoin = visitors.replacement_traverse(secondaryjoin,\\n {}, col_to_bind)\\n lazywhere = sql.and_(lazywhere, secondaryjoin)\\n bind_to_col = {binds[col].key: col for col in binds}\\n return lazywhere, bind_to_col, equated_columns\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n\\n\\nclass JoinCondition:\\n primaryjoin_initial: Optional[ColumnElement[bool]]\\n primaryjoin: ColumnElement[bool]\\n secondaryjoin: Optional[ColumnElement[bool]]\\n secondary: Optional[FromClause]\\n prop: RelationshipProperty[Any]\\n synchronize_pairs: _ColumnPairs\\n secondary_synchronize_pairs: _ColumnPairs\\n direction: RelationshipDirection\\n parent_persist_selectable: FromClause\\n child_persist_selectable: FromClause\\n parent_local_selectable: FromClause\\n child_local_selectable: FromClause\\n _local_remote_pairs: Optional[_ColumnPairs]\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n _track_overlapping_sync_targets: weakref.WeakKeyDictionary[\\n ColumnElement[Any], weakref.WeakKeyDictionary[RelationshipProperty[\\n Any], ColumnElement[Any]]] = weakref.WeakKeyDictionary()\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n\\n\\nclass _ColInAnnotations:\\n \\\"\\\"\\\"Serializable object that tests for a name in c._annotations.\\\"\\\"\\\"\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n\\n\\nclass _ColInAnnotations:\\n <docstring token>\\n __slots__ = 'name',\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n\\n\\nclass _ColInAnnotations:\\n <docstring token>\\n <assignment token>\\n\\n def __init__(self, name: str):\\n self.name = name\\n\\n def __call__(self, c: ClauseElement) ->bool:\\n return (self.name in c._annotations or \\n 'ok_to_adapt_in_join_condition' in c._annotations)\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n\\n\\nclass _ColInAnnotations:\\n <docstring token>\\n <assignment token>\\n\\n def __init__(self, name: str):\\n self.name = name\\n <function token>\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n\\n\\nclass _ColInAnnotations:\\n <docstring token>\\n <assignment token>\\n <function token>\\n <function token>\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n \\\"\\\"\\\"Describes an object property that holds a single item or list\\n of items that correspond to a related database table.\\n\\n Public constructor is the :func:`_orm.relationship` function.\\n\\n .. seealso::\\n\\n :ref:`relationship_config_toplevel`\\n\\n .. versionchanged:: 2.0 Added :class:`_orm.Relationship` as a Declarative\\n compatible subclass for :class:`_orm.RelationshipProperty`.\\n\\n \\\"\\\"\\\"\\n inherit_cache = True\\n \\\"\\\"\\\":meta private:\\\"\\\"\\\"\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n <docstring token>\\n inherit_cache = True\\n <docstring token>\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n<class token>\\n\\n\\nclass Relationship(RelationshipProperty[_T], _DeclarativeMapped[_T],\\n WriteOnlyMapped[_T], DynamicMapped[_T]):\\n <docstring token>\\n <assignment token>\\n <docstring token>\\n\",\n \"<docstring token>\\n<import token>\\n<code token>\\n<assignment token>\\n<function token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n<function token>\\n<class token>\\n<class token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8670,"cells":{"index":{"kind":"number","value":8670,"string":"8,670"},"blob_id":{"kind":"string","value":"e486e0ab91a8f5671435f5bbcf5340a62a970d3a"},"code":{"kind":"string","value":"class SmartChineseAnalyzer:\n def __init__(self):\n pass\n\n def create_components(self, filename):\n #tokenizer = SentenceTokenize(filename)\n #result = WordTokenFilter(tokenizer)\n #result = PorterStemFilter(result)\n \n if self.stopwords:\n result = StopFilter(result, self.stopwords)\n return TokenStreamComponents(tokenizer, result)\n\n\n \n"},"steps":{"kind":"list like","value":["class SmartChineseAnalyzer:\n def __init__(self):\n pass\n\n def create_components(self, filename):\n #tokenizer = SentenceTokenize(filename)\n #result = WordTokenFilter(tokenizer)\n #result = PorterStemFilter(result)\n \n if self.stopwords:\n result = StopFilter(result, self.stopwords)\n return TokenStreamComponents(tokenizer, result)\n\n\n \n","class SmartChineseAnalyzer:\n\n def __init__(self):\n pass\n\n def create_components(self, filename):\n if self.stopwords:\n result = StopFilter(result, self.stopwords)\n return TokenStreamComponents(tokenizer, result)\n","class SmartChineseAnalyzer:\n\n def __init__(self):\n pass\n <function token>\n","class SmartChineseAnalyzer:\n <function token>\n <function token>\n","<class token>\n"],"string":"[\n \"class SmartChineseAnalyzer:\\n def __init__(self):\\n pass\\n\\n def create_components(self, filename):\\n #tokenizer = SentenceTokenize(filename)\\n #result = WordTokenFilter(tokenizer)\\n #result = PorterStemFilter(result)\\n \\n if self.stopwords:\\n result = StopFilter(result, self.stopwords)\\n return TokenStreamComponents(tokenizer, result)\\n\\n\\n \\n\",\n \"class SmartChineseAnalyzer:\\n\\n def __init__(self):\\n pass\\n\\n def create_components(self, filename):\\n if self.stopwords:\\n result = StopFilter(result, self.stopwords)\\n return TokenStreamComponents(tokenizer, result)\\n\",\n \"class SmartChineseAnalyzer:\\n\\n def __init__(self):\\n pass\\n <function token>\\n\",\n \"class SmartChineseAnalyzer:\\n <function token>\\n <function token>\\n\",\n \"<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8671,"cells":{"index":{"kind":"number","value":8671,"string":"8,671"},"blob_id":{"kind":"string","value":"ef5c51a5c706387b62ef3f40c7cadf7dbef6d082"},"code":{"kind":"string","value":"from flask_minify.utils import get_optimized_hashing\n\n\nclass MemoryCache:\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n\n return self._cache\n\n @property\n def limit_exceeded(self):\n return len(self.store) >= self.limit\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n\n hashed_key = self.hashing(key.encode(\"utf-8\")).hexdigest()\n\n if not self[hashed_key]:\n self[hashed_key] = getter()\n\n return self[hashed_key]\n\n def clear(self):\n del self._cache\n self._cache = {}\n"},"steps":{"kind":"list like","value":["from flask_minify.utils import get_optimized_hashing\n\n\nclass MemoryCache:\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n\n return self._cache\n\n @property\n def limit_exceeded(self):\n return len(self.store) >= self.limit\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n\n hashed_key = self.hashing(key.encode(\"utf-8\")).hexdigest()\n\n if not self[hashed_key]:\n self[hashed_key] = getter()\n\n return self[hashed_key]\n\n def clear(self):\n del self._cache\n self._cache = {}\n","from flask_minify.utils import get_optimized_hashing\n\n\nclass MemoryCache:\n\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n return self._cache\n\n @property\n def limit_exceeded(self):\n return len(self.store) >= self.limit\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n\n def clear(self):\n del self._cache\n self._cache = {}\n","<import token>\n\n\nclass MemoryCache:\n\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n return self._cache\n\n @property\n def limit_exceeded(self):\n return len(self.store) >= self.limit\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n\n def clear(self):\n del self._cache\n self._cache = {}\n","<import token>\n\n\nclass MemoryCache:\n\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n return self._cache\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n\n def clear(self):\n del self._cache\n self._cache = {}\n","<import token>\n\n\nclass MemoryCache:\n\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n return self._cache\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n <function token>\n","<import token>\n\n\nclass MemoryCache:\n <function token>\n\n @property\n def store(self):\n if self.store_key_getter:\n return self._cache.setdefault(self.store_key_getter(), {})\n return self._cache\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n <function token>\n","<import token>\n\n\nclass MemoryCache:\n <function token>\n <function token>\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n\n def get_or_set(self, key, getter):\n if self.limit == 0:\n return getter()\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\n if not self[hashed_key]:\n self[hashed_key] = getter()\n return self[hashed_key]\n <function token>\n","<import token>\n\n\nclass MemoryCache:\n <function token>\n <function token>\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n\n def __setitem__(self, key, value):\n if self.limit_exceeded:\n self.store.popitem()\n self.store.update({key: value})\n <function token>\n <function token>\n","<import token>\n\n\nclass MemoryCache:\n <function token>\n <function token>\n <function token>\n\n def __getitem__(self, key):\n return self.store.get(key)\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass MemoryCache:\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n","<import token>\n<class token>\n"],"string":"[\n \"from flask_minify.utils import get_optimized_hashing\\n\\n\\nclass MemoryCache:\\n def __init__(self, store_key_getter=None, limit=0):\\n self.store_key_getter = store_key_getter\\n self.limit = limit\\n self._cache = {}\\n self.hashing = get_optimized_hashing()\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n\\n return self._cache\\n\\n @property\\n def limit_exceeded(self):\\n return len(self.store) >= self.limit\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n\\n hashed_key = self.hashing(key.encode(\\\"utf-8\\\")).hexdigest()\\n\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n\\n return self[hashed_key]\\n\\n def clear(self):\\n del self._cache\\n self._cache = {}\\n\",\n \"from flask_minify.utils import get_optimized_hashing\\n\\n\\nclass MemoryCache:\\n\\n def __init__(self, store_key_getter=None, limit=0):\\n self.store_key_getter = store_key_getter\\n self.limit = limit\\n self._cache = {}\\n self.hashing = get_optimized_hashing()\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n return self._cache\\n\\n @property\\n def limit_exceeded(self):\\n return len(self.store) >= self.limit\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n\\n def clear(self):\\n del self._cache\\n self._cache = {}\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n\\n def __init__(self, store_key_getter=None, limit=0):\\n self.store_key_getter = store_key_getter\\n self.limit = limit\\n self._cache = {}\\n self.hashing = get_optimized_hashing()\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n return self._cache\\n\\n @property\\n def limit_exceeded(self):\\n return len(self.store) >= self.limit\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n\\n def clear(self):\\n del self._cache\\n self._cache = {}\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n\\n def __init__(self, store_key_getter=None, limit=0):\\n self.store_key_getter = store_key_getter\\n self.limit = limit\\n self._cache = {}\\n self.hashing = get_optimized_hashing()\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n return self._cache\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n\\n def clear(self):\\n del self._cache\\n self._cache = {}\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n\\n def __init__(self, store_key_getter=None, limit=0):\\n self.store_key_getter = store_key_getter\\n self.limit = limit\\n self._cache = {}\\n self.hashing = get_optimized_hashing()\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n return self._cache\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n <function token>\\n\\n @property\\n def store(self):\\n if self.store_key_getter:\\n return self._cache.setdefault(self.store_key_getter(), {})\\n return self._cache\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n <function token>\\n <function token>\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n\\n def get_or_set(self, key, getter):\\n if self.limit == 0:\\n return getter()\\n hashed_key = self.hashing(key.encode('utf-8')).hexdigest()\\n if not self[hashed_key]:\\n self[hashed_key] = getter()\\n return self[hashed_key]\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n <function token>\\n <function token>\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n\\n def __setitem__(self, key, value):\\n if self.limit_exceeded:\\n self.store.popitem()\\n self.store.update({key: value})\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n <function token>\\n <function token>\\n <function token>\\n\\n def __getitem__(self, key):\\n return self.store.get(key)\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass MemoryCache:\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8672,"cells":{"index":{"kind":"number","value":8672,"string":"8,672"},"blob_id":{"kind":"string","value":"42187f460a64572d2581ed5baec41eaff47466f8"},"code":{"kind":"string","value":"version https://git-lfs.github.com/spec/v1\noid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49\nsize 964\n"},"steps":{"kind":"list like","value":["version https://git-lfs.github.com/spec/v1\noid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49\nsize 964\n"],"string":"[\n \"version https://git-lfs.github.com/spec/v1\\noid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49\\nsize 964\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":true,"string":"true"}}},{"rowIdx":8673,"cells":{"index":{"kind":"number","value":8673,"string":"8,673"},"blob_id":{"kind":"string","value":"83be35b79dcaa34f9273281976ebb71e81c58cdd"},"code":{"kind":"string","value":"import logging\nimport os\nimport time\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom configargparse import ArgumentParser\nfrom cryptography import x509\nfrom cryptography.hazmat.backends import default_backend\nfrom cryptography.x509.oid import ExtensionOID\nfrom cryptography.x509.extensions import ExtensionNotFound\nfrom prettylog import basic_config\nfrom prometheus_client import start_http_server\nfrom prometheus_client.core import GaugeMetricFamily, REGISTRY\n\nparser = ArgumentParser(\n default_config_files=[os.path.join(\"/etc/ssl-exporter.conf\")],\n auto_env_var_prefix=\"APP_\",\n)\n\nparser.add_argument(\"--host-address\", type=str, default=\"0.0.0.0\")\nparser.add_argument(\"--port\", type=int, default=\"9001\")\nparser.add_argument(\"--cert-paths\", nargs=\"+\", type=Path)\nparser.add_argument(\"--log-level\", type=str, default=\"INFO\")\nparser.add_argument(\"--log-format\", type=str, default=\"color\")\n\narguments = parser.parse_args()\n\nlog = logging.getLogger()\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n\n self.gauges[\"ssl_valid_days\"] = GaugeMetricFamily(\n \"ssl_valid_days\",\n \"Ssl cert valid days\",\n value=None,\n labels=[\"domain\", \"file_name\", \"serial_number\"],\n )\n\n for path in self.cert_paths:\n if not path.exists():\n log.error(\"File %r does not exists\", path)\n exit(1)\n self.get_metrics(path)\n\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open(\"rb\") as f:\n try:\n cert = x509.load_pem_x509_certificate(\n f.read(), default_backend()\n )\n except ValueError:\n log.exception(\"Cannot read certificate - %r\", path)\n return []\n file_name = path.name\n log.debug(\"File name of cert - %r\", file_name)\n\n not_valid_after = cert.not_valid_after\n log.debug(\"Ssl not valid after date - %r\", str(not_valid_after))\n\n left = not_valid_after - datetime.utcnow()\n log.debug(\"Ssl cert valid days - %r\", left.days)\n\n log.debug(\"Ssl cert serial number - %r\", cert.serial_number)\n\n try:\n ext = cert.extensions.get_extension_for_oid(\n ExtensionOID.SUBJECT_ALTERNATIVE_NAME\n )\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = [\"noname\"]\n\n log.debug(\"DNS names of cert - %r\", dns_names_list)\n\n for domain in dns_names_list:\n self.gauges[\"ssl_valid_days\"].add_metric(\n [domain, file_name, str(cert.serial_number)], int(left.days)\n )\n\n\ndef main():\n basic_config(\n level=arguments.log_level.upper(),\n buffered=False,\n log_format=arguments.log_format,\n )\n\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\nif __name__ == \"__main__\":\n main()\n"},"steps":{"kind":"list like","value":["import logging\nimport os\nimport time\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom configargparse import ArgumentParser\nfrom cryptography import x509\nfrom cryptography.hazmat.backends import default_backend\nfrom cryptography.x509.oid import ExtensionOID\nfrom cryptography.x509.extensions import ExtensionNotFound\nfrom prettylog import basic_config\nfrom prometheus_client import start_http_server\nfrom prometheus_client.core import GaugeMetricFamily, REGISTRY\n\nparser = ArgumentParser(\n default_config_files=[os.path.join(\"/etc/ssl-exporter.conf\")],\n auto_env_var_prefix=\"APP_\",\n)\n\nparser.add_argument(\"--host-address\", type=str, default=\"0.0.0.0\")\nparser.add_argument(\"--port\", type=int, default=\"9001\")\nparser.add_argument(\"--cert-paths\", nargs=\"+\", type=Path)\nparser.add_argument(\"--log-level\", type=str, default=\"INFO\")\nparser.add_argument(\"--log-format\", type=str, default=\"color\")\n\narguments = parser.parse_args()\n\nlog = logging.getLogger()\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n\n self.gauges[\"ssl_valid_days\"] = GaugeMetricFamily(\n \"ssl_valid_days\",\n \"Ssl cert valid days\",\n value=None,\n labels=[\"domain\", \"file_name\", \"serial_number\"],\n )\n\n for path in self.cert_paths:\n if not path.exists():\n log.error(\"File %r does not exists\", path)\n exit(1)\n self.get_metrics(path)\n\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open(\"rb\") as f:\n try:\n cert = x509.load_pem_x509_certificate(\n f.read(), default_backend()\n )\n except ValueError:\n log.exception(\"Cannot read certificate - %r\", path)\n return []\n file_name = path.name\n log.debug(\"File name of cert - %r\", file_name)\n\n not_valid_after = cert.not_valid_after\n log.debug(\"Ssl not valid after date - %r\", str(not_valid_after))\n\n left = not_valid_after - datetime.utcnow()\n log.debug(\"Ssl cert valid days - %r\", left.days)\n\n log.debug(\"Ssl cert serial number - %r\", cert.serial_number)\n\n try:\n ext = cert.extensions.get_extension_for_oid(\n ExtensionOID.SUBJECT_ALTERNATIVE_NAME\n )\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = [\"noname\"]\n\n log.debug(\"DNS names of cert - %r\", dns_names_list)\n\n for domain in dns_names_list:\n self.gauges[\"ssl_valid_days\"].add_metric(\n [domain, file_name, str(cert.serial_number)], int(left.days)\n )\n\n\ndef main():\n basic_config(\n level=arguments.log_level.upper(),\n buffered=False,\n log_format=arguments.log_format,\n )\n\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\nif __name__ == \"__main__\":\n main()\n","import logging\nimport os\nimport time\nfrom datetime import datetime\nfrom pathlib import Path\nfrom configargparse import ArgumentParser\nfrom cryptography import x509\nfrom cryptography.hazmat.backends import default_backend\nfrom cryptography.x509.oid import ExtensionOID\nfrom cryptography.x509.extensions import ExtensionNotFound\nfrom prettylog import basic_config\nfrom prometheus_client import start_http_server\nfrom prometheus_client.core import GaugeMetricFamily, REGISTRY\nparser = ArgumentParser(default_config_files=[os.path.join(\n '/etc/ssl-exporter.conf')], auto_env_var_prefix='APP_')\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\nparser.add_argument('--port', type=int, default='9001')\nparser.add_argument('--cert-paths', nargs='+', type=Path)\nparser.add_argument('--log-level', type=str, default='INFO')\nparser.add_argument('--log-format', type=str, default='color')\narguments = parser.parse_args()\nlog = logging.getLogger()\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\ndef main():\n basic_config(level=arguments.log_level.upper(), buffered=False,\n log_format=arguments.log_format)\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\nif __name__ == '__main__':\n main()\n","<import token>\nparser = ArgumentParser(default_config_files=[os.path.join(\n '/etc/ssl-exporter.conf')], auto_env_var_prefix='APP_')\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\nparser.add_argument('--port', type=int, default='9001')\nparser.add_argument('--cert-paths', nargs='+', type=Path)\nparser.add_argument('--log-level', type=str, default='INFO')\nparser.add_argument('--log-format', type=str, default='color')\narguments = parser.parse_args()\nlog = logging.getLogger()\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\ndef main():\n basic_config(level=arguments.log_level.upper(), buffered=False,\n log_format=arguments.log_format)\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\nif __name__ == '__main__':\n main()\n","<import token>\n<assignment token>\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\nparser.add_argument('--port', type=int, default='9001')\nparser.add_argument('--cert-paths', nargs='+', type=Path)\nparser.add_argument('--log-level', type=str, default='INFO')\nparser.add_argument('--log-format', type=str, default='color')\n<assignment token>\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\ndef main():\n basic_config(level=arguments.log_level.upper(), buffered=False,\n log_format=arguments.log_format)\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\nif __name__ == '__main__':\n main()\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\ndef main():\n basic_config(level=arguments.log_level.upper(), buffered=False,\n log_format=arguments.log_format)\n start_http_server(addr=arguments.host_address, port=arguments.port)\n collector = SslExporter(arguments.cert_paths)\n REGISTRY.register(collector)\n while True:\n time.sleep(1)\n\n\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\n<function token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n <assignment token>\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n\n def get_metrics(self, path: Path):\n with path.open('rb') as f:\n try:\n cert = x509.load_pem_x509_certificate(f.read(),\n default_backend())\n except ValueError:\n log.exception('Cannot read certificate - %r', path)\n return []\n file_name = path.name\n log.debug('File name of cert - %r', file_name)\n not_valid_after = cert.not_valid_after\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\n left = not_valid_after - datetime.utcnow()\n log.debug('Ssl cert valid days - %r', left.days)\n log.debug('Ssl cert serial number - %r', cert.serial_number)\n try:\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\n SUBJECT_ALTERNATIVE_NAME)\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\n except ExtensionNotFound:\n dns_names_list = ['noname']\n log.debug('DNS names of cert - %r', dns_names_list)\n for domain in dns_names_list:\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\n str(cert.serial_number)], int(left.days))\n\n\n<function token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n <assignment token>\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\n 'Ssl cert valid days', value=None, labels=['domain',\n 'file_name', 'serial_number'])\n for path in self.cert_paths:\n if not path.exists():\n log.error('File %r does not exists', path)\n exit(1)\n self.get_metrics(path)\n for name, data in self.gauges.items():\n yield data\n <function token>\n\n\n<function token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n <assignment token>\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n <function token>\n <function token>\n\n\n<function token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n\n\nclass SslExporter(object):\n <assignment token>\n <function token>\n <function token>\n <function token>\n\n\n<function token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n<class token>\n<function token>\n<code token>\n"],"string":"[\n \"import logging\\nimport os\\nimport time\\nfrom datetime import datetime\\nfrom pathlib import Path\\n\\nfrom configargparse import ArgumentParser\\nfrom cryptography import x509\\nfrom cryptography.hazmat.backends import default_backend\\nfrom cryptography.x509.oid import ExtensionOID\\nfrom cryptography.x509.extensions import ExtensionNotFound\\nfrom prettylog import basic_config\\nfrom prometheus_client import start_http_server\\nfrom prometheus_client.core import GaugeMetricFamily, REGISTRY\\n\\nparser = ArgumentParser(\\n default_config_files=[os.path.join(\\\"/etc/ssl-exporter.conf\\\")],\\n auto_env_var_prefix=\\\"APP_\\\",\\n)\\n\\nparser.add_argument(\\\"--host-address\\\", type=str, default=\\\"0.0.0.0\\\")\\nparser.add_argument(\\\"--port\\\", type=int, default=\\\"9001\\\")\\nparser.add_argument(\\\"--cert-paths\\\", nargs=\\\"+\\\", type=Path)\\nparser.add_argument(\\\"--log-level\\\", type=str, default=\\\"INFO\\\")\\nparser.add_argument(\\\"--log-format\\\", type=str, default=\\\"color\\\")\\n\\narguments = parser.parse_args()\\n\\nlog = logging.getLogger()\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n\\n self.gauges[\\\"ssl_valid_days\\\"] = GaugeMetricFamily(\\n \\\"ssl_valid_days\\\",\\n \\\"Ssl cert valid days\\\",\\n value=None,\\n labels=[\\\"domain\\\", \\\"file_name\\\", \\\"serial_number\\\"],\\n )\\n\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error(\\\"File %r does not exists\\\", path)\\n exit(1)\\n self.get_metrics(path)\\n\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open(\\\"rb\\\") as f:\\n try:\\n cert = x509.load_pem_x509_certificate(\\n f.read(), default_backend()\\n )\\n except ValueError:\\n log.exception(\\\"Cannot read certificate - %r\\\", path)\\n return []\\n file_name = path.name\\n log.debug(\\\"File name of cert - %r\\\", file_name)\\n\\n not_valid_after = cert.not_valid_after\\n log.debug(\\\"Ssl not valid after date - %r\\\", str(not_valid_after))\\n\\n left = not_valid_after - datetime.utcnow()\\n log.debug(\\\"Ssl cert valid days - %r\\\", left.days)\\n\\n log.debug(\\\"Ssl cert serial number - %r\\\", cert.serial_number)\\n\\n try:\\n ext = cert.extensions.get_extension_for_oid(\\n ExtensionOID.SUBJECT_ALTERNATIVE_NAME\\n )\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = [\\\"noname\\\"]\\n\\n log.debug(\\\"DNS names of cert - %r\\\", dns_names_list)\\n\\n for domain in dns_names_list:\\n self.gauges[\\\"ssl_valid_days\\\"].add_metric(\\n [domain, file_name, str(cert.serial_number)], int(left.days)\\n )\\n\\n\\ndef main():\\n basic_config(\\n level=arguments.log_level.upper(),\\n buffered=False,\\n log_format=arguments.log_format,\\n )\\n\\n start_http_server(addr=arguments.host_address, port=arguments.port)\\n collector = SslExporter(arguments.cert_paths)\\n REGISTRY.register(collector)\\n while True:\\n time.sleep(1)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\",\n \"import logging\\nimport os\\nimport time\\nfrom datetime import datetime\\nfrom pathlib import Path\\nfrom configargparse import ArgumentParser\\nfrom cryptography import x509\\nfrom cryptography.hazmat.backends import default_backend\\nfrom cryptography.x509.oid import ExtensionOID\\nfrom cryptography.x509.extensions import ExtensionNotFound\\nfrom prettylog import basic_config\\nfrom prometheus_client import start_http_server\\nfrom prometheus_client.core import GaugeMetricFamily, REGISTRY\\nparser = ArgumentParser(default_config_files=[os.path.join(\\n '/etc/ssl-exporter.conf')], auto_env_var_prefix='APP_')\\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\\nparser.add_argument('--port', type=int, default='9001')\\nparser.add_argument('--cert-paths', nargs='+', type=Path)\\nparser.add_argument('--log-level', type=str, default='INFO')\\nparser.add_argument('--log-format', type=str, default='color')\\narguments = parser.parse_args()\\nlog = logging.getLogger()\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\ndef main():\\n basic_config(level=arguments.log_level.upper(), buffered=False,\\n log_format=arguments.log_format)\\n start_http_server(addr=arguments.host_address, port=arguments.port)\\n collector = SslExporter(arguments.cert_paths)\\n REGISTRY.register(collector)\\n while True:\\n time.sleep(1)\\n\\n\\nif __name__ == '__main__':\\n main()\\n\",\n \"<import token>\\nparser = ArgumentParser(default_config_files=[os.path.join(\\n '/etc/ssl-exporter.conf')], auto_env_var_prefix='APP_')\\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\\nparser.add_argument('--port', type=int, default='9001')\\nparser.add_argument('--cert-paths', nargs='+', type=Path)\\nparser.add_argument('--log-level', type=str, default='INFO')\\nparser.add_argument('--log-format', type=str, default='color')\\narguments = parser.parse_args()\\nlog = logging.getLogger()\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\ndef main():\\n basic_config(level=arguments.log_level.upper(), buffered=False,\\n log_format=arguments.log_format)\\n start_http_server(addr=arguments.host_address, port=arguments.port)\\n collector = SslExporter(arguments.cert_paths)\\n REGISTRY.register(collector)\\n while True:\\n time.sleep(1)\\n\\n\\nif __name__ == '__main__':\\n main()\\n\",\n \"<import token>\\n<assignment token>\\nparser.add_argument('--host-address', type=str, default='0.0.0.0')\\nparser.add_argument('--port', type=int, default='9001')\\nparser.add_argument('--cert-paths', nargs='+', type=Path)\\nparser.add_argument('--log-level', type=str, default='INFO')\\nparser.add_argument('--log-format', type=str, default='color')\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\ndef main():\\n basic_config(level=arguments.log_level.upper(), buffered=False,\\n log_format=arguments.log_format)\\n start_http_server(addr=arguments.host_address, port=arguments.port)\\n collector = SslExporter(arguments.cert_paths)\\n REGISTRY.register(collector)\\n while True:\\n time.sleep(1)\\n\\n\\nif __name__ == '__main__':\\n main()\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\ndef main():\\n basic_config(level=arguments.log_level.upper(), buffered=False,\\n log_format=arguments.log_format)\\n start_http_server(addr=arguments.host_address, port=arguments.port)\\n collector = SslExporter(arguments.cert_paths)\\n REGISTRY.register(collector)\\n while True:\\n time.sleep(1)\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n gauges = {}\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\n<function token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n <assignment token>\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n\\n def get_metrics(self, path: Path):\\n with path.open('rb') as f:\\n try:\\n cert = x509.load_pem_x509_certificate(f.read(),\\n default_backend())\\n except ValueError:\\n log.exception('Cannot read certificate - %r', path)\\n return []\\n file_name = path.name\\n log.debug('File name of cert - %r', file_name)\\n not_valid_after = cert.not_valid_after\\n log.debug('Ssl not valid after date - %r', str(not_valid_after))\\n left = not_valid_after - datetime.utcnow()\\n log.debug('Ssl cert valid days - %r', left.days)\\n log.debug('Ssl cert serial number - %r', cert.serial_number)\\n try:\\n ext = cert.extensions.get_extension_for_oid(ExtensionOID.\\n SUBJECT_ALTERNATIVE_NAME)\\n dns_names_list = ext.value.get_values_for_type(x509.DNSName)\\n except ExtensionNotFound:\\n dns_names_list = ['noname']\\n log.debug('DNS names of cert - %r', dns_names_list)\\n for domain in dns_names_list:\\n self.gauges['ssl_valid_days'].add_metric([domain, file_name,\\n str(cert.serial_number)], int(left.days))\\n\\n\\n<function token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n <assignment token>\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n\\n def collect(self):\\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_valid_days',\\n 'Ssl cert valid days', value=None, labels=['domain',\\n 'file_name', 'serial_number'])\\n for path in self.cert_paths:\\n if not path.exists():\\n log.error('File %r does not exists', path)\\n exit(1)\\n self.get_metrics(path)\\n for name, data in self.gauges.items():\\n yield data\\n <function token>\\n\\n\\n<function token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n <assignment token>\\n\\n def __init__(self, cert_paths):\\n self.cert_paths = cert_paths\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\nclass SslExporter(object):\\n <assignment token>\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<class token>\\n<function token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8674,"cells":{"index":{"kind":"number","value":8674,"string":"8,674"},"blob_id":{"kind":"string","value":"dac8dbb0eba78d4f8dfbe3284325735324a87dc2"},"code":{"kind":"string","value":"\"\"\"\r\n时间最优\r\n\r\n思路：\r\n将和为目标值的那 两个 整数定义为 num1 和 num2\r\n创建一个新字典，内容存在数组中的数字及索引\r\n将数组nums转换为字典，\r\n遍历字典， num1为字典中的元素（其实与数组总的元素一样），\r\nnum2 为 target减去num1， 判定num2是否在字典中，如果存在，返回字典中num2的值（也就是在数组nums中的下标）和 i（也就是num1在数组中的下标）\r\n如果不存在，设置字典num1的值为i\r\n\"\"\"\r\n\r\ndef two_sum(nums, target):\r\n dct = {}\r\n for i, num1 in enumerate(nums):\r\n num2 = target - num1\r\n if num2 in dct:\r\n return [dct[num2], i]\r\n dct[num1] = i\r\n\r\n\r\nprint(two_sum([14, 2, 31, 4], 6))\r\n"},"steps":{"kind":"list like","value":["\"\"\"\r\n时间最优\r\n\r\n思路：\r\n将和为目标值的那 两个 整数定义为 num1 和 num2\r\n创建一个新字典，内容存在数组中的数字及索引\r\n将数组nums转换为字典，\r\n遍历字典， num1为字典中的元素（其实与数组总的元素一样），\r\nnum2 为 target减去num1， 判定num2是否在字典中，如果存在，返回字典中num2的值（也就是在数组nums中的下标）和 i（也就是num1在数组中的下标）\r\n如果不存在，设置字典num1的值为i\r\n\"\"\"\r\n\r\ndef two_sum(nums, target):\r\n dct = {}\r\n for i, num1 in enumerate(nums):\r\n num2 = target - num1\r\n if num2 in dct:\r\n return [dct[num2], i]\r\n dct[num1] = i\r\n\r\n\r\nprint(two_sum([14, 2, 31, 4], 6))\r\n","<docstring token>\n\n\ndef two_sum(nums, target):\n dct = {}\n for i, num1 in enumerate(nums):\n num2 = target - num1\n if num2 in dct:\n return [dct[num2], i]\n dct[num1] = i\n\n\nprint(two_sum([14, 2, 31, 4], 6))\n","<docstring token>\n\n\ndef two_sum(nums, target):\n dct = {}\n for i, num1 in enumerate(nums):\n num2 = target - num1\n if num2 in dct:\n return [dct[num2], i]\n dct[num1] = i\n\n\n<code token>\n","<docstring token>\n<function token>\n<code token>\n"],"string":"[\n \"\\\"\\\"\\\"\\r\\n时间最优\\r\\n\\r\\n思路：\\r\\n将和为目标值的那 两个 整数定义为 num1 和 num2\\r\\n创建一个新字典，内容存在数组中的数字及索引\\r\\n将数组nums转换为字典，\\r\\n遍历字典， num1为字典中的元素（其实与数组总的元素一样），\\r\\nnum2 为 target减去num1， 判定num2是否在字典中，如果存在，返回字典中num2的值（也就是在数组nums中的下标）和 i（也就是num1在数组中的下标）\\r\\n如果不存在，设置字典num1的值为i\\r\\n\\\"\\\"\\\"\\r\\n\\r\\ndef two_sum(nums, target):\\r\\n dct = {}\\r\\n for i, num1 in enumerate(nums):\\r\\n num2 = target - num1\\r\\n if num2 in dct:\\r\\n return [dct[num2], i]\\r\\n dct[num1] = i\\r\\n\\r\\n\\r\\nprint(two_sum([14, 2, 31, 4], 6))\\r\\n\",\n \"<docstring token>\\n\\n\\ndef two_sum(nums, target):\\n dct = {}\\n for i, num1 in enumerate(nums):\\n num2 = target - num1\\n if num2 in dct:\\n return [dct[num2], i]\\n dct[num1] = i\\n\\n\\nprint(two_sum([14, 2, 31, 4], 6))\\n\",\n \"<docstring token>\\n\\n\\ndef two_sum(nums, target):\\n dct = {}\\n for i, num1 in enumerate(nums):\\n num2 = target - num1\\n if num2 in dct:\\n return [dct[num2], i]\\n dct[num1] = i\\n\\n\\n<code token>\\n\",\n \"<docstring token>\\n<function token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8675,"cells":{"index":{"kind":"number","value":8675,"string":"8,675"},"blob_id":{"kind":"string","value":"60d8276a5715899823b12ffdf132925c6f2693bd"},"code":{"kind":"string","value":"from __future__ import annotations\n\n\nfrom typing import TYPE_CHECKING\nfrom datetime import datetime\n\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\nfrom sqlalchemy.orm import relationship\n\nfrom app.db.base_class import Base\n\nif TYPE_CHECKING:\n from .account import Account # noqa: F401\n from .code import Code # noqa: F401\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n amount = Column(Float, default=0, nullable=False)\n vtime = Column(DateTime(), nullable=False)\n\n vtype = Column(String(50), ForeignKey(\"t_juju_code.vtype\"))\n\n comment = Column(String(150), nullable=True)\n create_time = Column(DateTime(), default=datetime.now)\n update_time = Column(DateTime(), default=datetime.now,\n onupdate=datetime.now)\n\n owner_id = Column(Integer, ForeignKey(\"t_juju_account.id\"))\n modifier_id = Column(Integer, ForeignKey(\"t_juju_account.id\"))\n"},"steps":{"kind":"list like","value":["from __future__ import annotations\n\n\nfrom typing import TYPE_CHECKING\nfrom datetime import datetime\n\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\nfrom sqlalchemy.orm import relationship\n\nfrom app.db.base_class import Base\n\nif TYPE_CHECKING:\n from .account import Account # noqa: F401\n from .code import Code # noqa: F401\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n amount = Column(Float, default=0, nullable=False)\n vtime = Column(DateTime(), nullable=False)\n\n vtype = Column(String(50), ForeignKey(\"t_juju_code.vtype\"))\n\n comment = Column(String(150), nullable=True)\n create_time = Column(DateTime(), default=datetime.now)\n update_time = Column(DateTime(), default=datetime.now,\n onupdate=datetime.now)\n\n owner_id = Column(Integer, ForeignKey(\"t_juju_account.id\"))\n modifier_id = Column(Integer, ForeignKey(\"t_juju_account.id\"))\n","from __future__ import annotations\nfrom typing import TYPE_CHECKING\nfrom datetime import datetime\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\nfrom sqlalchemy.orm import relationship\nfrom app.db.base_class import Base\nif TYPE_CHECKING:\n from .account import Account\n from .code import Code\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n amount = Column(Float, default=0, nullable=False)\n vtime = Column(DateTime(), nullable=False)\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\n comment = Column(String(150), nullable=True)\n create_time = Column(DateTime(), default=datetime.now)\n update_time = Column(DateTime(), default=datetime.now, onupdate=\n datetime.now)\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\n","<import token>\nif TYPE_CHECKING:\n from .account import Account\n from .code import Code\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n amount = Column(Float, default=0, nullable=False)\n vtime = Column(DateTime(), nullable=False)\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\n comment = Column(String(150), nullable=True)\n create_time = Column(DateTime(), default=datetime.now)\n update_time = Column(DateTime(), default=datetime.now, onupdate=\n datetime.now)\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\n","<import token>\n<code token>\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n amount = Column(Float, default=0, nullable=False)\n vtime = Column(DateTime(), nullable=False)\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\n comment = Column(String(150), nullable=True)\n create_time = Column(DateTime(), default=datetime.now)\n update_time = Column(DateTime(), default=datetime.now, onupdate=\n datetime.now)\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\n","<import token>\n<code token>\n\n\nclass Voucher(Base):\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n","<import token>\n<code token>\n<class token>\n"],"string":"[\n \"from __future__ import annotations\\n\\n\\nfrom typing import TYPE_CHECKING\\nfrom datetime import datetime\\n\\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\\nfrom sqlalchemy.orm import relationship\\n\\nfrom app.db.base_class import Base\\n\\nif TYPE_CHECKING:\\n from .account import Account # noqa: F401\\n from .code import Code # noqa: F401\\n\\n\\nclass Voucher(Base):\\n __tablename__ = 't_juju_voucher'\\n code = Column(String(100), index=True, unique=True)\\n serial_no = Column(String(120), index=True, unique=True)\\n amount = Column(Float, default=0, nullable=False)\\n vtime = Column(DateTime(), nullable=False)\\n\\n vtype = Column(String(50), ForeignKey(\\\"t_juju_code.vtype\\\"))\\n\\n comment = Column(String(150), nullable=True)\\n create_time = Column(DateTime(), default=datetime.now)\\n update_time = Column(DateTime(), default=datetime.now,\\n onupdate=datetime.now)\\n\\n owner_id = Column(Integer, ForeignKey(\\\"t_juju_account.id\\\"))\\n modifier_id = Column(Integer, ForeignKey(\\\"t_juju_account.id\\\"))\\n\",\n \"from __future__ import annotations\\nfrom typing import TYPE_CHECKING\\nfrom datetime import datetime\\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\\nfrom sqlalchemy.orm import relationship\\nfrom app.db.base_class import Base\\nif TYPE_CHECKING:\\n from .account import Account\\n from .code import Code\\n\\n\\nclass Voucher(Base):\\n __tablename__ = 't_juju_voucher'\\n code = Column(String(100), index=True, unique=True)\\n serial_no = Column(String(120), index=True, unique=True)\\n amount = Column(Float, default=0, nullable=False)\\n vtime = Column(DateTime(), nullable=False)\\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\\n comment = Column(String(150), nullable=True)\\n create_time = Column(DateTime(), default=datetime.now)\\n update_time = Column(DateTime(), default=datetime.now, onupdate=\\n datetime.now)\\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n\",\n \"<import token>\\nif TYPE_CHECKING:\\n from .account import Account\\n from .code import Code\\n\\n\\nclass Voucher(Base):\\n __tablename__ = 't_juju_voucher'\\n code = Column(String(100), index=True, unique=True)\\n serial_no = Column(String(120), index=True, unique=True)\\n amount = Column(Float, default=0, nullable=False)\\n vtime = Column(DateTime(), nullable=False)\\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\\n comment = Column(String(150), nullable=True)\\n create_time = Column(DateTime(), default=datetime.now)\\n update_time = Column(DateTime(), default=datetime.now, onupdate=\\n datetime.now)\\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n\",\n \"<import token>\\n<code token>\\n\\n\\nclass Voucher(Base):\\n __tablename__ = 't_juju_voucher'\\n code = Column(String(100), index=True, unique=True)\\n serial_no = Column(String(120), index=True, unique=True)\\n amount = Column(Float, default=0, nullable=False)\\n vtime = Column(DateTime(), nullable=False)\\n vtype = Column(String(50), ForeignKey('t_juju_code.vtype'))\\n comment = Column(String(150), nullable=True)\\n create_time = Column(DateTime(), default=datetime.now)\\n update_time = Column(DateTime(), default=datetime.now, onupdate=\\n datetime.now)\\n owner_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n modifier_id = Column(Integer, ForeignKey('t_juju_account.id'))\\n\",\n \"<import token>\\n<code token>\\n\\n\\nclass Voucher(Base):\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n\",\n \"<import token>\\n<code token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8676,"cells":{"index":{"kind":"number","value":8676,"string":"8,676"},"blob_id":{"kind":"string","value":"c87ede0e3c6d4cc305450f68b4cf61fb63986760"},"code":{"kind":"string","value":"import uvicore\nfrom uvicore.support import module\nfrom uvicore.typing import Dict, List\nfrom uvicore.support.dumper import dump, dd\nfrom uvicore.contracts import Email\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *,\n mailer: str = None,\n mailer_options: Dict = None,\n to: List = [],\n cc: List = [],\n bcc: List = [],\n from_name: str = None,\n from_address: str = None,\n subject: str = None,\n html: str = None,\n text: str = None,\n attachments: List = [],\n ) -> None:\n # Get mailer and options from config\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone().merge(mailer_options)\n\n # New message superdict\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n\n def from_address(self, from_address: str):\n self._message.from_address = from_address\n return self\n\n def subject(self, subject: str):\n self._message.subject = subject\n return self\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n # Use dynamic module based on mailer driver\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n"},"steps":{"kind":"list like","value":["import uvicore\nfrom uvicore.support import module\nfrom uvicore.typing import Dict, List\nfrom uvicore.support.dumper import dump, dd\nfrom uvicore.contracts import Email\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *,\n mailer: str = None,\n mailer_options: Dict = None,\n to: List = [],\n cc: List = [],\n bcc: List = [],\n from_name: str = None,\n from_address: str = None,\n subject: str = None,\n html: str = None,\n text: str = None,\n attachments: List = [],\n ) -> None:\n # Get mailer and options from config\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone().merge(mailer_options)\n\n # New message superdict\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n\n def from_address(self, from_address: str):\n self._message.from_address = from_address\n return self\n\n def subject(self, subject: str):\n self._message.subject = subject\n return self\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n # Use dynamic module based on mailer driver\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","import uvicore\nfrom uvicore.support import module\nfrom uvicore.typing import Dict, List\nfrom uvicore.support.dumper import dump, dd\nfrom uvicore.contracts import Email\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n\n def from_address(self, from_address: str):\n self._message.from_address = from_address\n return self\n\n def subject(self, subject: str):\n self._message.subject = subject\n return self\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n\n def from_address(self, from_address: str):\n self._message.from_address = from_address\n return self\n\n def subject(self, subject: str):\n self._message.subject = subject\n return self\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n\n def from_address(self, from_address: str):\n self._message.from_address = from_address\n return self\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n\n def mailer(self, mailer: str):\n self._mailer = mailer\n self._mailer_options = self._config.mailers[self._mailer].clone()\n return self\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n\n def to(self, to: List):\n self._message.to = to\n return self\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n\n def from_name(self, from_name: str):\n self._message.from_name = from_name\n return self\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n <function token>\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n\n def attachments(self, attachments: List):\n self._message.attachments = attachments\n return self\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n <function token>\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n\n def text(self, text: str):\n self._message.text = text\n return self\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n\n def bcc(self, bcc: List):\n self._message.bcc = bcc\n return self\n <function token>\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n <function token>\n <function token>\n <function token>\n <function token>\n\n def html(self, html: str):\n self._message.html = html\n return self\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n\n def mailer_options(self, options: Dict):\n self._mailer_options.merge(Dict(options))\n return self\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subject: str=None, html: str=None, text:\n str=None, attachments: List=[]) ->None:\n self._config = uvicore.config.app.mail.clone()\n self._mailer = mailer or self._config.default\n self._mailer_options = self._config.mailers[self._mailer].clone(\n ).merge(mailer_options)\n self._message: Email = Email()\n self._message.to = to\n self._message.cc = cc\n self._message.bcc = bcc\n self._message.from_name = from_name or self._config.from_name\n self._message.from_address = from_address or self._config.from_address\n self._message.subject = subject\n self._message.html = html\n self._message.text = text\n self._message.attachments = attachments\n <function token>\n <function token>\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n <function token>\n <function token>\n <function token>\n <function token>\n\n def cc(self, cc: List):\n self._message.cc = cc\n return self\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n\n\n@uvicore.service()\nclass Mail:\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n async def send(self):\n driver = module.load(self._mailer_options.driver).object\n await driver.send(self._message, self._mailer_options)\n","<import token>\n<class token>\n"],"string":"[\n \"import uvicore\\nfrom uvicore.support import module\\nfrom uvicore.typing import Dict, List\\nfrom uvicore.support.dumper import dump, dd\\nfrom uvicore.contracts import Email\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *,\\n mailer: str = None,\\n mailer_options: Dict = None,\\n to: List = [],\\n cc: List = [],\\n bcc: List = [],\\n from_name: str = None,\\n from_address: str = None,\\n subject: str = None,\\n html: str = None,\\n text: str = None,\\n attachments: List = [],\\n ) -> None:\\n # Get mailer and options from config\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone().merge(mailer_options)\\n\\n # New message superdict\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n\\n def mailer(self, mailer: str):\\n self._mailer = mailer\\n self._mailer_options = self._config.mailers[self._mailer].clone()\\n return self\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n\\n def from_address(self, from_address: str):\\n self._message.from_address = from_address\\n return self\\n\\n def subject(self, subject: str):\\n self._message.subject = subject\\n return self\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n # Use dynamic module based on mailer driver\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"import uvicore\\nfrom uvicore.support import module\\nfrom uvicore.typing import Dict, List\\nfrom uvicore.support.dumper import dump, dd\\nfrom uvicore.contracts import Email\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n\\n def mailer(self, mailer: str):\\n self._mailer = mailer\\n self._mailer_options = self._config.mailers[self._mailer].clone()\\n return self\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n\\n def from_address(self, from_address: str):\\n self._message.from_address = from_address\\n return self\\n\\n def subject(self, subject: str):\\n self._message.subject = subject\\n return self\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n\\n def mailer(self, mailer: str):\\n self._mailer = mailer\\n self._mailer_options = self._config.mailers[self._mailer].clone()\\n return self\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n\\n def from_address(self, from_address: str):\\n self._message.from_address = from_address\\n return self\\n\\n def subject(self, subject: str):\\n self._message.subject = subject\\n return self\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n\\n def mailer(self, mailer: str):\\n self._mailer = mailer\\n self._mailer_options = self._config.mailers[self._mailer].clone()\\n return self\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n\\n def from_address(self, from_address: str):\\n self._message.from_address = from_address\\n return self\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n\\n def mailer(self, mailer: str):\\n self._mailer = mailer\\n self._mailer_options = self._config.mailers[self._mailer].clone()\\n return self\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n\\n def to(self, to: List):\\n self._message.to = to\\n return self\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n\\n def from_name(self, from_name: str):\\n self._message.from_name = from_name\\n return self\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n\\n def attachments(self, attachments: List):\\n self._message.attachments = attachments\\n return self\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n\\n def text(self, text: str):\\n self._message.text = text\\n return self\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n\\n def bcc(self, bcc: List):\\n self._message.bcc = bcc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def html(self, html: str):\\n self._message.html = html\\n return self\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n\\n def mailer_options(self, options: Dict):\\n self._mailer_options.merge(Dict(options))\\n return self\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n\\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\\n from_address: str=None, subject: str=None, html: str=None, text:\\n str=None, attachments: List=[]) ->None:\\n self._config = uvicore.config.app.mail.clone()\\n self._mailer = mailer or self._config.default\\n self._mailer_options = self._config.mailers[self._mailer].clone(\\n ).merge(mailer_options)\\n self._message: Email = Email()\\n self._message.to = to\\n self._message.cc = cc\\n self._message.bcc = bcc\\n self._message.from_name = from_name or self._config.from_name\\n self._message.from_address = from_address or self._config.from_address\\n self._message.subject = subject\\n self._message.html = html\\n self._message.text = text\\n self._message.attachments = attachments\\n <function token>\\n <function token>\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def cc(self, cc: List):\\n self._message.cc = cc\\n return self\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n\\n\\n@uvicore.service()\\nclass Mail:\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n async def send(self):\\n driver = module.load(self._mailer_options.driver).object\\n await driver.send(self._message, self._mailer_options)\\n\",\n \"<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8677,"cells":{"index":{"kind":"number","value":8677,"string":"8,677"},"blob_id":{"kind":"string","value":"4a8a733a965e25ad7ef53600fad6dd47343655b0"},"code":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 12 16:38:22 2017\n\n@author: secoder\n\"\"\"\nimport io\nimport random\nimport nltk\nfrom nltk.tokenize import RegexpTokenizer\n\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\n\n\nfrom collections import OrderedDict\nfrom collections import Counter\n\nfrom sklearn.metrics import pairwise_distances\n\nimport numpy as np\nimport scipy\n\nimport json\nimport codecs\n\nfrom dateutil import parser\nimport time\nimport datetime\n\nimport operator\n\n#import cPickle as pickle\n#\n#import traceback\n\nfrom skimage import filters\n\nimport unicodedata as ud\n\nfrom config import project_name\n\n\nclass recommendationsys:\n \n def __init__(self, nyear):\n \n # by default we will filter out those don't have publications in recent 10 years\n self.activityyear = 10\n\n self.debug = 0 \n self.nremd = 3\n \n #----------------------\n PROJECT_DIRECTORY = 'output/project/' + project_name\n\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n\n \n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n #---------------------- \n \n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n \n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n \n \n \"\"\"\n \"\"\"\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n \n \"\"\"\n \"\"\" \n def resentpublicationsidx(self,authoridx):\n #print 'start recentpublications\\n'\n resentpub = []\n \n idx = self.authortitlesidx[authoridx]\n \n # sort by years\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n \n # if the most recent publication is before the 'nyears' \n # remove this one from the list\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\n return resentpub\n # ---- \n \n for i in idx:\n authorsjson = [] \n \n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([(\"name\",author)]))\n \n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\"%Y-%m-%d %H:%M:%S\")\n resentpub.append(OrderedDict([(\"title\",self.rawtitles[i]),(\"authors\",authorsjson), (\"year\",date),(\"publicationVenue\",self.booktitle[i])]))\n\n #print 'end recentpublications\\n'\n return resentpub\n \n \n \"\"\"\n \"\"\"\n def resentpublications(self,name):\n #print 'start recentpublications\\n'\n resentpub = []\n\n #if isinstance(name, unicode): for python 2.7\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n idx = self.authortitlesidx[idx]\n \n # sort by years\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n \n # if the most recent publication is before the 'nyears' \n # remove this one from the list\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\n return resentpub\n # ---- \n \n for i in idx:\n authorsjson = [] \n \n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([(\"name\",author)]))\n \n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\"%Y-%m-%d %H:%M:%S\")\n resentpub.append(OrderedDict([(\"title\",self.rawtitles[i]),(\"authors\",authorsjson), (\"year\",date),(\"publicationVenue\",self.booktitle[i])]))\n\n #print 'end recentpublications\\n'\n return resentpub\n \n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs=[]\n\n# for title in self.titles:\n# pairs = pairs + list(nltk.bigrams(title.split()))\n\n pairs = nltk.bigrams(self.allcorp)\n \n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n \n def keyword(self,name):\n #print 'start keyword\\n'\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n# content = self.authorcontents[idx].lower()\n# \n# # get the unique words from the content\n# content = set(content.split())\n# \n# i = []\n# for c in content:\n# count = self.vectorizer.vocabulary_.get(c, 0) \n# i.append(count)\n# \n# i = np.array(i)\n# i = i.argsort()\n# content = np.array(list(content))\n# content = content[i]\n# content = content[-3:]\n# keywords = list(reversed(content)) \n# \n contentjson = []\n# for topic in keywords:\n# contentjson.append(OrderedDict([(\"topic\", topic)]))\n \n # bigram keywords -------------\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n# #print 'start bigram\\n'\n# \n# userpairs = list(nltk.bigrams(content))\n# \n# \n# # do the same on raw titles \n# \n# keywordsraw=[]\n# for p in userpairs:\n# pairsdic=self.cfd[p[0]]\n# n=pairsdic[p[1]]\n# if n>=2:\n# keywordsraw.append((p,n))\n# \n# uniqkeywords=set(keywordsraw)\n# keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\n# \n# finalkeywords=[]\n# for p in keywords:\n# #c=wn.synsets(p[0][1])[0].pos()\n# if (p[1]>=2):\n# finalkeywords.append((' '.join(p[0]),p[1],keywordsraw.count(p)))\n# \n# finalkeywords.reverse()\n \n for topic in finalkeywords:\n #print topic[0]\n contentjson.append(OrderedDict([(\"topic\", topic[0])]))\n \n #print 'end bigram\\n'\n #print 'end keyword\\n'\n return contentjson\n \n \"\"\"\n \"\"\"\n def keywordbyidx(self,idx):\n \n contentjson = []\n \n # bigram keywords -------------\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n \n for topic in finalkeywords:\n #print topic[0]\n contentjson.append(OrderedDict([(\"topic\", topic[0])]))\n \n return contentjson\n\n \n \"\"\"\n \"\"\" \n def bigramkeywords(self, text):\n #print 'start bigramkeyword\\n'\n # bigram keywords -------------\n #content = text.lower().split()\n content = text\n #print 'start bigram\\n'\n \n userpairs = list(nltk.bigrams(content))\n \n \n # in case there is no valid keywords due to our requirement\n # the one with highest occurrence will be pick from the backup plan \n keywordsbackup = []\n # the valid keywords\n keywords=[]\n for p in userpairs:\n pairsdic=self.cfd[p[0]]\n n=pairsdic[p[1]]\n if n>=self.keywordthreshold:\n keywords.append((p,n))\n keywordsbackup.append((p,n))\n\n finalkeywords=[]\n \n uniqkeywords=set(keywords)\n keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if (p[1]>=25) or (userpairs.count(p[0])>1):\n finalkeywords.append([' '.join(p[0]),p[1],userpairs.count(p[0])])\n \n finalkeywords.reverse() \n \n \n \n if not finalkeywords:\n # found valid keywords\n uniqkeywords=set(keywordsbackup)\n keywordsbackup=sorted(uniqkeywords, key=lambda keywordsbackup: keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]), keywordsbackup[-1][1],userpairs.count(keywordsbackup[0])])\n else: \n # deal with plural\n pluralidx = self.findpluralbigram(finalkeywords)\n \n self.removepluralbigram(finalkeywords,pluralidx)\n \n \n #print 'end bigramkeyword\\n'\n return finalkeywords\n \n \"\"\"\n \"\"\"\n def removepluralbigram(self, bigram, pluralidx):\n # if pluralidx is emtpy, just return\n if not pluralidx:\n print('empty')\n return \n \n delcount = 0\n pren = 0 \n\n for i in pluralidx:\n #delcount = 0\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n \n \n \"\"\"\n \"\"\"\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n\n c.append(t1)\n \n uniqbigram = list(set(c))\n pluralidx = []\n \n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n \n return pluralidx\n \"\"\"\n \"\"\"\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n \n countidx = np.argsort(coauthorcount)\n # reverse it to descend order\n countidx = countidx[::-1]\n \n coauthorcount = np.array(coauthorcount)\n \n result = []\n for i in countidx:\n result.append(OrderedDict([(\"name\",self.authors[uniqcoauthors[i]]),(\"cooperationCount\",coauthorcount[i])]))\n return (result,list(uniqcoauthors[countidx]),list(coauthorcount[countidx]))\n \n \n \n \"\"\"\n \"\"\"\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n\n \"\"\"\n \"\"\"\n def mycoauthorsV4(self, name):\n \n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n \n \n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n \"\"\"\n def mycoauthorsV4byidx(self, idx):\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n \n \n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n \"\"\"\n def mycoauthorsV4bymentionlist(self, name):\n \n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict ={'None':0}\n \n \n result = []\n # sort by mention counts\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.itemgetter(1), reverse=True)\n \n for i in sorted_mentiondict:\n result.append(OrderedDict([(\"name\",i[0]),(\"cooperationCount\",i[1])]))\n \n return result\n \"\"\"\n \"\"\"\n def mycoauthorsbyyear(self, idx, year):\n \n years = np.array(self.years)\n\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [ self.coauthorsidx[i] for i in yearidx]\n \n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n return (list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n find the new coauthors for a user in current year against previous year\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\n \"\"\"\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n \n return newCoauthors\n\n \"\"\"\n Call the weakties after mynewcoauthors() to find the common nodes \n between a user and his/her coming new coauthors in the year before\n their coauthorship\n \"\"\"\n def weakties(self, userX, userY, year):\n \n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\n \n # if userX and userY already have a strong ties, just return []\n if userY in coauthornetX:\n return ([], [], [])\n \n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\n \n # find the common nodes \n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\n \n nodescountX = []\n nodescountY = []\n \n if weaktienodes:\n for i in weaktienodes:\n nodescountX.append(cx[coauthornetX.index(i)])\n nodescountY.append(cy[coauthornetY.index(i)])\n \n \n return (weaktienodes, nodescountX, nodescountY)\n \n \"\"\"\n 2nd hoop connection\n \"\"\"\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i,n],[count1[coauthors1.index(i)],count2[coauthors2.index(n)], count3[coauthors3.index(userY)]]])\n\n\n \"\"\"\n Get all the content(paper titles) of the userIdx before \n the 'year'(include the year) \n \"\"\"\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n\n titleIdx = np.array(titleIdx)\n\n years = [self.years[i] for i in titleIdx]\n\n years = np.array(years)\n \n # sort the years and put the latest year first\n # then the content will also be sorted by recent paper first\n years.sort()\n years = years[::-1]\n\n yearIdx = np.where(years<=year)[0]\n \n content = [self.titles[i] for i in titleIdx[yearIdx]]\n \n return content\n\n \"\"\"\n return the most frequent participated venue of a user\n \"\"\"\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n \n return frqvenues[0][0]\n\n \"\"\"\n only consider the recent 10 papers\n \"\"\"\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n \n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n \n # build the corpus of all the content\n contents = []\n \n \n for i in contentX:\n contents.extend(i.split(' '))\n \n lenx = len(contents)\n \n for i in contentY:\n contents.extend(i.split(' '))\n \n # normalize the different forms of words \n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents] \n \n # reconstruct content for userX and userY use the normalized words\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n\n\n \n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(newcontentY)])\n \n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0]\n \n return cosinesimilarity\n\n \"\"\"\n network similarity\n \"\"\"\n def networksimilarity(self, userX, userY, year):\n \n # first calculate FG(userX) according to paper\n # User similarities on social networks\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n \n edgesFG = len(coauthors)\n \n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n \n # second, calculate MFG(userX, userY)\n weakties, cx, cy = self.weakties(userX, userY, year)\n \n edgesMFG = 2 * len(weakties)\n \n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n \n # last calculate the network similarity\n \n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG)/np.log(2 * edgesFG)\n else:\n ns = -1\n \n return (ns, edgesFG, edgesMFG, cx, cy)\n\n \"\"\"\n text processing, normalize the words to their prototype, such as \n plural form, progressive, etc\n \"\"\"\n def textnormalizing(self, text):\n #l = len(text)\n c = 0\n for i in text:\n # network - networks\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # bus - buses\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # study - studies \n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # network - networking\n # get - getting\n # explore - exploring \n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n \n c = c + 1\n \n return text\n \n \"\"\"\n \"\"\"\n\n \n \"\"\"\n radius of the cluster\n \"\"\"\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n \n dis = dismatrix[idx,nth]\n \n self.mindis = min(dis)\n self.maxdis = max(dis)\n \n self.radius = self.maxdis\n \n \n \n # return [mindis, maxdis, radius]\n \n \n \"\"\"\n show contents in the same cluster\n \"\"\"\n def showcontents(self,labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n \n return contents\n \n \"\"\"\n check if there is digtial in the string\n \"\"\"\n def digstring(self,s):\n for i in s:\n if i.isdigit():\n return True\n return False\n \n \"\"\"\n compute the distance between two points a and b\n \"\"\"\n def distance(self,a,b):\n\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n \n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n \n a = np.array(a);\n b = np.array(b);\n return np.sqrt(sum(np.square(a - b)))\n \n \"\"\"\n \"\"\"\n def updatecoauthornetworkV2(self,net,authors,namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n \n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n # if net is empty\n if not net:\n net.append(tmpidx)\n else:\n if i>len(net)-1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n\n \"\"\"\n load the person or organization label\n \"\"\"\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel,'r','utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1] \n f.close()\n self.labels = labels\n\n \"\"\"\n \"\"\"\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork,'r','utf-8')\n source=''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n\t\t\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n \n f.close()\n return network\n \n \n \"\"\"\n \"\"\"\n def docluster(self):\n tokenizer = RegexpTokenizer(r'\\w+')\n\n\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n\n sw = set(nltk.corpus.stopwords.words('english'))\n \n \n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles,'r','utf-8')\n for line in f: \n # remove the '\\n' at the end\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n \n self.allcorp += tokenlist\n #for corp in newline:\n # self.allcorp.append(corp)\n \n # collect all the words except digtals and stopwords\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in sw) & ~(self.digstring(w))])\n self.titles.append(tokenlist)\n f.close()\n # end use codecs\n \n # filename = './CHI/CHI_authors.txt'\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = [] # undirect link, etc, dblp coauthorship network\n self.mentionnetwork = {} # direct link, etc,tweet mention network\n self.id_name = {}\n \n\n self.coauthornetV2 = []\n \n # readin the mention network\n self.mentionnetwork = self.mention_network()\n \n # read years\n self.debugmsg('start year \\n', 0)\n self.years = []\n \n f = codecs.open(self.f_years,'r','utf-8')\n for line in f:\n # remive \\n\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n #line = line.split()\n #year = line[-1]\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n \n # read conference \n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n \n f = codecs.open(self.f_booktitle,'r','utf-8')\n for line in f:\n # remove the \\n at the end\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n \n # read authors\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors,'r','utf-8')\n\n for line in f:\n # remove the last '\\n' \n line = line[:-1]\n # split the authors by ','\n newline = line.split(\",\")\n namelist = newline\n self.coathors.append(namelist) \n \n \n authoridx = []\n \n for name in newline: \n \n # dictonary version \n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n\n self.authorcontents[idx] = self.authorcontents[idx] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n\n self.authordict[name] = m\n\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n \n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n\n idx = m\n m = m + 1\n authoridx.append(idx)\n # end dict version\n \n self.coauthorsidx.append(authoridx)\n i = i + 1\n\n f.close()\n\n \n f = codecs.open(self.f_authors_id,'r','utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n #print(i)\n #print('preline: {}, line: {}'.format(preline, line))\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n \n else:\n continue\n \n #print(i)\n f.close()\n \n \n # load the per and org classification result\n self.per_org_label()\n \n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1,stop_words='english')\n \n X = self.vectorizer.fit_transform(self.authorcontents)\n \n #Xarray = X.toarray()\n Xarray = X\n \n #plt.plot(hist)\n \n transformer = TfidfTransformer()\n \n self.tfidf = transformer.fit_transform(Xarray)\n #self.tfidfarray = self.tfidf.toarray()\n self.tfidfarray = self.tfidf\n \n self.featurenames = self.vectorizer.get_feature_names()\n\n \n \n \n \n \n \"\"\" \n \"\"\"\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n #idx = self.authors.index(name)\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n name = name.decode('utf-8')\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n \n #content=[]\n \n \n \n self.myidx = authorIdx \n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n \n self.debugmsg('start distance computing \\n', 0)\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\n self.debugmsg('end distance computing \\n', 0)\n\n # here we can define the range to apply the otsu for recommendations\n # for example self.closeauthordis[0:1000] or all them\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis) \n self.debugmsg('end otsufilter\\n', 0) \n \n # splitidx contains the first index of three groups, close, medium, far\n # now generate three recommendations in each group\n recommendations = []\n \n # save the valid remdidx\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n # skip myself go to next one\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n #print remdinfo\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n #self.debugmsg(str(n) + ' ' + str(i), 0)\n \n i = i + 1\n \n # didn't find required number of valid remd untill the end\n # start backwards search\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n #self.debugmsg('search backward ' + str(i), 0)\n \n\n # randomlize the order of the recommendations\n random.shuffle(recommendations)\n \n self.result=OrderedDict([(\"name\",name),(\"recommendations\",recommendations)]) \n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result \n \n \"\"\" \n \"\"\"\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n #idx = self.authors.index(name)\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n name = name.decode('utf-8')\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n \n #content=[]\n \n \n \n self.myidx = authorIdx \n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n \n self.debugmsg('start distance computing \\n', 0)\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\n self.debugmsg('end distance computing \\n', 0)\n\n # here we can define the range to apply the otsu for recommendations\n # for example self.closeauthordis[0:1000] or all them\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis) \n self.debugmsg('end otsufilter\\n', 0) \n \n # splitidx contains the first index of three groups, close, medium, far\n # now generate three recommendations in each group\n recommendations = []\n \n # save the valid remdidx\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n # skip myself go to next one\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n #print remdinfo\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n #self.debugmsg(str(n) + ' ' + str(i), 0)\n \n i = i + 1\n \n # didn't find required number of valid remd untill the end\n # start backwards search\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n #self.debugmsg('search backward ' + str(i), 0)\n \n\n # randomlize the order of the recommendations\n random.shuffle(recommendations)\n \n self.result=OrderedDict([(\"name\",name),(\"recommendations\",recommendations)]) \n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result \n \n \"\"\"\n find n nearset neighbors of point p in given space using linear search\n if n == 0, sort all the points in space\n \"\"\"\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n \n\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n \n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n \n if n > 0 :\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n \n # delete myself, cuz the distance is always 0\n idx = np.where(closeauthors == self.myidx)[0][0]\n \n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n \n return (closeauthors, closeauthordis)\n \n\n\n \"\"\"\n split the distance in to 3 groups using otsu filtering\n return the first index of each group\n \"\"\"\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n \n #tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis>t1])\n \n # the first index of each group\n# trd[1] = len(tdis[tdis<t1])\n# trd[2] = len(tdis) - len(tdis[tdis>t2])\n \n # get the medium 3 in the medium group\n # get the last 3 in the far group\n trd[1] = len(tdis[tdis<t1]) + int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\n trd[2] = len(tdis) - 3 \n \n return trd\n\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove my co-authors\n \"\"\"\n def getremdinfo(self, clsidx):\n # get the author index from closeauthors\n remdidx = self.closeauthors[clsidx]\n \n recentpub = self.resentpublicationsidx(remdidx)\n \n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n \n if idx.count(self.myidx):\n # remove the coauthor\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[clsidx]),(\"coAuthors\",coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])\n else:\n return []\n\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove known people in the mention network\n \"\"\"\n def getremdinfoV2(self, clsidx):\n # get the author index from closeauthors\n remdidx = self.closeauthors[clsidx]\n \n username = self.authors[self.myidx]\n \n recentpub = self.resentpublicationsidx(remdidx)\n \n if recentpub:\n name = self.authors[remdidx]\n #[coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n mentionlist = self.mentionnetwork[username]\n \n if name in mentionlist:\n # skip the coauthor\n return []\n \n #\n remdid = self.id_name[name]\n \n if self.labels[remdid] == 'org':\n return []\n \n # get the recommendation's mention list\n coauthors = self.mycoauthorsV4bymentionlist(name)\n \n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[clsidx]),(\"coAuthors\", coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])\n else:\n return []\n\n \"\"\"\n \"\"\"\n def updatedistance(self):\n # 1st degree connection in coauthorship\n deg1con=self.coauthornet[self.myidx,self.closeauthors]\n deg1conidx = np.where(deg1con>0)[0]\n #deg1con = deg1con[deg1con>0]\n \n # 2nd degree connection in coauthorship\n deg2conidx = np.where(deg1con==0)[0]\n deg2con = np.zeros(deg2conidx.size)\n \n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i,self.closeauthors[deg2conidx]]\n \n deg1con = deg1con[deg1con>0]\n \n deg1con = deg1con/max(deg1con)\n return (deg1conidx, deg1con,deg2conidx,deg2con)\n \n \"\"\"\n return the top N recommendations:\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \n morethan 5 years) \n \"\"\"\n def filteredrecommendations(self, n):\n \n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n \n i = 0\n for name in self.recommendauthor:\n #coauthors = []\n #researchtopic = []\n #recentpub = []\n #coauthorsjson = []\n #[coauthors, idx, c] = self.mycoauthors(name)\n #[coauthors, idx, c] = self.mycoauthorsV2(name)\n #[coauthors, idx, c] = self.mycoauthorsV3(name)\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n\n # remove the coauthors \n if idx.count(self.myidx):\n i = i+1\n continue\n \n recentpub = self.resentpublications(name)\n\n # check if the recentpub is empty which is not active anymore\n if not recentpub:\n i = i+1\n continue\n # -- \n\n self.filteredauthors.append(name) \n \n # take too much time skip in test\n # researchtopic = self.keyword(name)\n researchtopic = []\n researchtopic.append(OrderedDict([(\"topic\", \"TBD\")]))\n \n \n #recommendations.append({'name':name, 'coAuthors':coauthors, 'researchTopcs':researchtopic, 'recentPublications':recentpub} )\n recommendations.append(OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[i]),(\"coAuthors\",coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])) \n #result={'name':user, 'recommendations':recommendations};\n \n # save the picked idx\n self.filteridx.append(i) \n i = i+1\n \n # only need top n recommendations\n \n if len(self.filteridx) == n:\n break\n \n return recommendations\n \n \n \"\"\"\n \"\"\"\n def thresholdrecommendations(self, remds,n):\n \n thredremd = []\n self.trd = np.zeros(3)\n \n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis>t1])\n \n # get the top 3 in each group\n self.trd[1] = len(tdis[tdis<t1])\n self.trd[2] = len(tdis) - len(tdis[tdis>t2])\n \n # get the top 3 in first group, median 3 in second group, \n # last 3 in third group\n# self.trd[1] = int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\n# self.trd[2] = len(tdis) - 3\n \n \n for i in range(3):\n for j in range(int(n/3)):\n k = int(self.trd[i]+j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n \n return thredremd\n \n\n \n \"\"\"\n \"\"\"\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n \n \n \"\"\"\n \"\"\"\n def save_json(self,filename): \n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename +'.json','w',encoding=\"utf-8\") as outfile:\n outfile.write((json.dumps((self.result), ensure_ascii=False)))\n \n \n"},"steps":{"kind":"list like","value":["# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 12 16:38:22 2017\n\n@author: secoder\n\"\"\"\nimport io\nimport random\nimport nltk\nfrom nltk.tokenize import RegexpTokenizer\n\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\n\n\nfrom collections import OrderedDict\nfrom collections import Counter\n\nfrom sklearn.metrics import pairwise_distances\n\nimport numpy as np\nimport scipy\n\nimport json\nimport codecs\n\nfrom dateutil import parser\nimport time\nimport datetime\n\nimport operator\n\n#import cPickle as pickle\n#\n#import traceback\n\nfrom skimage import filters\n\nimport unicodedata as ud\n\nfrom config import project_name\n\n\nclass recommendationsys:\n \n def __init__(self, nyear):\n \n # by default we will filter out those don't have publications in recent 10 years\n self.activityyear = 10\n\n self.debug = 0 \n self.nremd = 3\n \n #----------------------\n PROJECT_DIRECTORY = 'output/project/' + project_name\n\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n\n \n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n #---------------------- \n \n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n \n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n \n \n \"\"\"\n \"\"\"\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n \n \"\"\"\n \"\"\" \n def resentpublicationsidx(self,authoridx):\n #print 'start recentpublications\\n'\n resentpub = []\n \n idx = self.authortitlesidx[authoridx]\n \n # sort by years\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n \n # if the most recent publication is before the 'nyears' \n # remove this one from the list\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\n return resentpub\n # ---- \n \n for i in idx:\n authorsjson = [] \n \n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([(\"name\",author)]))\n \n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\"%Y-%m-%d %H:%M:%S\")\n resentpub.append(OrderedDict([(\"title\",self.rawtitles[i]),(\"authors\",authorsjson), (\"year\",date),(\"publicationVenue\",self.booktitle[i])]))\n\n #print 'end recentpublications\\n'\n return resentpub\n \n \n \"\"\"\n \"\"\"\n def resentpublications(self,name):\n #print 'start recentpublications\\n'\n resentpub = []\n\n #if isinstance(name, unicode): for python 2.7\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n idx = self.authortitlesidx[idx]\n \n # sort by years\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n \n # if the most recent publication is before the 'nyears' \n # remove this one from the list\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\n return resentpub\n # ---- \n \n for i in idx:\n authorsjson = [] \n \n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([(\"name\",author)]))\n \n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\"%Y-%m-%d %H:%M:%S\")\n resentpub.append(OrderedDict([(\"title\",self.rawtitles[i]),(\"authors\",authorsjson), (\"year\",date),(\"publicationVenue\",self.booktitle[i])]))\n\n #print 'end recentpublications\\n'\n return resentpub\n \n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs=[]\n\n# for title in self.titles:\n# pairs = pairs + list(nltk.bigrams(title.split()))\n\n pairs = nltk.bigrams(self.allcorp)\n \n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n \n def keyword(self,name):\n #print 'start keyword\\n'\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n# content = self.authorcontents[idx].lower()\n# \n# # get the unique words from the content\n# content = set(content.split())\n# \n# i = []\n# for c in content:\n# count = self.vectorizer.vocabulary_.get(c, 0) \n# i.append(count)\n# \n# i = np.array(i)\n# i = i.argsort()\n# content = np.array(list(content))\n# content = content[i]\n# content = content[-3:]\n# keywords = list(reversed(content)) \n# \n contentjson = []\n# for topic in keywords:\n# contentjson.append(OrderedDict([(\"topic\", topic)]))\n \n # bigram keywords -------------\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n# #print 'start bigram\\n'\n# \n# userpairs = list(nltk.bigrams(content))\n# \n# \n# # do the same on raw titles \n# \n# keywordsraw=[]\n# for p in userpairs:\n# pairsdic=self.cfd[p[0]]\n# n=pairsdic[p[1]]\n# if n>=2:\n# keywordsraw.append((p,n))\n# \n# uniqkeywords=set(keywordsraw)\n# keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\n# \n# finalkeywords=[]\n# for p in keywords:\n# #c=wn.synsets(p[0][1])[0].pos()\n# if (p[1]>=2):\n# finalkeywords.append((' '.join(p[0]),p[1],keywordsraw.count(p)))\n# \n# finalkeywords.reverse()\n \n for topic in finalkeywords:\n #print topic[0]\n contentjson.append(OrderedDict([(\"topic\", topic[0])]))\n \n #print 'end bigram\\n'\n #print 'end keyword\\n'\n return contentjson\n \n \"\"\"\n \"\"\"\n def keywordbyidx(self,idx):\n \n contentjson = []\n \n # bigram keywords -------------\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n \n for topic in finalkeywords:\n #print topic[0]\n contentjson.append(OrderedDict([(\"topic\", topic[0])]))\n \n return contentjson\n\n \n \"\"\"\n \"\"\" \n def bigramkeywords(self, text):\n #print 'start bigramkeyword\\n'\n # bigram keywords -------------\n #content = text.lower().split()\n content = text\n #print 'start bigram\\n'\n \n userpairs = list(nltk.bigrams(content))\n \n \n # in case there is no valid keywords due to our requirement\n # the one with highest occurrence will be pick from the backup plan \n keywordsbackup = []\n # the valid keywords\n keywords=[]\n for p in userpairs:\n pairsdic=self.cfd[p[0]]\n n=pairsdic[p[1]]\n if n>=self.keywordthreshold:\n keywords.append((p,n))\n keywordsbackup.append((p,n))\n\n finalkeywords=[]\n \n uniqkeywords=set(keywords)\n keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if (p[1]>=25) or (userpairs.count(p[0])>1):\n finalkeywords.append([' '.join(p[0]),p[1],userpairs.count(p[0])])\n \n finalkeywords.reverse() \n \n \n \n if not finalkeywords:\n # found valid keywords\n uniqkeywords=set(keywordsbackup)\n keywordsbackup=sorted(uniqkeywords, key=lambda keywordsbackup: keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]), keywordsbackup[-1][1],userpairs.count(keywordsbackup[0])])\n else: \n # deal with plural\n pluralidx = self.findpluralbigram(finalkeywords)\n \n self.removepluralbigram(finalkeywords,pluralidx)\n \n \n #print 'end bigramkeyword\\n'\n return finalkeywords\n \n \"\"\"\n \"\"\"\n def removepluralbigram(self, bigram, pluralidx):\n # if pluralidx is emtpy, just return\n if not pluralidx:\n print('empty')\n return \n \n delcount = 0\n pren = 0 \n\n for i in pluralidx:\n #delcount = 0\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n \n \n \"\"\"\n \"\"\"\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n\n c.append(t1)\n \n uniqbigram = list(set(c))\n pluralidx = []\n \n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n \n return pluralidx\n \"\"\"\n \"\"\"\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n \n countidx = np.argsort(coauthorcount)\n # reverse it to descend order\n countidx = countidx[::-1]\n \n coauthorcount = np.array(coauthorcount)\n \n result = []\n for i in countidx:\n result.append(OrderedDict([(\"name\",self.authors[uniqcoauthors[i]]),(\"cooperationCount\",coauthorcount[i])]))\n return (result,list(uniqcoauthors[countidx]),list(coauthorcount[countidx]))\n \n \n \n \"\"\"\n \"\"\"\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n #idx = self.authors.index(name)\n idx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n\n \"\"\"\n \"\"\"\n def mycoauthorsV4(self, name):\n \n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n \n \n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n \"\"\"\n def mycoauthorsV4byidx(self, idx):\n \n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([(\"name\",self.authors[unicoauthors[-(i+1)]]),(\"cooperationCount\",coauthorcount[-(i+1)])]))\n \n \n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n \"\"\"\n def mycoauthorsV4bymentionlist(self, name):\n \n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict ={'None':0}\n \n \n result = []\n # sort by mention counts\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.itemgetter(1), reverse=True)\n \n for i in sorted_mentiondict:\n result.append(OrderedDict([(\"name\",i[0]),(\"cooperationCount\",i[1])]))\n \n return result\n \"\"\"\n \"\"\"\n def mycoauthorsbyyear(self, idx, year):\n \n years = np.array(self.years)\n\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [ self.coauthorsidx[i] for i in yearidx]\n \n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n # remove itself\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n \n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n \n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n \n return (list(unicoauthors[::-1]),list(coauthorcount[::-1]))\n \n \"\"\"\n find the new coauthors for a user in current year against previous year\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\n \"\"\"\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n \n return newCoauthors\n\n \"\"\"\n Call the weakties after mynewcoauthors() to find the common nodes \n between a user and his/her coming new coauthors in the year before\n their coauthorship\n \"\"\"\n def weakties(self, userX, userY, year):\n \n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\n \n # if userX and userY already have a strong ties, just return []\n if userY in coauthornetX:\n return ([], [], [])\n \n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\n \n # find the common nodes \n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\n \n nodescountX = []\n nodescountY = []\n \n if weaktienodes:\n for i in weaktienodes:\n nodescountX.append(cx[coauthornetX.index(i)])\n nodescountY.append(cy[coauthornetY.index(i)])\n \n \n return (weaktienodes, nodescountX, nodescountY)\n \n \"\"\"\n 2nd hoop connection\n \"\"\"\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i,n],[count1[coauthors1.index(i)],count2[coauthors2.index(n)], count3[coauthors3.index(userY)]]])\n\n\n \"\"\"\n Get all the content(paper titles) of the userIdx before \n the 'year'(include the year) \n \"\"\"\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n\n titleIdx = np.array(titleIdx)\n\n years = [self.years[i] for i in titleIdx]\n\n years = np.array(years)\n \n # sort the years and put the latest year first\n # then the content will also be sorted by recent paper first\n years.sort()\n years = years[::-1]\n\n yearIdx = np.where(years<=year)[0]\n \n content = [self.titles[i] for i in titleIdx[yearIdx]]\n \n return content\n\n \"\"\"\n return the most frequent participated venue of a user\n \"\"\"\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n \n return frqvenues[0][0]\n\n \"\"\"\n only consider the recent 10 papers\n \"\"\"\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n \n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n \n # build the corpus of all the content\n contents = []\n \n \n for i in contentX:\n contents.extend(i.split(' '))\n \n lenx = len(contents)\n \n for i in contentY:\n contents.extend(i.split(' '))\n \n # normalize the different forms of words \n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents] \n \n # reconstruct content for userX and userY use the normalized words\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n\n\n \n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(newcontentY)])\n \n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0]\n \n return cosinesimilarity\n\n \"\"\"\n network similarity\n \"\"\"\n def networksimilarity(self, userX, userY, year):\n \n # first calculate FG(userX) according to paper\n # User similarities on social networks\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n \n edgesFG = len(coauthors)\n \n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n \n # second, calculate MFG(userX, userY)\n weakties, cx, cy = self.weakties(userX, userY, year)\n \n edgesMFG = 2 * len(weakties)\n \n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n \n # last calculate the network similarity\n \n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG)/np.log(2 * edgesFG)\n else:\n ns = -1\n \n return (ns, edgesFG, edgesMFG, cx, cy)\n\n \"\"\"\n text processing, normalize the words to their prototype, such as \n plural form, progressive, etc\n \"\"\"\n def textnormalizing(self, text):\n #l = len(text)\n c = 0\n for i in text:\n # network - networks\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # bus - buses\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # study - studies \n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n # network - networking\n # get - getting\n # explore - exploring \n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n \n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n \n c = c + 1\n \n return text\n \n \"\"\"\n \"\"\"\n\n \n \"\"\"\n radius of the cluster\n \"\"\"\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n \n dis = dismatrix[idx,nth]\n \n self.mindis = min(dis)\n self.maxdis = max(dis)\n \n self.radius = self.maxdis\n \n \n \n # return [mindis, maxdis, radius]\n \n \n \"\"\"\n show contents in the same cluster\n \"\"\"\n def showcontents(self,labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n \n return contents\n \n \"\"\"\n check if there is digtial in the string\n \"\"\"\n def digstring(self,s):\n for i in s:\n if i.isdigit():\n return True\n return False\n \n \"\"\"\n compute the distance between two points a and b\n \"\"\"\n def distance(self,a,b):\n\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n \n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n \n a = np.array(a);\n b = np.array(b);\n return np.sqrt(sum(np.square(a - b)))\n \n \"\"\"\n \"\"\"\n def updatecoauthornetworkV2(self,net,authors,namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n \n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n # if net is empty\n if not net:\n net.append(tmpidx)\n else:\n if i>len(net)-1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n\n \"\"\"\n load the person or organization label\n \"\"\"\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel,'r','utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1] \n f.close()\n self.labels = labels\n\n \"\"\"\n \"\"\"\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork,'r','utf-8')\n source=''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n\t\t\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n \n f.close()\n return network\n \n \n \"\"\"\n \"\"\"\n def docluster(self):\n tokenizer = RegexpTokenizer(r'\\w+')\n\n\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n\n sw = set(nltk.corpus.stopwords.words('english'))\n \n \n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles,'r','utf-8')\n for line in f: \n # remove the '\\n' at the end\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n \n self.allcorp += tokenlist\n #for corp in newline:\n # self.allcorp.append(corp)\n \n # collect all the words except digtals and stopwords\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in sw) & ~(self.digstring(w))])\n self.titles.append(tokenlist)\n f.close()\n # end use codecs\n \n # filename = './CHI/CHI_authors.txt'\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = [] # undirect link, etc, dblp coauthorship network\n self.mentionnetwork = {} # direct link, etc,tweet mention network\n self.id_name = {}\n \n\n self.coauthornetV2 = []\n \n # readin the mention network\n self.mentionnetwork = self.mention_network()\n \n # read years\n self.debugmsg('start year \\n', 0)\n self.years = []\n \n f = codecs.open(self.f_years,'r','utf-8')\n for line in f:\n # remive \\n\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n #line = line.split()\n #year = line[-1]\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n \n # read conference \n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n \n f = codecs.open(self.f_booktitle,'r','utf-8')\n for line in f:\n # remove the \\n at the end\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n \n # read authors\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors,'r','utf-8')\n\n for line in f:\n # remove the last '\\n' \n line = line[:-1]\n # split the authors by ','\n newline = line.split(\",\")\n namelist = newline\n self.coathors.append(namelist) \n \n \n authoridx = []\n \n for name in newline: \n \n # dictonary version \n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n\n self.authorcontents[idx] = self.authorcontents[idx] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n\n self.authordict[name] = m\n\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n \n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n\n idx = m\n m = m + 1\n authoridx.append(idx)\n # end dict version\n \n self.coauthorsidx.append(authoridx)\n i = i + 1\n\n f.close()\n\n \n f = codecs.open(self.f_authors_id,'r','utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n #print(i)\n #print('preline: {}, line: {}'.format(preline, line))\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n \n else:\n continue\n \n #print(i)\n f.close()\n \n \n # load the per and org classification result\n self.per_org_label()\n \n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1,stop_words='english')\n \n X = self.vectorizer.fit_transform(self.authorcontents)\n \n #Xarray = X.toarray()\n Xarray = X\n \n #plt.plot(hist)\n \n transformer = TfidfTransformer()\n \n self.tfidf = transformer.fit_transform(Xarray)\n #self.tfidfarray = self.tfidf.toarray()\n self.tfidfarray = self.tfidf\n \n self.featurenames = self.vectorizer.get_feature_names()\n\n \n \n \n \n \n \"\"\" \n \"\"\"\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n #idx = self.authors.index(name)\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n name = name.decode('utf-8')\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n \n #content=[]\n \n \n \n self.myidx = authorIdx \n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n \n self.debugmsg('start distance computing \\n', 0)\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\n self.debugmsg('end distance computing \\n', 0)\n\n # here we can define the range to apply the otsu for recommendations\n # for example self.closeauthordis[0:1000] or all them\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis) \n self.debugmsg('end otsufilter\\n', 0) \n \n # splitidx contains the first index of three groups, close, medium, far\n # now generate three recommendations in each group\n recommendations = []\n \n # save the valid remdidx\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n # skip myself go to next one\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n #print remdinfo\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n #self.debugmsg(str(n) + ' ' + str(i), 0)\n \n i = i + 1\n \n # didn't find required number of valid remd untill the end\n # start backwards search\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n #self.debugmsg('search backward ' + str(i), 0)\n \n\n # randomlize the order of the recommendations\n random.shuffle(recommendations)\n \n self.result=OrderedDict([(\"name\",name),(\"recommendations\",recommendations)]) \n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result \n \n \"\"\" \n \"\"\"\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n #idx = self.authors.index(name)\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n else:\n #idx = self.authors.index(name.decode('utf-8')) \n name = name.decode('utf-8')\n name = ud.normalize('NFC',name)\n authorIdx = self.authordict.get(name)\n \n #content=[]\n \n \n \n self.myidx = authorIdx \n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n \n self.debugmsg('start distance computing \\n', 0)\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\n self.debugmsg('end distance computing \\n', 0)\n\n # here we can define the range to apply the otsu for recommendations\n # for example self.closeauthordis[0:1000] or all them\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis) \n self.debugmsg('end otsufilter\\n', 0) \n \n # splitidx contains the first index of three groups, close, medium, far\n # now generate three recommendations in each group\n recommendations = []\n \n # save the valid remdidx\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n # skip myself go to next one\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n #print remdinfo\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n #self.debugmsg(str(n) + ' ' + str(i), 0)\n \n i = i + 1\n \n # didn't find required number of valid remd untill the end\n # start backwards search\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n #self.debugmsg('search backward ' + str(i), 0)\n \n\n # randomlize the order of the recommendations\n random.shuffle(recommendations)\n \n self.result=OrderedDict([(\"name\",name),(\"recommendations\",recommendations)]) \n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result \n \n \"\"\"\n find n nearset neighbors of point p in given space using linear search\n if n == 0, sort all the points in space\n \"\"\"\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n \n\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n \n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n \n if n > 0 :\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n \n # delete myself, cuz the distance is always 0\n idx = np.where(closeauthors == self.myidx)[0][0]\n \n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n \n return (closeauthors, closeauthordis)\n \n\n\n \"\"\"\n split the distance in to 3 groups using otsu filtering\n return the first index of each group\n \"\"\"\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n \n #tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis>t1])\n \n # the first index of each group\n# trd[1] = len(tdis[tdis<t1])\n# trd[2] = len(tdis) - len(tdis[tdis>t2])\n \n # get the medium 3 in the medium group\n # get the last 3 in the far group\n trd[1] = len(tdis[tdis<t1]) + int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\n trd[2] = len(tdis) - 3 \n \n return trd\n\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove my co-authors\n \"\"\"\n def getremdinfo(self, clsidx):\n # get the author index from closeauthors\n remdidx = self.closeauthors[clsidx]\n \n recentpub = self.resentpublicationsidx(remdidx)\n \n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n \n if idx.count(self.myidx):\n # remove the coauthor\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[clsidx]),(\"coAuthors\",coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])\n else:\n return []\n\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove known people in the mention network\n \"\"\"\n def getremdinfoV2(self, clsidx):\n # get the author index from closeauthors\n remdidx = self.closeauthors[clsidx]\n \n username = self.authors[self.myidx]\n \n recentpub = self.resentpublicationsidx(remdidx)\n \n if recentpub:\n name = self.authors[remdidx]\n #[coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n mentionlist = self.mentionnetwork[username]\n \n if name in mentionlist:\n # skip the coauthor\n return []\n \n #\n remdid = self.id_name[name]\n \n if self.labels[remdid] == 'org':\n return []\n \n # get the recommendation's mention list\n coauthors = self.mycoauthorsV4bymentionlist(name)\n \n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[clsidx]),(\"coAuthors\", coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])\n else:\n return []\n\n \"\"\"\n \"\"\"\n def updatedistance(self):\n # 1st degree connection in coauthorship\n deg1con=self.coauthornet[self.myidx,self.closeauthors]\n deg1conidx = np.where(deg1con>0)[0]\n #deg1con = deg1con[deg1con>0]\n \n # 2nd degree connection in coauthorship\n deg2conidx = np.where(deg1con==0)[0]\n deg2con = np.zeros(deg2conidx.size)\n \n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i,self.closeauthors[deg2conidx]]\n \n deg1con = deg1con[deg1con>0]\n \n deg1con = deg1con/max(deg1con)\n return (deg1conidx, deg1con,deg2conidx,deg2con)\n \n \"\"\"\n return the top N recommendations:\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \n morethan 5 years) \n \"\"\"\n def filteredrecommendations(self, n):\n \n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n \n i = 0\n for name in self.recommendauthor:\n #coauthors = []\n #researchtopic = []\n #recentpub = []\n #coauthorsjson = []\n #[coauthors, idx, c] = self.mycoauthors(name)\n #[coauthors, idx, c] = self.mycoauthorsV2(name)\n #[coauthors, idx, c] = self.mycoauthorsV3(name)\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n\n # remove the coauthors \n if idx.count(self.myidx):\n i = i+1\n continue\n \n recentpub = self.resentpublications(name)\n\n # check if the recentpub is empty which is not active anymore\n if not recentpub:\n i = i+1\n continue\n # -- \n\n self.filteredauthors.append(name) \n \n # take too much time skip in test\n # researchtopic = self.keyword(name)\n researchtopic = []\n researchtopic.append(OrderedDict([(\"topic\", \"TBD\")]))\n \n \n #recommendations.append({'name':name, 'coAuthors':coauthors, 'researchTopcs':researchtopic, 'recentPublications':recentpub} )\n recommendations.append(OrderedDict([(\"name\",name), (\"relevancy\",self.closeauthordis[i]),(\"coAuthors\",coauthors),(\"researchTopics\",researchtopic), (\"recentPublications\",recentpub)])) \n #result={'name':user, 'recommendations':recommendations};\n \n # save the picked idx\n self.filteridx.append(i) \n i = i+1\n \n # only need top n recommendations\n \n if len(self.filteridx) == n:\n break\n \n return recommendations\n \n \n \"\"\"\n \"\"\"\n def thresholdrecommendations(self, remds,n):\n \n thredremd = []\n self.trd = np.zeros(3)\n \n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis>t1])\n \n # get the top 3 in each group\n self.trd[1] = len(tdis[tdis<t1])\n self.trd[2] = len(tdis) - len(tdis[tdis>t2])\n \n # get the top 3 in first group, median 3 in second group, \n # last 3 in third group\n# self.trd[1] = int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\n# self.trd[2] = len(tdis) - 3\n \n \n for i in range(3):\n for j in range(int(n/3)):\n k = int(self.trd[i]+j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n \n return thredremd\n \n\n \n \"\"\"\n \"\"\"\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n \n \n \"\"\"\n \"\"\"\n def save_json(self,filename): \n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename +'.json','w',encoding=\"utf-8\") as outfile:\n outfile.write((json.dumps((self.result), ensure_ascii=False)))\n \n \n","<docstring token>\nimport io\nimport random\nimport nltk\nfrom nltk.tokenize import RegexpTokenizer\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\nfrom collections import OrderedDict\nfrom collections import Counter\nfrom sklearn.metrics import pairwise_distances\nimport numpy as np\nimport scipy\nimport json\nimport codecs\nfrom dateutil import parser\nimport time\nimport datetime\nimport operator\nfrom skimage import filters\nimport unicodedata as ud\nfrom config import project_name\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n \"\"\"\n \"\"\"\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n \"\"\"\n \"\"\"\n\n def resentpublicationsidx(self, authoridx):\n resentpub = []\n idx = self.authortitlesidx[authoridx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n \"\"\"\n \"\"\"\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n \"\"\"\n \"\"\"\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n \"\"\"\n \"\"\"\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n \"\"\"\n \"\"\"\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n \"\"\"\n \"\"\"\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n \"\"\"\n \"\"\"\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n \"\"\"\n \"\"\"\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n find the new coauthors for a user in current year against previous year\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\n \"\"\"\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n \"\"\"\n Call the weakties after mynewcoauthors() to find the common nodes \n between a user and his/her coming new coauthors in the year before\n their coauthorship\n \"\"\"\n\n def weakties(self, userX, userY, year):\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\n if userY in coauthornetX:\n return [], [], []\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\n nodescountX = []\n nodescountY = []\n if weaktienodes:\n for i in weaktienodes:\n nodescountX.append(cx[coauthornetX.index(i)])\n nodescountY.append(cy[coauthornetY.index(i)])\n return weaktienodes, nodescountX, nodescountY\n \"\"\"\n 2nd hoop connection\n \"\"\"\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n \"\"\"\n Get all the content(paper titles) of the userIdx before \n the 'year'(include the year) \n \"\"\"\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n \"\"\"\n return the most frequent participated venue of a user\n \"\"\"\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n \"\"\"\n only consider the recent 10 papers\n \"\"\"\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n \"\"\"\n network similarity\n \"\"\"\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n \"\"\"\n text processing, normalize the words to their prototype, such as \n plural form, progressive, etc\n \"\"\"\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n \"\"\"\n \"\"\"\n \"\"\"\n radius of the cluster\n \"\"\"\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n \"\"\"\n show contents in the same cluster\n \"\"\"\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n \"\"\"\n check if there is digtial in the string\n \"\"\"\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n \"\"\"\n compute the distance between two points a and b\n \"\"\"\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n \"\"\"\n \"\"\"\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n \"\"\"\n load the person or organization label\n \"\"\"\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n \"\"\"\n \"\"\"\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n \"\"\"\n \"\"\"\n\n def docluster(self):\n tokenizer = RegexpTokenizer('\\\\w+')\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n sw = set(nltk.corpus.stopwords.words('english'))\n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n self.allcorp += tokenlist\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\n sw) & ~self.digstring(w)])\n self.titles.append(tokenlist)\n f.close()\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = []\n self.mentionnetwork = {}\n self.id_name = {}\n self.coauthornetV2 = []\n self.mentionnetwork = self.mention_network()\n self.debugmsg('start year \\n', 0)\n self.years = []\n f = codecs.open(self.f_years, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n newline = line.split(',')\n namelist = newline\n self.coathors.append(namelist)\n authoridx = []\n for name in newline:\n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n self.authorcontents[idx] = self.authorcontents[idx\n ] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx\n ] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n self.authordict[name] = m\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n idx = m\n m = m + 1\n authoridx.append(idx)\n self.coauthorsidx.append(authoridx)\n i = i + 1\n f.close()\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n else:\n continue\n f.close()\n self.per_org_label()\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\n ='english')\n X = self.vectorizer.fit_transform(self.authorcontents)\n Xarray = X\n transformer = TfidfTransformer()\n self.tfidf = transformer.fit_transform(Xarray)\n self.tfidfarray = self.tfidf\n self.featurenames = self.vectorizer.get_feature_names()\n \"\"\" \n \"\"\"\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n \"\"\" \n \"\"\"\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n \"\"\"\n find n nearset neighbors of point p in given space using linear search\n if n == 0, sort all the points in space\n \"\"\"\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n \"\"\"\n split the distance in to 3 groups using otsu filtering\n return the first index of each group\n \"\"\"\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove my co-authors\n \"\"\"\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove known people in the mention network\n \"\"\"\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n \"\"\"\n \"\"\"\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n \"\"\"\n return the top N recommendations:\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \n morethan 5 years) \n \"\"\"\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n \"\"\"\n \"\"\"\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n \"\"\"\n \"\"\"\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n \"\"\"\n \"\"\"\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n \"\"\"\n \"\"\"\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n \"\"\"\n \"\"\"\n\n def resentpublicationsidx(self, authoridx):\n resentpub = []\n idx = self.authortitlesidx[authoridx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n \"\"\"\n \"\"\"\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n \"\"\"\n \"\"\"\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n \"\"\"\n \"\"\"\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n \"\"\"\n \"\"\"\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n \"\"\"\n \"\"\"\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n \"\"\"\n \"\"\"\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n \"\"\"\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n \"\"\"\n \"\"\"\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n \"\"\"\n find the new coauthors for a user in current year against previous year\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\n \"\"\"\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n \"\"\"\n Call the weakties after mynewcoauthors() to find the common nodes \n between a user and his/her coming new coauthors in the year before\n their coauthorship\n \"\"\"\n\n def weakties(self, userX, userY, year):\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\n if userY in coauthornetX:\n return [], [], []\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\n nodescountX = []\n nodescountY = []\n if weaktienodes:\n for i in weaktienodes:\n nodescountX.append(cx[coauthornetX.index(i)])\n nodescountY.append(cy[coauthornetY.index(i)])\n return weaktienodes, nodescountX, nodescountY\n \"\"\"\n 2nd hoop connection\n \"\"\"\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n \"\"\"\n Get all the content(paper titles) of the userIdx before \n the 'year'(include the year) \n \"\"\"\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n \"\"\"\n return the most frequent participated venue of a user\n \"\"\"\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n \"\"\"\n only consider the recent 10 papers\n \"\"\"\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n \"\"\"\n network similarity\n \"\"\"\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n \"\"\"\n text processing, normalize the words to their prototype, such as \n plural form, progressive, etc\n \"\"\"\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n \"\"\"\n \"\"\"\n \"\"\"\n radius of the cluster\n \"\"\"\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n \"\"\"\n show contents in the same cluster\n \"\"\"\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n \"\"\"\n check if there is digtial in the string\n \"\"\"\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n \"\"\"\n compute the distance between two points a and b\n \"\"\"\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n \"\"\"\n \"\"\"\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n \"\"\"\n load the person or organization label\n \"\"\"\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n \"\"\"\n \"\"\"\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n \"\"\"\n \"\"\"\n\n def docluster(self):\n tokenizer = RegexpTokenizer('\\\\w+')\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n sw = set(nltk.corpus.stopwords.words('english'))\n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n self.allcorp += tokenlist\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\n sw) & ~self.digstring(w)])\n self.titles.append(tokenlist)\n f.close()\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = []\n self.mentionnetwork = {}\n self.id_name = {}\n self.coauthornetV2 = []\n self.mentionnetwork = self.mention_network()\n self.debugmsg('start year \\n', 0)\n self.years = []\n f = codecs.open(self.f_years, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n newline = line.split(',')\n namelist = newline\n self.coathors.append(namelist)\n authoridx = []\n for name in newline:\n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n self.authorcontents[idx] = self.authorcontents[idx\n ] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx\n ] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n self.authordict[name] = m\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n idx = m\n m = m + 1\n authoridx.append(idx)\n self.coauthorsidx.append(authoridx)\n i = i + 1\n f.close()\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n else:\n continue\n f.close()\n self.per_org_label()\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\n ='english')\n X = self.vectorizer.fit_transform(self.authorcontents)\n Xarray = X\n transformer = TfidfTransformer()\n self.tfidf = transformer.fit_transform(Xarray)\n self.tfidfarray = self.tfidf\n self.featurenames = self.vectorizer.get_feature_names()\n \"\"\" \n \"\"\"\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n \"\"\" \n \"\"\"\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n \"\"\"\n find n nearset neighbors of point p in given space using linear search\n if n == 0, sort all the points in space\n \"\"\"\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n \"\"\"\n split the distance in to 3 groups using otsu filtering\n return the first index of each group\n \"\"\"\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove my co-authors\n \"\"\"\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n \"\"\"\n extract the detail inforamtion of the recommendation by its indx in\n the closeauthors\n ignor those unqualified ones which has few papers or not active \n recently, and also remove known people in the mention network\n \"\"\"\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n \"\"\"\n \"\"\"\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n \"\"\"\n return the top N recommendations:\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \n morethan 5 years) \n \"\"\"\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n \"\"\"\n \"\"\"\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n \"\"\"\n \"\"\"\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n \"\"\"\n \"\"\"\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n\n def resentpublicationsidx(self, authoridx):\n resentpub = []\n idx = self.authortitlesidx[authoridx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n\n def weakties(self, userX, userY, year):\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\n if userY in coauthornetX:\n return [], [], []\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\n nodescountX = []\n nodescountY = []\n if weaktienodes:\n for i in weaktienodes:\n nodescountX.append(cx[coauthornetX.index(i)])\n nodescountY.append(cy[coauthornetY.index(i)])\n return weaktienodes, nodescountX, nodescountY\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n\n def docluster(self):\n tokenizer = RegexpTokenizer('\\\\w+')\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n sw = set(nltk.corpus.stopwords.words('english'))\n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n self.allcorp += tokenlist\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\n sw) & ~self.digstring(w)])\n self.titles.append(tokenlist)\n f.close()\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = []\n self.mentionnetwork = {}\n self.id_name = {}\n self.coauthornetV2 = []\n self.mentionnetwork = self.mention_network()\n self.debugmsg('start year \\n', 0)\n self.years = []\n f = codecs.open(self.f_years, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n newline = line.split(',')\n namelist = newline\n self.coathors.append(namelist)\n authoridx = []\n for name in newline:\n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n self.authorcontents[idx] = self.authorcontents[idx\n ] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx\n ] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n self.authordict[name] = m\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n idx = m\n m = m + 1\n authoridx.append(idx)\n self.coauthorsidx.append(authoridx)\n i = i + 1\n f.close()\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n else:\n continue\n f.close()\n self.per_org_label()\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\n ='english')\n X = self.vectorizer.fit_transform(self.authorcontents)\n Xarray = X\n transformer = TfidfTransformer()\n self.tfidf = transformer.fit_transform(Xarray)\n self.tfidfarray = self.tfidf\n self.featurenames = self.vectorizer.get_feature_names()\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n\n def resentpublicationsidx(self, authoridx):\n resentpub = []\n idx = self.authortitlesidx[authoridx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n\n def docluster(self):\n tokenizer = RegexpTokenizer('\\\\w+')\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n sw = set(nltk.corpus.stopwords.words('english'))\n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n self.allcorp += tokenlist\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\n sw) & ~self.digstring(w)])\n self.titles.append(tokenlist)\n f.close()\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = []\n self.mentionnetwork = {}\n self.id_name = {}\n self.coauthornetV2 = []\n self.mentionnetwork = self.mention_network()\n self.debugmsg('start year \\n', 0)\n self.years = []\n f = codecs.open(self.f_years, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n newline = line.split(',')\n namelist = newline\n self.coathors.append(namelist)\n authoridx = []\n for name in newline:\n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n self.authorcontents[idx] = self.authorcontents[idx\n ] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx\n ] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n self.authordict[name] = m\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n idx = m\n m = m + 1\n authoridx.append(idx)\n self.coauthorsidx.append(authoridx)\n i = i + 1\n f.close()\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n else:\n continue\n f.close()\n self.per_org_label()\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\n ='english')\n X = self.vectorizer.fit_transform(self.authorcontents)\n Xarray = X\n transformer = TfidfTransformer()\n self.tfidf = transformer.fit_transform(Xarray)\n self.tfidfarray = self.tfidf\n self.featurenames = self.vectorizer.get_feature_names()\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n\n def docluster(self):\n tokenizer = RegexpTokenizer('\\\\w+')\n self.rawtitles = []\n self.titles = []\n self.allcorp = []\n sw = set(nltk.corpus.stopwords.words('english'))\n self.debugmsg('start titles \\n', 0)\n f = codecs.open(self.f_titles, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n self.rawtitles.append(line)\n line = line.lower()\n tokenlist = tokenizer.tokenize(line)\n self.allcorp += tokenlist\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\n sw) & ~self.digstring(w)])\n self.titles.append(tokenlist)\n f.close()\n self.authordict = {}\n self.authors = []\n self.authorcontents = []\n self.authorrawcontents = []\n self.authortitlesidx = []\n self.authorbooktitleidx = []\n self.coathors = []\n self.coauthorsidx = []\n self.mentionnetwork = {}\n self.id_name = {}\n self.coauthornetV2 = []\n self.mentionnetwork = self.mention_network()\n self.debugmsg('start year \\n', 0)\n self.years = []\n f = codecs.open(self.f_years, 'r', 'utf-8')\n for line in f:\n if line[-1] == '\\n':\n line = line[:-1]\n if line == '':\n line = 0\n timestamp = time.mktime(parser.parse(line).timetuple())\n self.years.append(int(timestamp))\n f.close()\n self.debugmsg('start booktitle \\n', 0)\n self.booktitle = []\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n self.booktitle.append(line)\n f.close()\n self.debugmsg('start authors \\n', 0)\n i = 0\n m = 0\n f = codecs.open(self.f_authors, 'r', 'utf-8')\n for line in f:\n line = line[:-1]\n newline = line.split(',')\n namelist = newline\n self.coathors.append(namelist)\n authoridx = []\n for name in newline:\n idx = self.authordict.get(name)\n if idx is not None:\n self.authortitlesidx[idx].append(i)\n self.authorbooktitleidx[idx].append(i)\n self.authorcontents[idx] = self.authorcontents[idx\n ] + ' ' + self.titles[i]\n self.authorrawcontents[idx] = self.authorrawcontents[idx\n ] + ' ' + self.rawtitles[i]\n else:\n self.authors.append(name)\n self.authordict[name] = m\n self.authorcontents.append(self.titles[i])\n self.authorrawcontents.append(self.rawtitles[i])\n self.authortitlesidx.append([i])\n self.authorbooktitleidx.append([i])\n idx = m\n m = m + 1\n authoridx.append(idx)\n self.coauthorsidx.append(authoridx)\n i = i + 1\n f.close()\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\n i = 0\n preline = ''\n for line in f:\n if preline != line:\n if line[-1] == '\\n':\n newline = line[:-1]\n self.id_name[self.authors[i]] = newline\n preline = line\n i = i + 1\n else:\n continue\n f.close()\n self.per_org_label()\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\n ='english')\n X = self.vectorizer.fit_transform(self.authorcontents)\n Xarray = X\n transformer = TfidfTransformer()\n self.tfidf = transformer.fit_transform(Xarray)\n self.tfidfarray = self.tfidf\n self.featurenames = self.vectorizer.get_feature_names()\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n\n def networksimilarity(self, userX, userY, year):\n coauthors, c = self.mycoauthorsbyyear(userX, year)\n edgesFG = len(coauthors)\n n = 0\n for i in coauthors:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(coauthors[n:]))\n edgesFG = edgesFG + len(con)\n n = n + 1\n weakties, cx, cy = self.weakties(userX, userY, year)\n edgesMFG = 2 * len(weakties)\n n = 0\n for i in weakties:\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\n con = list(set(subcoauthors).intersection(weakties[n:]))\n edgesMFG = edgesMFG + len(con)\n n = n + 1\n if edgesFG * edgesMFG:\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\n else:\n ns = -1\n return ns, edgesFG, edgesMFG, cx, cy\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n\n def distance(self, a, b):\n if scipy.sparse.issparse(a):\n a = a.toarray()\n a = a[0]\n if scipy.sparse.issparse(b):\n b = b.toarray()\n b = b[0]\n a = np.array(a)\n b = np.array(b)\n return np.sqrt(sum(np.square(a - b)))\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n\n def digstring(self, s):\n for i in s:\n if i.isdigit():\n return True\n return False\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n\n def __init__(self, nyear):\n self.activityyear = 10\n self.debug = 0\n self.nremd = 3\n PROJECT_DIRECTORY = 'output/project/' + project_name\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\n self.npaper = 10\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\n self.keywordthreshold = 10\n self.debugmsg('start init', 0)\n self.docluster()\n self.initNLTKConditionalFreqDist()\n self.filterN = len(self.authors)\n self.debugmsg('end init\\n', 0)\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n\n def save_json(self, filename):\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\n 'utf-8') as outfile:\n outfile.write(json.dumps(self.result, ensure_ascii=False))\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n\n def getremdinfo(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\n if idx.count(self.myidx):\n return []\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n\n def contentsimilarity(self, userX, userY, year):\n contentX = self.getcontentbyyear(userX, year)\n if not contentX:\n return -1\n contentX = contentX[0:10]\n contentY = self.getcontentbyyear(userY, year)\n if not contentY:\n return -1\n contentY = contentY[0:10]\n contents = []\n for i in contentX:\n contents.extend(i.split(' '))\n lenx = len(contents)\n for i in contentY:\n contents.extend(i.split(' '))\n stemmer = nltk.stem.PorterStemmer()\n stems = [stemmer.stem(t) for t in contents]\n newcontentX = stems[0:lenx]\n newcontentY = stems[lenx:]\n vectorizer = CountVectorizer()\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\n newcontentY)])\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\n ]\n return cosinesimilarity\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\n return newCoauthors\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n\n def findpluralbigram(self, keywordsinfo):\n c = []\n for i in keywordsinfo:\n t = i[0].split()\n t1 = ''\n for n in t:\n if n[-1] == 's':\n n = n[:-1]\n t1 = t1 + n\n c.append(t1)\n uniqbigram = list(set(c))\n pluralidx = []\n for i in uniqbigram:\n count = c.count(i)\n if count > 1:\n cc = []\n for n in range(len(c)):\n if i == c[n]:\n cc.append(n)\n pluralidx.append(cc)\n return pluralidx\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n\n def per_org_label(self):\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\n labels = {}\n for line in f:\n items = line.split()\n labels[items[0]] = items[1]\n f.close()\n self.labels = labels\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n\n def updatedistance(self):\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\n deg1conidx = np.where(deg1con > 0)[0]\n deg2conidx = np.where(deg1con == 0)[0]\n deg2con = np.zeros(deg2conidx.size)\n for i in self.closeauthors[deg1conidx]:\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\n deg2conidx]]\n deg1con = deg1con[deg1con > 0]\n deg1con = deg1con / max(deg1con)\n return deg1conidx, deg1con, deg2conidx, deg2con\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n\n def getcontentbyyear(self, userIdx, year):\n titleIdx = self.authortitlesidx[userIdx]\n titleIdx = np.array(titleIdx)\n years = [self.years[i] for i in titleIdx]\n years = np.array(years)\n years.sort()\n years = years[::-1]\n yearIdx = np.where(years <= year)[0]\n content = [self.titles[i] for i in titleIdx[yearIdx]]\n return content\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n\n def keyword(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def textnormalizing(self, text):\n c = 0\n for i in text:\n if i[-1] == 's':\n ii = i[:-1]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-2:] == 'es':\n ii = i[:-2]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ies':\n ii = i[:-3] + 'y'\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n if i[-3:] == 'ing':\n ii = i[:-3]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-4]\n if ii in text:\n text[c] = ii\n c = c + 1\n continue\n ii = i[:-3] + 'e'\n if ii in text:\n text[c] = c + 1\n continue\n c = c + 1\n return text\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def secondhoopties(self, userX, userY, year):\n result = []\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\n for i in coauthors1:\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\n for n in coauthors2:\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\n if userY in coauthors3:\n result.append([[i, n], [count1[coauthors1.index(i)],\n count2[coauthors2.index(n)], count3[coauthors3.\n index(userY)]]])\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4bymentionlist(self, name):\n if name in self.mentionnetwork.keys():\n mentiondict = self.mentionnetwork[name]\n else:\n mentiondict = {'None': 0}\n result = []\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\n itemgetter(1), reverse=True)\n for i in sorted_mentiondict:\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\n i[1])]))\n return result\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n\n def bigramkeywords(self, text):\n content = text\n userpairs = list(nltk.bigrams(content))\n keywordsbackup = []\n keywords = []\n for p in userpairs:\n pairsdic = self.cfd[p[0]]\n n = pairsdic[p[1]]\n if n >= self.keywordthreshold:\n keywords.append((p, n))\n keywordsbackup.append((p, n))\n finalkeywords = []\n uniqkeywords = set(keywords)\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\n for p in keywords:\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\n (p[0])])\n finalkeywords.reverse()\n if not finalkeywords:\n uniqkeywords = set(keywordsbackup)\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\n keywordsbackup[1])\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\n else:\n pluralidx = self.findpluralbigram(finalkeywords)\n self.removepluralbigram(finalkeywords, pluralidx)\n return finalkeywords\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n\n def keywordbyidx(self, idx):\n contentjson = []\n content = self.authorcontents[idx].lower().split()\n finalkeywords = self.bigramkeywords(content)\n for topic in finalkeywords:\n contentjson.append(OrderedDict([('topic', topic[0])]))\n return contentjson\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n\n def filteredcloseauthordis(self):\n return self.closeauthordis[self.filteridx]\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n\n def mycoauthorsV3(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n\n def otsufilter(self, tdis):\n trd = np.zeros(3, int)\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\n tdis[tdis < t1])) / 2) - 1\n trd[2] = len(tdis) - 3\n return trd\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n\n def mention_network(self):\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\n source = ''\n network = {}\n for line in f:\n items = line.split('\"')\n if source == '':\n source = items[0]\n target = {}\n if source == items[0]:\n target[items[1]] = int(items[2])\n else:\n network[items[0]] = target\n source = items[0]\n target = {}\n f.close()\n return network\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n\n def nNNlinesearch(self, space, p, n):\n closeauthordis = []\n closeauthordis = pairwise_distances(space, p, metric='cosine')\n closeauthordis = closeauthordis.flatten()\n closeauthors = closeauthordis.argsort()\n closeauthordis.sort()\n if n > 0:\n closeauthors = closeauthors[0:n]\n closeauthordis = closeauthordis[0:n]\n idx = np.where(closeauthors == self.myidx)[0][0]\n closeauthors = np.delete(closeauthors, idx)\n closeauthordis = np.delete(closeauthordis, idx)\n return closeauthors, closeauthordis\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n\n def mycoauthorsV4byidx(self, idx):\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV4(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthors = []\n for i in self.coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n result = []\n for i in range(len(coauthorcount)):\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def removepluralbigram(self, bigram, pluralidx):\n if not pluralidx:\n print('empty')\n return\n delcount = 0\n pren = 0\n for i in pluralidx:\n for n in i[1:]:\n if n > pren:\n n = n - delcount\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\n bigram.remove(bigram[n])\n delcount = delcount + 1\n pren = n\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getremdinfoV2(self, clsidx):\n remdidx = self.closeauthors[clsidx]\n username = self.authors[self.myidx]\n recentpub = self.resentpublicationsidx(remdidx)\n if recentpub:\n name = self.authors[remdidx]\n mentionlist = self.mentionnetwork[username]\n if name in mentionlist:\n return []\n remdid = self.id_name[name]\n if self.labels[remdid] == 'org':\n return []\n coauthors = self.mycoauthorsV4bymentionlist(name)\n researchtopic = self.keywordbyidx(remdidx)\n return OrderedDict([('name', name), ('relevancy', self.\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\n 'researchTopics', researchtopic), ('recentPublications',\n recentpub)])\n else:\n return []\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n\n def debugmsg(self, msg, lvl):\n if self.debug <= lvl:\n print(msg)\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n\n def thresholdrecommendations(self, remds, n):\n thredremd = []\n self.trd = np.zeros(3)\n tdis = self.filteredcloseauthordis()\n t1 = filters.threshold_otsu(tdis)\n t2 = filters.threshold_otsu(tdis[tdis > t1])\n self.trd[1] = len(tdis[tdis < t1])\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\n for i in range(3):\n for j in range(int(n / 3)):\n k = int(self.trd[i] + j)\n name = remds[k]['name']\n researchtopic = self.keyword(name)\n remds[k]['researchTopics'] = researchtopic\n thredremd.append(remds[k])\n return thredremd\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def updatecoauthornetworkV2(self, net, authors, namelist):\n nameidx = []\n for name in namelist:\n nameidx.append(authors.index(name))\n for i in nameidx:\n tmpidx = nameidx[:]\n tmpidx.remove(i)\n if not net:\n net.append(tmpidx)\n elif i > len(net) - 1:\n net.append(tmpidx)\n else:\n net[i].extend(tmpidx)\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n\n def initNLTKConditionalFreqDist(self):\n self.debugmsg('start initNLTK CFD\\n', 0)\n pairs = []\n pairs = nltk.bigrams(self.allcorp)\n self.cfd = nltk.ConditionalFreqDist(pairs)\n self.debugmsg('end initNLTK CFD\\n', 0)\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n\n def radiusofcluster(self, labels, nth, dismatrix):\n idx = np.where(labels == nth)[0]\n dis = dismatrix[idx, nth]\n self.mindis = min(dis)\n self.maxdis = max(dis)\n self.radius = self.maxdis\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV3(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfo(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV3 \\n', 0)\n return self.result\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n\n def showcontents(self, labels, nth, allcontents):\n contents = []\n idx = np.where(labels == nth)\n idx = np.array(idx)\n idx = idx.flatten()\n for i in idx:\n contents.append(allcontents[i])\n return contents\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def getVenue(self, userIdx):\n venues = self.authorbooktitleidx[userIdx]\n c = Counter(venues)\n frqvenues = c.most_common()\n return frqvenues[0][0]\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsbyyear(self, idx, year):\n years = np.array(self.years)\n yearidx = np.where(years <= year)[0]\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\n coauthors = []\n for i in coauthorsidx:\n if idx in i:\n t = i[:]\n t.remove(idx)\n coauthors.extend(t)\n coauthors = np.array(coauthors)\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\n unicoauthors = unicoauthors[coauthorcount.argsort()]\n coauthorcount.sort()\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def mycoauthorsV2(self, name):\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n coauthorship = self.coauthornetV2[idx]\n uniqcoauthors = np.array(list(set(coauthorship)))\n coauthorcount = []\n for i in uniqcoauthors:\n coauthorcount.append(coauthorship.count(i))\n countidx = np.argsort(coauthorcount)\n countidx = countidx[::-1]\n coauthorcount = np.array(coauthorcount)\n result = []\n for i in countidx:\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\n i]]), ('cooperationCount', coauthorcount[i])]))\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\n countidx])\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def recommendationV4(self, name, n):\n self.nremd = n\n self.debugmsg('Will generate recommendations in 3 groups and ' +\n str(n) + ' for each group', 1)\n self.debugmsg('find the idx', 0)\n if isinstance(name, str):\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n else:\n name = name.decode('utf-8')\n name = ud.normalize('NFC', name)\n authorIdx = self.authordict.get(name)\n self.myidx = authorIdx\n self.debugmsg('get the feature vector', 0)\n featuretfidf = self.tfidfarray[authorIdx]\n self.debugmsg('start distance computing \\n', 0)\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\n tfidfarray, featuretfidf, 0)\n self.debugmsg('end distance computing \\n', 0)\n self.debugmsg('start otsuifilter\\n', 0)\n splitidx = self.otsufilter(self.closeauthordis)\n self.debugmsg('end otsufilter\\n', 0)\n recommendations = []\n remdidx = []\n for i in splitidx:\n n = 0\n backwardcount = 1\n while n != self.nremd:\n if self.closeauthors[i] != self.myidx:\n remdinfo = self.getremdinfoV2(i)\n if remdinfo and ~remdidx.count(i):\n recommendations.append(remdinfo)\n n = n + 1\n remdidx.append(i)\n i = i + 1\n if i == len(self.closeauthordis) or backwardcount > 1:\n if backwardcount == 1:\n backwardstart = i - self.nremd\n i = backwardstart - backwardcount\n backwardcount = backwardcount + 1\n random.shuffle(recommendations)\n self.result = OrderedDict([('name', name), ('recommendations',\n recommendations)])\n self.debugmsg('end recommendationV4 \\n', 0)\n return self.result\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def filteredrecommendations(self, n):\n recommendations = []\n self.filteridx = []\n self.filteredauthors = []\n i = 0\n for name in self.recommendauthor:\n [coauthors, idx, c] = self.mycoauthorsV4(name)\n if idx.count(self.myidx):\n i = i + 1\n continue\n recentpub = self.resentpublications(name)\n if not recentpub:\n i = i + 1\n continue\n self.filteredauthors.append(name)\n researchtopic = []\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\n recommendations.append(OrderedDict([('name', name), (\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\n coauthors), ('researchTopics', researchtopic), (\n 'recentPublications', recentpub)]))\n self.filteridx.append(i)\n i = i + 1\n if len(self.filteridx) == n:\n break\n return recommendations\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n\n def resentpublications(self, name):\n resentpub = []\n if isinstance(name, str):\n idx = self.authordict.get(name)\n else:\n idx = self.authordict.get(name.decode('utf-8'))\n idx = self.authortitlesidx[idx]\n years = [self.years[i] for i in idx]\n years = np.array(years)\n years = years.argsort()\n idx = np.array(idx)[years]\n idx = idx.tolist()\n idx.reverse()\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\n return resentpub\n for i in idx:\n authorsjson = []\n for author in self.coathors[i]:\n authorsjson.append(OrderedDict([('name', author)]))\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\n '%Y-%m-%d %H:%M:%S')\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\n 'authors', authorsjson), ('year', date), (\n 'publicationVenue', self.booktitle[i])]))\n return resentpub\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n\n\nclass recommendationsys:\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <function token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n <docstring token>\n <function token>\n","<docstring token>\n<import token>\n<class token>\n"],"string":"[\n \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nCreated on Wed Apr 12 16:38:22 2017\\n\\n@author: secoder\\n\\\"\\\"\\\"\\nimport io\\nimport random\\nimport nltk\\nfrom nltk.tokenize import RegexpTokenizer\\n\\n\\nfrom sklearn.feature_extraction.text import CountVectorizer\\nfrom sklearn.feature_extraction.text import TfidfTransformer\\n\\n\\nfrom collections import OrderedDict\\nfrom collections import Counter\\n\\nfrom sklearn.metrics import pairwise_distances\\n\\nimport numpy as np\\nimport scipy\\n\\nimport json\\nimport codecs\\n\\nfrom dateutil import parser\\nimport time\\nimport datetime\\n\\nimport operator\\n\\n#import cPickle as pickle\\n#\\n#import traceback\\n\\nfrom skimage import filters\\n\\nimport unicodedata as ud\\n\\nfrom config import project_name\\n\\n\\nclass recommendationsys:\\n \\n def __init__(self, nyear):\\n \\n # by default we will filter out those don't have publications in recent 10 years\\n self.activityyear = 10\\n\\n self.debug = 0 \\n self.nremd = 3\\n \\n #----------------------\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n\\n \\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n #---------------------- \\n \\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n \\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\" \\n def resentpublicationsidx(self,authoridx):\\n #print 'start recentpublications\\\\n'\\n resentpub = []\\n \\n idx = self.authortitlesidx[authoridx]\\n \\n # sort by years\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n \\n # if the most recent publication is before the 'nyears' \\n # remove this one from the list\\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\\n return resentpub\\n # ---- \\n \\n for i in idx:\\n authorsjson = [] \\n \\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([(\\\"name\\\",author)]))\\n \\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\\"%Y-%m-%d %H:%M:%S\\\")\\n resentpub.append(OrderedDict([(\\\"title\\\",self.rawtitles[i]),(\\\"authors\\\",authorsjson), (\\\"year\\\",date),(\\\"publicationVenue\\\",self.booktitle[i])]))\\n\\n #print 'end recentpublications\\\\n'\\n return resentpub\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def resentpublications(self,name):\\n #print 'start recentpublications\\\\n'\\n resentpub = []\\n\\n #if isinstance(name, unicode): for python 2.7\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n idx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n idx = self.authordict.get(name.decode('utf-8'))\\n \\n idx = self.authortitlesidx[idx]\\n \\n # sort by years\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n \\n # if the most recent publication is before the 'nyears' \\n # remove this one from the list\\n if (int(self.years[idx[0]]) < self.nyear) or (len(idx) < self.npaper):\\n return resentpub\\n # ---- \\n \\n for i in idx:\\n authorsjson = [] \\n \\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([(\\\"name\\\",author)]))\\n \\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\\"%Y-%m-%d %H:%M:%S\\\")\\n resentpub.append(OrderedDict([(\\\"title\\\",self.rawtitles[i]),(\\\"authors\\\",authorsjson), (\\\"year\\\",date),(\\\"publicationVenue\\\",self.booktitle[i])]))\\n\\n #print 'end recentpublications\\\\n'\\n return resentpub\\n \\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs=[]\\n\\n# for title in self.titles:\\n# pairs = pairs + list(nltk.bigrams(title.split()))\\n\\n pairs = nltk.bigrams(self.allcorp)\\n \\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n \\n def keyword(self,name):\\n #print 'start keyword\\\\n'\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n idx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n idx = self.authordict.get(name.decode('utf-8'))\\n \\n# content = self.authorcontents[idx].lower()\\n# \\n# # get the unique words from the content\\n# content = set(content.split())\\n# \\n# i = []\\n# for c in content:\\n# count = self.vectorizer.vocabulary_.get(c, 0) \\n# i.append(count)\\n# \\n# i = np.array(i)\\n# i = i.argsort()\\n# content = np.array(list(content))\\n# content = content[i]\\n# content = content[-3:]\\n# keywords = list(reversed(content)) \\n# \\n contentjson = []\\n# for topic in keywords:\\n# contentjson.append(OrderedDict([(\\\"topic\\\", topic)]))\\n \\n # bigram keywords -------------\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n# #print 'start bigram\\\\n'\\n# \\n# userpairs = list(nltk.bigrams(content))\\n# \\n# \\n# # do the same on raw titles \\n# \\n# keywordsraw=[]\\n# for p in userpairs:\\n# pairsdic=self.cfd[p[0]]\\n# n=pairsdic[p[1]]\\n# if n>=2:\\n# keywordsraw.append((p,n))\\n# \\n# uniqkeywords=set(keywordsraw)\\n# keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n# \\n# finalkeywords=[]\\n# for p in keywords:\\n# #c=wn.synsets(p[0][1])[0].pos()\\n# if (p[1]>=2):\\n# finalkeywords.append((' '.join(p[0]),p[1],keywordsraw.count(p)))\\n# \\n# finalkeywords.reverse()\\n \\n for topic in finalkeywords:\\n #print topic[0]\\n contentjson.append(OrderedDict([(\\\"topic\\\", topic[0])]))\\n \\n #print 'end bigram\\\\n'\\n #print 'end keyword\\\\n'\\n return contentjson\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def keywordbyidx(self,idx):\\n \\n contentjson = []\\n \\n # bigram keywords -------------\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n \\n for topic in finalkeywords:\\n #print topic[0]\\n contentjson.append(OrderedDict([(\\\"topic\\\", topic[0])]))\\n \\n return contentjson\\n\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\" \\n def bigramkeywords(self, text):\\n #print 'start bigramkeyword\\\\n'\\n # bigram keywords -------------\\n #content = text.lower().split()\\n content = text\\n #print 'start bigram\\\\n'\\n \\n userpairs = list(nltk.bigrams(content))\\n \\n \\n # in case there is no valid keywords due to our requirement\\n # the one with highest occurrence will be pick from the backup plan \\n keywordsbackup = []\\n # the valid keywords\\n keywords=[]\\n for p in userpairs:\\n pairsdic=self.cfd[p[0]]\\n n=pairsdic[p[1]]\\n if n>=self.keywordthreshold:\\n keywords.append((p,n))\\n keywordsbackup.append((p,n))\\n\\n finalkeywords=[]\\n \\n uniqkeywords=set(keywords)\\n keywords=sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if (p[1]>=25) or (userpairs.count(p[0])>1):\\n finalkeywords.append([' '.join(p[0]),p[1],userpairs.count(p[0])])\\n \\n finalkeywords.reverse() \\n \\n \\n \\n if not finalkeywords:\\n # found valid keywords\\n uniqkeywords=set(keywordsbackup)\\n keywordsbackup=sorted(uniqkeywords, key=lambda keywordsbackup: keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]), keywordsbackup[-1][1],userpairs.count(keywordsbackup[0])])\\n else: \\n # deal with plural\\n pluralidx = self.findpluralbigram(finalkeywords)\\n \\n self.removepluralbigram(finalkeywords,pluralidx)\\n \\n \\n #print 'end bigramkeyword\\\\n'\\n return finalkeywords\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def removepluralbigram(self, bigram, pluralidx):\\n # if pluralidx is emtpy, just return\\n if not pluralidx:\\n print('empty')\\n return \\n \\n delcount = 0\\n pren = 0 \\n\\n for i in pluralidx:\\n #delcount = 0\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n\\n c.append(t1)\\n \\n uniqbigram = list(set(c))\\n pluralidx = []\\n \\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n \\n return pluralidx\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n idx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n idx = self.authordict.get(name.decode('utf-8'))\\n \\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n \\n countidx = np.argsort(coauthorcount)\\n # reverse it to descend order\\n countidx = countidx[::-1]\\n \\n coauthorcount = np.array(coauthorcount)\\n \\n result = []\\n for i in countidx:\\n result.append(OrderedDict([(\\\"name\\\",self.authors[uniqcoauthors[i]]),(\\\"cooperationCount\\\",coauthorcount[i])]))\\n return (result,list(uniqcoauthors[countidx]),list(coauthorcount[countidx]))\\n \\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n idx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n idx = self.authordict.get(name.decode('utf-8'))\\n \\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n # remove itself\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n \\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n \\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n \\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([(\\\"name\\\",self.authors[unicoauthors[-(i+1)]]),(\\\"cooperationCount\\\",coauthorcount[-(i+1)])]))\\n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\\n\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsV4(self, name):\\n \\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n \\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n # remove itself\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n \\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n \\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n \\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([(\\\"name\\\",self.authors[unicoauthors[-(i+1)]]),(\\\"cooperationCount\\\",coauthorcount[-(i+1)])]))\\n \\n \\n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsV4byidx(self, idx):\\n \\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n # remove itself\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n \\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n \\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n \\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([(\\\"name\\\",self.authors[unicoauthors[-(i+1)]]),(\\\"cooperationCount\\\",coauthorcount[-(i+1)])]))\\n \\n \\n return (result,list(unicoauthors[::-1]),list(coauthorcount[::-1]))\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsV4bymentionlist(self, name):\\n \\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict ={'None':0}\\n \\n \\n result = []\\n # sort by mention counts\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.itemgetter(1), reverse=True)\\n \\n for i in sorted_mentiondict:\\n result.append(OrderedDict([(\\\"name\\\",i[0]),(\\\"cooperationCount\\\",i[1])]))\\n \\n return result\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mycoauthorsbyyear(self, idx, year):\\n \\n years = np.array(self.years)\\n\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [ self.coauthorsidx[i] for i in yearidx]\\n \\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n # remove itself\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n \\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n \\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n \\n return (list(unicoauthors[::-1]),list(coauthorcount[::-1]))\\n \\n \\\"\\\"\\\"\\n find the new coauthors for a user in current year against previous year\\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\\n \\\"\\\"\\\"\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n \\n return newCoauthors\\n\\n \\\"\\\"\\\"\\n Call the weakties after mynewcoauthors() to find the common nodes \\n between a user and his/her coming new coauthors in the year before\\n their coauthorship\\n \\\"\\\"\\\"\\n def weakties(self, userX, userY, year):\\n \\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\\n \\n # if userX and userY already have a strong ties, just return []\\n if userY in coauthornetX:\\n return ([], [], [])\\n \\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\\n \\n # find the common nodes \\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\\n \\n nodescountX = []\\n nodescountY = []\\n \\n if weaktienodes:\\n for i in weaktienodes:\\n nodescountX.append(cx[coauthornetX.index(i)])\\n nodescountY.append(cy[coauthornetY.index(i)])\\n \\n \\n return (weaktienodes, nodescountX, nodescountY)\\n \\n \\\"\\\"\\\"\\n 2nd hoop connection\\n \\\"\\\"\\\"\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i,n],[count1[coauthors1.index(i)],count2[coauthors2.index(n)], count3[coauthors3.index(userY)]]])\\n\\n\\n \\\"\\\"\\\"\\n Get all the content(paper titles) of the userIdx before \\n the 'year'(include the year) \\n \\\"\\\"\\\"\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n\\n titleIdx = np.array(titleIdx)\\n\\n years = [self.years[i] for i in titleIdx]\\n\\n years = np.array(years)\\n \\n # sort the years and put the latest year first\\n # then the content will also be sorted by recent paper first\\n years.sort()\\n years = years[::-1]\\n\\n yearIdx = np.where(years<=year)[0]\\n \\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n \\n return content\\n\\n \\\"\\\"\\\"\\n return the most frequent participated venue of a user\\n \\\"\\\"\\\"\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n \\n return frqvenues[0][0]\\n\\n \\\"\\\"\\\"\\n only consider the recent 10 papers\\n \\\"\\\"\\\"\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n \\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n \\n # build the corpus of all the content\\n contents = []\\n \\n \\n for i in contentX:\\n contents.extend(i.split(' '))\\n \\n lenx = len(contents)\\n \\n for i in contentY:\\n contents.extend(i.split(' '))\\n \\n # normalize the different forms of words \\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents] \\n \\n # reconstruct content for userX and userY use the normalized words\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n\\n\\n \\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(newcontentY)])\\n \\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0]\\n \\n return cosinesimilarity\\n\\n \\\"\\\"\\\"\\n network similarity\\n \\\"\\\"\\\"\\n def networksimilarity(self, userX, userY, year):\\n \\n # first calculate FG(userX) according to paper\\n # User similarities on social networks\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n \\n edgesFG = len(coauthors)\\n \\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n \\n # second, calculate MFG(userX, userY)\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n \\n edgesMFG = 2 * len(weakties)\\n \\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n \\n # last calculate the network similarity\\n \\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG)/np.log(2 * edgesFG)\\n else:\\n ns = -1\\n \\n return (ns, edgesFG, edgesMFG, cx, cy)\\n\\n \\\"\\\"\\\"\\n text processing, normalize the words to their prototype, such as \\n plural form, progressive, etc\\n \\\"\\\"\\\"\\n def textnormalizing(self, text):\\n #l = len(text)\\n c = 0\\n for i in text:\\n # network - networks\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n \\n # bus - buses\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n \\n # study - studies \\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n \\n # network - networking\\n # get - getting\\n # explore - exploring \\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n \\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n \\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n \\n c = c + 1\\n \\n return text\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n \\n \\\"\\\"\\\"\\n radius of the cluster\\n \\\"\\\"\\\"\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n \\n dis = dismatrix[idx,nth]\\n \\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n \\n self.radius = self.maxdis\\n \\n \\n \\n # return [mindis, maxdis, radius]\\n \\n \\n \\\"\\\"\\\"\\n show contents in the same cluster\\n \\\"\\\"\\\"\\n def showcontents(self,labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n \\n return contents\\n \\n \\\"\\\"\\\"\\n check if there is digtial in the string\\n \\\"\\\"\\\"\\n def digstring(self,s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n \\n \\\"\\\"\\\"\\n compute the distance between two points a and b\\n \\\"\\\"\\\"\\n def distance(self,a,b):\\n\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n \\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n \\n a = np.array(a);\\n b = np.array(b);\\n return np.sqrt(sum(np.square(a - b)))\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def updatecoauthornetworkV2(self,net,authors,namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n \\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n # if net is empty\\n if not net:\\n net.append(tmpidx)\\n else:\\n if i>len(net)-1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n\\n \\\"\\\"\\\"\\n load the person or organization label\\n \\\"\\\"\\\"\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel,'r','utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1] \\n f.close()\\n self.labels = labels\\n\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork,'r','utf-8')\\n source=''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n\\t\\t\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n \\n f.close()\\n return network\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def docluster(self):\\n tokenizer = RegexpTokenizer(r'\\\\w+')\\n\\n\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n\\n sw = set(nltk.corpus.stopwords.words('english'))\\n \\n \\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles,'r','utf-8')\\n for line in f: \\n # remove the '\\\\n' at the end\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n \\n self.allcorp += tokenlist\\n #for corp in newline:\\n # self.allcorp.append(corp)\\n \\n # collect all the words except digtals and stopwords\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in sw) & ~(self.digstring(w))])\\n self.titles.append(tokenlist)\\n f.close()\\n # end use codecs\\n \\n # filename = './CHI/CHI_authors.txt'\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = [] # undirect link, etc, dblp coauthorship network\\n self.mentionnetwork = {} # direct link, etc,tweet mention network\\n self.id_name = {}\\n \\n\\n self.coauthornetV2 = []\\n \\n # readin the mention network\\n self.mentionnetwork = self.mention_network()\\n \\n # read years\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n \\n f = codecs.open(self.f_years,'r','utf-8')\\n for line in f:\\n # remive \\\\n\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n #line = line.split()\\n #year = line[-1]\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n \\n # read conference \\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n \\n f = codecs.open(self.f_booktitle,'r','utf-8')\\n for line in f:\\n # remove the \\\\n at the end\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n \\n # read authors\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors,'r','utf-8')\\n\\n for line in f:\\n # remove the last '\\\\n' \\n line = line[:-1]\\n # split the authors by ','\\n newline = line.split(\\\",\\\")\\n namelist = newline\\n self.coathors.append(namelist) \\n \\n \\n authoridx = []\\n \\n for name in newline: \\n \\n # dictonary version \\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n\\n self.authorcontents[idx] = self.authorcontents[idx] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n\\n self.authordict[name] = m\\n\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n \\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n # end dict version\\n \\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n\\n f.close()\\n\\n \\n f = codecs.open(self.f_authors_id,'r','utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n #print(i)\\n #print('preline: {}, line: {}'.format(preline, line))\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n \\n else:\\n continue\\n \\n #print(i)\\n f.close()\\n \\n \\n # load the per and org classification result\\n self.per_org_label()\\n \\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1,stop_words='english')\\n \\n X = self.vectorizer.fit_transform(self.authorcontents)\\n \\n #Xarray = X.toarray()\\n Xarray = X\\n \\n #plt.plot(hist)\\n \\n transformer = TfidfTransformer()\\n \\n self.tfidf = transformer.fit_transform(Xarray)\\n #self.tfidfarray = self.tfidf.toarray()\\n self.tfidfarray = self.tfidf\\n \\n self.featurenames = self.vectorizer.get_feature_names()\\n\\n \\n \\n \\n \\n \\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n name = ud.normalize('NFC',name)\\n authorIdx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n name = name.decode('utf-8')\\n name = ud.normalize('NFC',name)\\n authorIdx = self.authordict.get(name)\\n \\n #content=[]\\n \\n \\n \\n self.myidx = authorIdx \\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n \\n self.debugmsg('start distance computing \\\\n', 0)\\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n\\n # here we can define the range to apply the otsu for recommendations\\n # for example self.closeauthordis[0:1000] or all them\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis) \\n self.debugmsg('end otsufilter\\\\n', 0) \\n \\n # splitidx contains the first index of three groups, close, medium, far\\n # now generate three recommendations in each group\\n recommendations = []\\n \\n # save the valid remdidx\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n # skip myself go to next one\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n #print remdinfo\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n #self.debugmsg(str(n) + ' ' + str(i), 0)\\n \\n i = i + 1\\n \\n # didn't find required number of valid remd untill the end\\n # start backwards search\\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n #self.debugmsg('search backward ' + str(i), 0)\\n \\n\\n # randomlize the order of the recommendations\\n random.shuffle(recommendations)\\n \\n self.result=OrderedDict([(\\\"name\\\",name),(\\\"recommendations\\\",recommendations)]) \\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result \\n \\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' + str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n #idx = self.authors.index(name)\\n name = ud.normalize('NFC',name)\\n authorIdx = self.authordict.get(name)\\n else:\\n #idx = self.authors.index(name.decode('utf-8')) \\n name = name.decode('utf-8')\\n name = ud.normalize('NFC',name)\\n authorIdx = self.authordict.get(name)\\n \\n #content=[]\\n \\n \\n \\n self.myidx = authorIdx \\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n \\n self.debugmsg('start distance computing \\\\n', 0)\\n (self.closeauthors, self.closeauthordis) = self.nNNlinesearch(self.tfidfarray,featuretfidf,0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n\\n # here we can define the range to apply the otsu for recommendations\\n # for example self.closeauthordis[0:1000] or all them\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis) \\n self.debugmsg('end otsufilter\\\\n', 0) \\n \\n # splitidx contains the first index of three groups, close, medium, far\\n # now generate three recommendations in each group\\n recommendations = []\\n \\n # save the valid remdidx\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n # skip myself go to next one\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n #print remdinfo\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n #self.debugmsg(str(n) + ' ' + str(i), 0)\\n \\n i = i + 1\\n \\n # didn't find required number of valid remd untill the end\\n # start backwards search\\n if (i == len(self.closeauthordis)) or (backwardcount > 1):\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n #self.debugmsg('search backward ' + str(i), 0)\\n \\n\\n # randomlize the order of the recommendations\\n random.shuffle(recommendations)\\n \\n self.result=OrderedDict([(\\\"name\\\",name),(\\\"recommendations\\\",recommendations)]) \\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result \\n \\n \\\"\\\"\\\"\\n find n nearset neighbors of point p in given space using linear search\\n if n == 0, sort all the points in space\\n \\\"\\\"\\\"\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n \\n\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n \\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n \\n if n > 0 :\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n \\n # delete myself, cuz the distance is always 0\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n \\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n \\n return (closeauthors, closeauthordis)\\n \\n\\n\\n \\\"\\\"\\\"\\n split the distance in to 3 groups using otsu filtering\\n return the first index of each group\\n \\\"\\\"\\\"\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n \\n #tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis>t1])\\n \\n # the first index of each group\\n# trd[1] = len(tdis[tdis<t1])\\n# trd[2] = len(tdis) - len(tdis[tdis>t2])\\n \\n # get the medium 3 in the medium group\\n # get the last 3 in the far group\\n trd[1] = len(tdis[tdis<t1]) + int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\\n trd[2] = len(tdis) - 3 \\n \\n return trd\\n\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove my co-authors\\n \\\"\\\"\\\"\\n def getremdinfo(self, clsidx):\\n # get the author index from closeauthors\\n remdidx = self.closeauthors[clsidx]\\n \\n recentpub = self.resentpublicationsidx(remdidx)\\n \\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n \\n if idx.count(self.myidx):\\n # remove the coauthor\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([(\\\"name\\\",name), (\\\"relevancy\\\",self.closeauthordis[clsidx]),(\\\"coAuthors\\\",coauthors),(\\\"researchTopics\\\",researchtopic), (\\\"recentPublications\\\",recentpub)])\\n else:\\n return []\\n\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove known people in the mention network\\n \\\"\\\"\\\"\\n def getremdinfoV2(self, clsidx):\\n # get the author index from closeauthors\\n remdidx = self.closeauthors[clsidx]\\n \\n username = self.authors[self.myidx]\\n \\n recentpub = self.resentpublicationsidx(remdidx)\\n \\n if recentpub:\\n name = self.authors[remdidx]\\n #[coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n mentionlist = self.mentionnetwork[username]\\n \\n if name in mentionlist:\\n # skip the coauthor\\n return []\\n \\n #\\n remdid = self.id_name[name]\\n \\n if self.labels[remdid] == 'org':\\n return []\\n \\n # get the recommendation's mention list\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n \\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([(\\\"name\\\",name), (\\\"relevancy\\\",self.closeauthordis[clsidx]),(\\\"coAuthors\\\", coauthors),(\\\"researchTopics\\\",researchtopic), (\\\"recentPublications\\\",recentpub)])\\n else:\\n return []\\n\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def updatedistance(self):\\n # 1st degree connection in coauthorship\\n deg1con=self.coauthornet[self.myidx,self.closeauthors]\\n deg1conidx = np.where(deg1con>0)[0]\\n #deg1con = deg1con[deg1con>0]\\n \\n # 2nd degree connection in coauthorship\\n deg2conidx = np.where(deg1con==0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n \\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i,self.closeauthors[deg2conidx]]\\n \\n deg1con = deg1con[deg1con>0]\\n \\n deg1con = deg1con/max(deg1con)\\n return (deg1conidx, deg1con,deg2conidx,deg2con)\\n \\n \\\"\\\"\\\"\\n return the top N recommendations:\\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \\n morethan 5 years) \\n \\\"\\\"\\\"\\n def filteredrecommendations(self, n):\\n \\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n \\n i = 0\\n for name in self.recommendauthor:\\n #coauthors = []\\n #researchtopic = []\\n #recentpub = []\\n #coauthorsjson = []\\n #[coauthors, idx, c] = self.mycoauthors(name)\\n #[coauthors, idx, c] = self.mycoauthorsV2(name)\\n #[coauthors, idx, c] = self.mycoauthorsV3(name)\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n\\n # remove the coauthors \\n if idx.count(self.myidx):\\n i = i+1\\n continue\\n \\n recentpub = self.resentpublications(name)\\n\\n # check if the recentpub is empty which is not active anymore\\n if not recentpub:\\n i = i+1\\n continue\\n # -- \\n\\n self.filteredauthors.append(name) \\n \\n # take too much time skip in test\\n # researchtopic = self.keyword(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([(\\\"topic\\\", \\\"TBD\\\")]))\\n \\n \\n #recommendations.append({'name':name, 'coAuthors':coauthors, 'researchTopcs':researchtopic, 'recentPublications':recentpub} )\\n recommendations.append(OrderedDict([(\\\"name\\\",name), (\\\"relevancy\\\",self.closeauthordis[i]),(\\\"coAuthors\\\",coauthors),(\\\"researchTopics\\\",researchtopic), (\\\"recentPublications\\\",recentpub)])) \\n #result={'name':user, 'recommendations':recommendations};\\n \\n # save the picked idx\\n self.filteridx.append(i) \\n i = i+1\\n \\n # only need top n recommendations\\n \\n if len(self.filteridx) == n:\\n break\\n \\n return recommendations\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def thresholdrecommendations(self, remds,n):\\n \\n thredremd = []\\n self.trd = np.zeros(3)\\n \\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis>t1])\\n \\n # get the top 3 in each group\\n self.trd[1] = len(tdis[tdis<t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis>t2])\\n \\n # get the top 3 in first group, median 3 in second group, \\n # last 3 in third group\\n# self.trd[1] = int((len(tdis[tdis<t2]) - len(tdis[tdis<t1]))/2)-1\\n# self.trd[2] = len(tdis) - 3\\n \\n \\n for i in range(3):\\n for j in range(int(n/3)):\\n k = int(self.trd[i]+j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n \\n return thredremd\\n \\n\\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n \\n \\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n def save_json(self,filename): \\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename +'.json','w',encoding=\\\"utf-8\\\") as outfile:\\n outfile.write((json.dumps((self.result), ensure_ascii=False)))\\n \\n \\n\",\n \"<docstring token>\\nimport io\\nimport random\\nimport nltk\\nfrom nltk.tokenize import RegexpTokenizer\\nfrom sklearn.feature_extraction.text import CountVectorizer\\nfrom sklearn.feature_extraction.text import TfidfTransformer\\nfrom collections import OrderedDict\\nfrom collections import Counter\\nfrom sklearn.metrics import pairwise_distances\\nimport numpy as np\\nimport scipy\\nimport json\\nimport codecs\\nfrom dateutil import parser\\nimport time\\nimport datetime\\nimport operator\\nfrom skimage import filters\\nimport unicodedata as ud\\nfrom config import project_name\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def resentpublicationsidx(self, authoridx):\\n resentpub = []\\n idx = self.authortitlesidx[authoridx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n find the new coauthors for a user in current year against previous year\\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\\n \\\"\\\"\\\"\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n \\\"\\\"\\\"\\n Call the weakties after mynewcoauthors() to find the common nodes \\n between a user and his/her coming new coauthors in the year before\\n their coauthorship\\n \\\"\\\"\\\"\\n\\n def weakties(self, userX, userY, year):\\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\\n if userY in coauthornetX:\\n return [], [], []\\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\\n nodescountX = []\\n nodescountY = []\\n if weaktienodes:\\n for i in weaktienodes:\\n nodescountX.append(cx[coauthornetX.index(i)])\\n nodescountY.append(cy[coauthornetY.index(i)])\\n return weaktienodes, nodescountX, nodescountY\\n \\\"\\\"\\\"\\n 2nd hoop connection\\n \\\"\\\"\\\"\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n \\\"\\\"\\\"\\n Get all the content(paper titles) of the userIdx before \\n the 'year'(include the year) \\n \\\"\\\"\\\"\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n \\\"\\\"\\\"\\n return the most frequent participated venue of a user\\n \\\"\\\"\\\"\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n \\\"\\\"\\\"\\n only consider the recent 10 papers\\n \\\"\\\"\\\"\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n \\\"\\\"\\\"\\n network similarity\\n \\\"\\\"\\\"\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n \\\"\\\"\\\"\\n text processing, normalize the words to their prototype, such as \\n plural form, progressive, etc\\n \\\"\\\"\\\"\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n radius of the cluster\\n \\\"\\\"\\\"\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n \\\"\\\"\\\"\\n show contents in the same cluster\\n \\\"\\\"\\\"\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n \\\"\\\"\\\"\\n check if there is digtial in the string\\n \\\"\\\"\\\"\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n \\\"\\\"\\\"\\n compute the distance between two points a and b\\n \\\"\\\"\\\"\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n \\\"\\\"\\\"\\n load the person or organization label\\n \\\"\\\"\\\"\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def docluster(self):\\n tokenizer = RegexpTokenizer('\\\\\\\\w+')\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n sw = set(nltk.corpus.stopwords.words('english'))\\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n self.allcorp += tokenlist\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\\n sw) & ~self.digstring(w)])\\n self.titles.append(tokenlist)\\n f.close()\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = []\\n self.mentionnetwork = {}\\n self.id_name = {}\\n self.coauthornetV2 = []\\n self.mentionnetwork = self.mention_network()\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n f = codecs.open(self.f_years, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n newline = line.split(',')\\n namelist = newline\\n self.coathors.append(namelist)\\n authoridx = []\\n for name in newline:\\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n self.authorcontents[idx] = self.authorcontents[idx\\n ] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx\\n ] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n self.authordict[name] = m\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n f.close()\\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n else:\\n continue\\n f.close()\\n self.per_org_label()\\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\\n ='english')\\n X = self.vectorizer.fit_transform(self.authorcontents)\\n Xarray = X\\n transformer = TfidfTransformer()\\n self.tfidf = transformer.fit_transform(Xarray)\\n self.tfidfarray = self.tfidf\\n self.featurenames = self.vectorizer.get_feature_names()\\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n \\\"\\\"\\\"\\n find n nearset neighbors of point p in given space using linear search\\n if n == 0, sort all the points in space\\n \\\"\\\"\\\"\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n \\\"\\\"\\\"\\n split the distance in to 3 groups using otsu filtering\\n return the first index of each group\\n \\\"\\\"\\\"\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove my co-authors\\n \\\"\\\"\\\"\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove known people in the mention network\\n \\\"\\\"\\\"\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n \\\"\\\"\\\"\\n return the top N recommendations:\\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \\n morethan 5 years) \\n \\\"\\\"\\\"\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def resentpublicationsidx(self, authoridx):\\n resentpub = []\\n idx = self.authortitlesidx[authoridx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n \\\"\\\"\\\"\\n find the new coauthors for a user in current year against previous year\\n example: mynewcoauthors(23, 2014, 2015) will returen the new coauthors\\n in 2015 regarding the year 2014 for user 23. 23 is the index of a user\\n \\\"\\\"\\\"\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n \\\"\\\"\\\"\\n Call the weakties after mynewcoauthors() to find the common nodes \\n between a user and his/her coming new coauthors in the year before\\n their coauthorship\\n \\\"\\\"\\\"\\n\\n def weakties(self, userX, userY, year):\\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\\n if userY in coauthornetX:\\n return [], [], []\\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\\n nodescountX = []\\n nodescountY = []\\n if weaktienodes:\\n for i in weaktienodes:\\n nodescountX.append(cx[coauthornetX.index(i)])\\n nodescountY.append(cy[coauthornetY.index(i)])\\n return weaktienodes, nodescountX, nodescountY\\n \\\"\\\"\\\"\\n 2nd hoop connection\\n \\\"\\\"\\\"\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n \\\"\\\"\\\"\\n Get all the content(paper titles) of the userIdx before \\n the 'year'(include the year) \\n \\\"\\\"\\\"\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n \\\"\\\"\\\"\\n return the most frequent participated venue of a user\\n \\\"\\\"\\\"\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n \\\"\\\"\\\"\\n only consider the recent 10 papers\\n \\\"\\\"\\\"\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n \\\"\\\"\\\"\\n network similarity\\n \\\"\\\"\\\"\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n \\\"\\\"\\\"\\n text processing, normalize the words to their prototype, such as \\n plural form, progressive, etc\\n \\\"\\\"\\\"\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n radius of the cluster\\n \\\"\\\"\\\"\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n \\\"\\\"\\\"\\n show contents in the same cluster\\n \\\"\\\"\\\"\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n \\\"\\\"\\\"\\n check if there is digtial in the string\\n \\\"\\\"\\\"\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n \\\"\\\"\\\"\\n compute the distance between two points a and b\\n \\\"\\\"\\\"\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n \\\"\\\"\\\"\\n load the person or organization label\\n \\\"\\\"\\\"\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def docluster(self):\\n tokenizer = RegexpTokenizer('\\\\\\\\w+')\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n sw = set(nltk.corpus.stopwords.words('english'))\\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n self.allcorp += tokenlist\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\\n sw) & ~self.digstring(w)])\\n self.titles.append(tokenlist)\\n f.close()\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = []\\n self.mentionnetwork = {}\\n self.id_name = {}\\n self.coauthornetV2 = []\\n self.mentionnetwork = self.mention_network()\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n f = codecs.open(self.f_years, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n newline = line.split(',')\\n namelist = newline\\n self.coathors.append(namelist)\\n authoridx = []\\n for name in newline:\\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n self.authorcontents[idx] = self.authorcontents[idx\\n ] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx\\n ] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n self.authordict[name] = m\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n f.close()\\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n else:\\n continue\\n f.close()\\n self.per_org_label()\\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\\n ='english')\\n X = self.vectorizer.fit_transform(self.authorcontents)\\n Xarray = X\\n transformer = TfidfTransformer()\\n self.tfidf = transformer.fit_transform(Xarray)\\n self.tfidfarray = self.tfidf\\n self.featurenames = self.vectorizer.get_feature_names()\\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n \\\"\\\"\\\" \\n \\\"\\\"\\\"\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n \\\"\\\"\\\"\\n find n nearset neighbors of point p in given space using linear search\\n if n == 0, sort all the points in space\\n \\\"\\\"\\\"\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n \\\"\\\"\\\"\\n split the distance in to 3 groups using otsu filtering\\n return the first index of each group\\n \\\"\\\"\\\"\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove my co-authors\\n \\\"\\\"\\\"\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n \\\"\\\"\\\"\\n extract the detail inforamtion of the recommendation by its indx in\\n the closeauthors\\n ignor those unqualified ones which has few papers or not active \\n recently, and also remove known people in the mention network\\n \\\"\\\"\\\"\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n \\\"\\\"\\\"\\n return the top N recommendations:\\n recommendations, coauthors, researchtopics, recentpub(at least 3 and no \\n morethan 5 years) \\n \\\"\\\"\\\"\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n\\n def resentpublicationsidx(self, authoridx):\\n resentpub = []\\n idx = self.authortitlesidx[authoridx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n\\n def weakties(self, userX, userY, year):\\n coauthornetX, cx = self.mycoauthorsbyyear(userX, year)\\n if userY in coauthornetX:\\n return [], [], []\\n coauthornetY, cy = self.mycoauthorsbyyear(userY, year)\\n weaktienodes = list(set(coauthornetX).intersection(coauthornetY))\\n nodescountX = []\\n nodescountY = []\\n if weaktienodes:\\n for i in weaktienodes:\\n nodescountX.append(cx[coauthornetX.index(i)])\\n nodescountY.append(cy[coauthornetY.index(i)])\\n return weaktienodes, nodescountX, nodescountY\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n\\n def docluster(self):\\n tokenizer = RegexpTokenizer('\\\\\\\\w+')\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n sw = set(nltk.corpus.stopwords.words('english'))\\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n self.allcorp += tokenlist\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\\n sw) & ~self.digstring(w)])\\n self.titles.append(tokenlist)\\n f.close()\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = []\\n self.mentionnetwork = {}\\n self.id_name = {}\\n self.coauthornetV2 = []\\n self.mentionnetwork = self.mention_network()\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n f = codecs.open(self.f_years, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n newline = line.split(',')\\n namelist = newline\\n self.coathors.append(namelist)\\n authoridx = []\\n for name in newline:\\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n self.authorcontents[idx] = self.authorcontents[idx\\n ] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx\\n ] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n self.authordict[name] = m\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n f.close()\\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n else:\\n continue\\n f.close()\\n self.per_org_label()\\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\\n ='english')\\n X = self.vectorizer.fit_transform(self.authorcontents)\\n Xarray = X\\n transformer = TfidfTransformer()\\n self.tfidf = transformer.fit_transform(Xarray)\\n self.tfidfarray = self.tfidf\\n self.featurenames = self.vectorizer.get_feature_names()\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n\\n def resentpublicationsidx(self, authoridx):\\n resentpub = []\\n idx = self.authortitlesidx[authoridx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n\\n def docluster(self):\\n tokenizer = RegexpTokenizer('\\\\\\\\w+')\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n sw = set(nltk.corpus.stopwords.words('english'))\\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n self.allcorp += tokenlist\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\\n sw) & ~self.digstring(w)])\\n self.titles.append(tokenlist)\\n f.close()\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = []\\n self.mentionnetwork = {}\\n self.id_name = {}\\n self.coauthornetV2 = []\\n self.mentionnetwork = self.mention_network()\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n f = codecs.open(self.f_years, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n newline = line.split(',')\\n namelist = newline\\n self.coathors.append(namelist)\\n authoridx = []\\n for name in newline:\\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n self.authorcontents[idx] = self.authorcontents[idx\\n ] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx\\n ] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n self.authordict[name] = m\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n f.close()\\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n else:\\n continue\\n f.close()\\n self.per_org_label()\\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\\n ='english')\\n X = self.vectorizer.fit_transform(self.authorcontents)\\n Xarray = X\\n transformer = TfidfTransformer()\\n self.tfidf = transformer.fit_transform(Xarray)\\n self.tfidfarray = self.tfidf\\n self.featurenames = self.vectorizer.get_feature_names()\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n\\n def docluster(self):\\n tokenizer = RegexpTokenizer('\\\\\\\\w+')\\n self.rawtitles = []\\n self.titles = []\\n self.allcorp = []\\n sw = set(nltk.corpus.stopwords.words('english'))\\n self.debugmsg('start titles \\\\n', 0)\\n f = codecs.open(self.f_titles, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n self.rawtitles.append(line)\\n line = line.lower()\\n tokenlist = tokenizer.tokenize(line)\\n self.allcorp += tokenlist\\n tokenlist = ' '.join([w for w in tokenlist if (w.lower() not in\\n sw) & ~self.digstring(w)])\\n self.titles.append(tokenlist)\\n f.close()\\n self.authordict = {}\\n self.authors = []\\n self.authorcontents = []\\n self.authorrawcontents = []\\n self.authortitlesidx = []\\n self.authorbooktitleidx = []\\n self.coathors = []\\n self.coauthorsidx = []\\n self.mentionnetwork = {}\\n self.id_name = {}\\n self.coauthornetV2 = []\\n self.mentionnetwork = self.mention_network()\\n self.debugmsg('start year \\\\n', 0)\\n self.years = []\\n f = codecs.open(self.f_years, 'r', 'utf-8')\\n for line in f:\\n if line[-1] == '\\\\n':\\n line = line[:-1]\\n if line == '':\\n line = 0\\n timestamp = time.mktime(parser.parse(line).timetuple())\\n self.years.append(int(timestamp))\\n f.close()\\n self.debugmsg('start booktitle \\\\n', 0)\\n self.booktitle = []\\n f = codecs.open(self.f_booktitle, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n self.booktitle.append(line)\\n f.close()\\n self.debugmsg('start authors \\\\n', 0)\\n i = 0\\n m = 0\\n f = codecs.open(self.f_authors, 'r', 'utf-8')\\n for line in f:\\n line = line[:-1]\\n newline = line.split(',')\\n namelist = newline\\n self.coathors.append(namelist)\\n authoridx = []\\n for name in newline:\\n idx = self.authordict.get(name)\\n if idx is not None:\\n self.authortitlesidx[idx].append(i)\\n self.authorbooktitleidx[idx].append(i)\\n self.authorcontents[idx] = self.authorcontents[idx\\n ] + ' ' + self.titles[i]\\n self.authorrawcontents[idx] = self.authorrawcontents[idx\\n ] + ' ' + self.rawtitles[i]\\n else:\\n self.authors.append(name)\\n self.authordict[name] = m\\n self.authorcontents.append(self.titles[i])\\n self.authorrawcontents.append(self.rawtitles[i])\\n self.authortitlesidx.append([i])\\n self.authorbooktitleidx.append([i])\\n idx = m\\n m = m + 1\\n authoridx.append(idx)\\n self.coauthorsidx.append(authoridx)\\n i = i + 1\\n f.close()\\n f = codecs.open(self.f_authors_id, 'r', 'utf-8')\\n i = 0\\n preline = ''\\n for line in f:\\n if preline != line:\\n if line[-1] == '\\\\n':\\n newline = line[:-1]\\n self.id_name[self.authors[i]] = newline\\n preline = line\\n i = i + 1\\n else:\\n continue\\n f.close()\\n self.per_org_label()\\n self.vectorizer = CountVectorizer(max_df=0.95, min_df=1, stop_words\\n ='english')\\n X = self.vectorizer.fit_transform(self.authorcontents)\\n Xarray = X\\n transformer = TfidfTransformer()\\n self.tfidf = transformer.fit_transform(Xarray)\\n self.tfidfarray = self.tfidf\\n self.featurenames = self.vectorizer.get_feature_names()\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n\\n def networksimilarity(self, userX, userY, year):\\n coauthors, c = self.mycoauthorsbyyear(userX, year)\\n edgesFG = len(coauthors)\\n n = 0\\n for i in coauthors:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(coauthors[n:]))\\n edgesFG = edgesFG + len(con)\\n n = n + 1\\n weakties, cx, cy = self.weakties(userX, userY, year)\\n edgesMFG = 2 * len(weakties)\\n n = 0\\n for i in weakties:\\n subcoauthors, c = self.mycoauthorsbyyear(i, year)\\n con = list(set(subcoauthors).intersection(weakties[n:]))\\n edgesMFG = edgesMFG + len(con)\\n n = n + 1\\n if edgesFG * edgesMFG:\\n ns = np.log(edgesMFG) / np.log(2 * edgesFG)\\n else:\\n ns = -1\\n return ns, edgesFG, edgesMFG, cx, cy\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n\\n def distance(self, a, b):\\n if scipy.sparse.issparse(a):\\n a = a.toarray()\\n a = a[0]\\n if scipy.sparse.issparse(b):\\n b = b.toarray()\\n b = b[0]\\n a = np.array(a)\\n b = np.array(b)\\n return np.sqrt(sum(np.square(a - b)))\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n\\n def digstring(self, s):\\n for i in s:\\n if i.isdigit():\\n return True\\n return False\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n\\n def __init__(self, nyear):\\n self.activityyear = 10\\n self.debug = 0\\n self.nremd = 3\\n PROJECT_DIRECTORY = 'output/project/' + project_name\\n self.f_titles = PROJECT_DIRECTORY + '/cleantitles_target.txt'\\n self.f_authors = PROJECT_DIRECTORY + '/authors_target.txt'\\n self.f_years = PROJECT_DIRECTORY + '/years_target.txt'\\n self.f_booktitle = PROJECT_DIRECTORY + '/venues_target.txt'\\n self.f_mentionnetwork = PROJECT_DIRECTORY + '/mention_network.txt'\\n self.f_perorglabel = PROJECT_DIRECTORY + '/per_org.txt'\\n self.f_authors_id = PROJECT_DIRECTORY + '/authors_id_target.txt'\\n self.npaper = 10\\n self.nyear = time.mktime(parser.parse(str(nyear)).timetuple())\\n self.keywordthreshold = 10\\n self.debugmsg('start init', 0)\\n self.docluster()\\n self.initNLTKConditionalFreqDist()\\n self.filterN = len(self.authors)\\n self.debugmsg('end init\\\\n', 0)\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n\\n def save_json(self, filename):\\n PROJECT_DIRECTORY = 'output/project/' + project_name + '/'\\n with io.open(PROJECT_DIRECTORY + filename + '.json', 'w', encoding=\\n 'utf-8') as outfile:\\n outfile.write(json.dumps(self.result, ensure_ascii=False))\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n\\n def getremdinfo(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n [coauthors, idx, c] = self.mycoauthorsV4byidx(remdidx)\\n if idx.count(self.myidx):\\n return []\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n\\n def contentsimilarity(self, userX, userY, year):\\n contentX = self.getcontentbyyear(userX, year)\\n if not contentX:\\n return -1\\n contentX = contentX[0:10]\\n contentY = self.getcontentbyyear(userY, year)\\n if not contentY:\\n return -1\\n contentY = contentY[0:10]\\n contents = []\\n for i in contentX:\\n contents.extend(i.split(' '))\\n lenx = len(contents)\\n for i in contentY:\\n contents.extend(i.split(' '))\\n stemmer = nltk.stem.PorterStemmer()\\n stems = [stemmer.stem(t) for t in contents]\\n newcontentX = stems[0:lenx]\\n newcontentY = stems[lenx:]\\n vectorizer = CountVectorizer()\\n v = vectorizer.fit_transform([' '.join(newcontentX), ' '.join(\\n newcontentY)])\\n cosinesimilarity = pairwise_distances(v[0], v[1], metric='cosine')[0][0\\n ]\\n return cosinesimilarity\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mynewcoauthors(self, userIdx, yearPre, yearCur):\\n coauthornetPre, cp = self.mycoauthorsbyyear(userIdx, yearPre)\\n coauthornetCur, cc = self.mycoauthorsbyyear(userIdx, yearCur)\\n newCoauthors = np.setdiff1d(coauthornetCur, coauthornetPre)\\n return newCoauthors\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n\\n def findpluralbigram(self, keywordsinfo):\\n c = []\\n for i in keywordsinfo:\\n t = i[0].split()\\n t1 = ''\\n for n in t:\\n if n[-1] == 's':\\n n = n[:-1]\\n t1 = t1 + n\\n c.append(t1)\\n uniqbigram = list(set(c))\\n pluralidx = []\\n for i in uniqbigram:\\n count = c.count(i)\\n if count > 1:\\n cc = []\\n for n in range(len(c)):\\n if i == c[n]:\\n cc.append(n)\\n pluralidx.append(cc)\\n return pluralidx\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n\\n def per_org_label(self):\\n f = codecs.open(self.f_perorglabel, 'r', 'utf-8')\\n labels = {}\\n for line in f:\\n items = line.split()\\n labels[items[0]] = items[1]\\n f.close()\\n self.labels = labels\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n\\n def updatedistance(self):\\n deg1con = self.coauthornet[self.myidx, self.closeauthors]\\n deg1conidx = np.where(deg1con > 0)[0]\\n deg2conidx = np.where(deg1con == 0)[0]\\n deg2con = np.zeros(deg2conidx.size)\\n for i in self.closeauthors[deg1conidx]:\\n deg2con = deg2con + self.coauthornet[i, self.closeauthors[\\n deg2conidx]]\\n deg1con = deg1con[deg1con > 0]\\n deg1con = deg1con / max(deg1con)\\n return deg1conidx, deg1con, deg2conidx, deg2con\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n\\n def getcontentbyyear(self, userIdx, year):\\n titleIdx = self.authortitlesidx[userIdx]\\n titleIdx = np.array(titleIdx)\\n years = [self.years[i] for i in titleIdx]\\n years = np.array(years)\\n years.sort()\\n years = years[::-1]\\n yearIdx = np.where(years <= year)[0]\\n content = [self.titles[i] for i in titleIdx[yearIdx]]\\n return content\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n\\n def keyword(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def textnormalizing(self, text):\\n c = 0\\n for i in text:\\n if i[-1] == 's':\\n ii = i[:-1]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-2:] == 'es':\\n ii = i[:-2]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ies':\\n ii = i[:-3] + 'y'\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n if i[-3:] == 'ing':\\n ii = i[:-3]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-4]\\n if ii in text:\\n text[c] = ii\\n c = c + 1\\n continue\\n ii = i[:-3] + 'e'\\n if ii in text:\\n text[c] = c + 1\\n continue\\n c = c + 1\\n return text\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def secondhoopties(self, userX, userY, year):\\n result = []\\n coauthors1, count1 = self.mycoauthorsbyyear(userX, 2016)\\n for i in coauthors1:\\n coauthors2, count2 = self.mycoauthorsbyyear(i, 2016)\\n for n in coauthors2:\\n coauthors3, count3 = self.mycoauthorsbyyear(n, 2016)\\n if userY in coauthors3:\\n result.append([[i, n], [count1[coauthors1.index(i)],\\n count2[coauthors2.index(n)], count3[coauthors3.\\n index(userY)]]])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4bymentionlist(self, name):\\n if name in self.mentionnetwork.keys():\\n mentiondict = self.mentionnetwork[name]\\n else:\\n mentiondict = {'None': 0}\\n result = []\\n sorted_mentiondict = sorted(mentiondict.items(), key=operator.\\n itemgetter(1), reverse=True)\\n for i in sorted_mentiondict:\\n result.append(OrderedDict([('name', i[0]), ('cooperationCount',\\n i[1])]))\\n return result\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n\\n def bigramkeywords(self, text):\\n content = text\\n userpairs = list(nltk.bigrams(content))\\n keywordsbackup = []\\n keywords = []\\n for p in userpairs:\\n pairsdic = self.cfd[p[0]]\\n n = pairsdic[p[1]]\\n if n >= self.keywordthreshold:\\n keywords.append((p, n))\\n keywordsbackup.append((p, n))\\n finalkeywords = []\\n uniqkeywords = set(keywords)\\n keywords = sorted(uniqkeywords, key=lambda keywords: keywords[1])\\n for p in keywords:\\n if p[1] >= 25 or userpairs.count(p[0]) > 1:\\n finalkeywords.append([' '.join(p[0]), p[1], userpairs.count\\n (p[0])])\\n finalkeywords.reverse()\\n if not finalkeywords:\\n uniqkeywords = set(keywordsbackup)\\n keywordsbackup = sorted(uniqkeywords, key=lambda keywordsbackup:\\n keywordsbackup[1])\\n finalkeywords.append([' '.join(keywordsbackup[-1][0]),\\n keywordsbackup[-1][1], userpairs.count(keywordsbackup[0])])\\n else:\\n pluralidx = self.findpluralbigram(finalkeywords)\\n self.removepluralbigram(finalkeywords, pluralidx)\\n return finalkeywords\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n\\n def keywordbyidx(self, idx):\\n contentjson = []\\n content = self.authorcontents[idx].lower().split()\\n finalkeywords = self.bigramkeywords(content)\\n for topic in finalkeywords:\\n contentjson.append(OrderedDict([('topic', topic[0])]))\\n return contentjson\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n\\n def filteredcloseauthordis(self):\\n return self.closeauthordis[self.filteridx]\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n\\n def mycoauthorsV3(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n\\n def otsufilter(self, tdis):\\n trd = np.zeros(3, int)\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n trd[1] = len(tdis[tdis < t1]) + int((len(tdis[tdis < t2]) - len(\\n tdis[tdis < t1])) / 2) - 1\\n trd[2] = len(tdis) - 3\\n return trd\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mention_network(self):\\n f = codecs.open(self.f_mentionnetwork, 'r', 'utf-8')\\n source = ''\\n network = {}\\n for line in f:\\n items = line.split('\\\"')\\n if source == '':\\n source = items[0]\\n target = {}\\n if source == items[0]:\\n target[items[1]] = int(items[2])\\n else:\\n network[items[0]] = target\\n source = items[0]\\n target = {}\\n f.close()\\n return network\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def nNNlinesearch(self, space, p, n):\\n closeauthordis = []\\n closeauthordis = pairwise_distances(space, p, metric='cosine')\\n closeauthordis = closeauthordis.flatten()\\n closeauthors = closeauthordis.argsort()\\n closeauthordis.sort()\\n if n > 0:\\n closeauthors = closeauthors[0:n]\\n closeauthordis = closeauthordis[0:n]\\n idx = np.where(closeauthors == self.myidx)[0][0]\\n closeauthors = np.delete(closeauthors, idx)\\n closeauthordis = np.delete(closeauthordis, idx)\\n return closeauthors, closeauthordis\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n\\n def mycoauthorsV4byidx(self, idx):\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV4(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthors = []\\n for i in self.coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n result = []\\n for i in range(len(coauthorcount)):\\n result.append(OrderedDict([('name', self.authors[unicoauthors[-\\n (i + 1)]]), ('cooperationCount', coauthorcount[-(i + 1)])]))\\n return result, list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def removepluralbigram(self, bigram, pluralidx):\\n if not pluralidx:\\n print('empty')\\n return\\n delcount = 0\\n pren = 0\\n for i in pluralidx:\\n for n in i[1:]:\\n if n > pren:\\n n = n - delcount\\n bigram[i[0]][1] = bigram[i[0]][1] + bigram[n][1]\\n bigram.remove(bigram[n])\\n delcount = delcount + 1\\n pren = n\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getremdinfoV2(self, clsidx):\\n remdidx = self.closeauthors[clsidx]\\n username = self.authors[self.myidx]\\n recentpub = self.resentpublicationsidx(remdidx)\\n if recentpub:\\n name = self.authors[remdidx]\\n mentionlist = self.mentionnetwork[username]\\n if name in mentionlist:\\n return []\\n remdid = self.id_name[name]\\n if self.labels[remdid] == 'org':\\n return []\\n coauthors = self.mycoauthorsV4bymentionlist(name)\\n researchtopic = self.keywordbyidx(remdidx)\\n return OrderedDict([('name', name), ('relevancy', self.\\n closeauthordis[clsidx]), ('coAuthors', coauthors), (\\n 'researchTopics', researchtopic), ('recentPublications',\\n recentpub)])\\n else:\\n return []\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n\\n def debugmsg(self, msg, lvl):\\n if self.debug <= lvl:\\n print(msg)\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n\\n def thresholdrecommendations(self, remds, n):\\n thredremd = []\\n self.trd = np.zeros(3)\\n tdis = self.filteredcloseauthordis()\\n t1 = filters.threshold_otsu(tdis)\\n t2 = filters.threshold_otsu(tdis[tdis > t1])\\n self.trd[1] = len(tdis[tdis < t1])\\n self.trd[2] = len(tdis) - len(tdis[tdis > t2])\\n for i in range(3):\\n for j in range(int(n / 3)):\\n k = int(self.trd[i] + j)\\n name = remds[k]['name']\\n researchtopic = self.keyword(name)\\n remds[k]['researchTopics'] = researchtopic\\n thredremd.append(remds[k])\\n return thredremd\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def updatecoauthornetworkV2(self, net, authors, namelist):\\n nameidx = []\\n for name in namelist:\\n nameidx.append(authors.index(name))\\n for i in nameidx:\\n tmpidx = nameidx[:]\\n tmpidx.remove(i)\\n if not net:\\n net.append(tmpidx)\\n elif i > len(net) - 1:\\n net.append(tmpidx)\\n else:\\n net[i].extend(tmpidx)\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n\\n def initNLTKConditionalFreqDist(self):\\n self.debugmsg('start initNLTK CFD\\\\n', 0)\\n pairs = []\\n pairs = nltk.bigrams(self.allcorp)\\n self.cfd = nltk.ConditionalFreqDist(pairs)\\n self.debugmsg('end initNLTK CFD\\\\n', 0)\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n\\n def radiusofcluster(self, labels, nth, dismatrix):\\n idx = np.where(labels == nth)[0]\\n dis = dismatrix[idx, nth]\\n self.mindis = min(dis)\\n self.maxdis = max(dis)\\n self.radius = self.maxdis\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV3(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfo(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV3 \\\\n', 0)\\n return self.result\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def showcontents(self, labels, nth, allcontents):\\n contents = []\\n idx = np.where(labels == nth)\\n idx = np.array(idx)\\n idx = idx.flatten()\\n for i in idx:\\n contents.append(allcontents[i])\\n return contents\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def getVenue(self, userIdx):\\n venues = self.authorbooktitleidx[userIdx]\\n c = Counter(venues)\\n frqvenues = c.most_common()\\n return frqvenues[0][0]\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsbyyear(self, idx, year):\\n years = np.array(self.years)\\n yearidx = np.where(years <= year)[0]\\n coauthorsidx = [self.coauthorsidx[i] for i in yearidx]\\n coauthors = []\\n for i in coauthorsidx:\\n if idx in i:\\n t = i[:]\\n t.remove(idx)\\n coauthors.extend(t)\\n coauthors = np.array(coauthors)\\n unicoauthors, coauthorcount = np.unique(coauthors, return_counts=True)\\n unicoauthors = unicoauthors[coauthorcount.argsort()]\\n coauthorcount.sort()\\n return list(unicoauthors[::-1]), list(coauthorcount[::-1])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def mycoauthorsV2(self, name):\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n coauthorship = self.coauthornetV2[idx]\\n uniqcoauthors = np.array(list(set(coauthorship)))\\n coauthorcount = []\\n for i in uniqcoauthors:\\n coauthorcount.append(coauthorship.count(i))\\n countidx = np.argsort(coauthorcount)\\n countidx = countidx[::-1]\\n coauthorcount = np.array(coauthorcount)\\n result = []\\n for i in countidx:\\n result.append(OrderedDict([('name', self.authors[uniqcoauthors[\\n i]]), ('cooperationCount', coauthorcount[i])]))\\n return result, list(uniqcoauthors[countidx]), list(coauthorcount[\\n countidx])\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def recommendationV4(self, name, n):\\n self.nremd = n\\n self.debugmsg('Will generate recommendations in 3 groups and ' +\\n str(n) + ' for each group', 1)\\n self.debugmsg('find the idx', 0)\\n if isinstance(name, str):\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n else:\\n name = name.decode('utf-8')\\n name = ud.normalize('NFC', name)\\n authorIdx = self.authordict.get(name)\\n self.myidx = authorIdx\\n self.debugmsg('get the feature vector', 0)\\n featuretfidf = self.tfidfarray[authorIdx]\\n self.debugmsg('start distance computing \\\\n', 0)\\n self.closeauthors, self.closeauthordis = self.nNNlinesearch(self.\\n tfidfarray, featuretfidf, 0)\\n self.debugmsg('end distance computing \\\\n', 0)\\n self.debugmsg('start otsuifilter\\\\n', 0)\\n splitidx = self.otsufilter(self.closeauthordis)\\n self.debugmsg('end otsufilter\\\\n', 0)\\n recommendations = []\\n remdidx = []\\n for i in splitidx:\\n n = 0\\n backwardcount = 1\\n while n != self.nremd:\\n if self.closeauthors[i] != self.myidx:\\n remdinfo = self.getremdinfoV2(i)\\n if remdinfo and ~remdidx.count(i):\\n recommendations.append(remdinfo)\\n n = n + 1\\n remdidx.append(i)\\n i = i + 1\\n if i == len(self.closeauthordis) or backwardcount > 1:\\n if backwardcount == 1:\\n backwardstart = i - self.nremd\\n i = backwardstart - backwardcount\\n backwardcount = backwardcount + 1\\n random.shuffle(recommendations)\\n self.result = OrderedDict([('name', name), ('recommendations',\\n recommendations)])\\n self.debugmsg('end recommendationV4 \\\\n', 0)\\n return self.result\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def filteredrecommendations(self, n):\\n recommendations = []\\n self.filteridx = []\\n self.filteredauthors = []\\n i = 0\\n for name in self.recommendauthor:\\n [coauthors, idx, c] = self.mycoauthorsV4(name)\\n if idx.count(self.myidx):\\n i = i + 1\\n continue\\n recentpub = self.resentpublications(name)\\n if not recentpub:\\n i = i + 1\\n continue\\n self.filteredauthors.append(name)\\n researchtopic = []\\n researchtopic.append(OrderedDict([('topic', 'TBD')]))\\n recommendations.append(OrderedDict([('name', name), (\\n 'relevancy', self.closeauthordis[i]), ('coAuthors',\\n coauthors), ('researchTopics', researchtopic), (\\n 'recentPublications', recentpub)]))\\n self.filteridx.append(i)\\n i = i + 1\\n if len(self.filteridx) == n:\\n break\\n return recommendations\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n\\n def resentpublications(self, name):\\n resentpub = []\\n if isinstance(name, str):\\n idx = self.authordict.get(name)\\n else:\\n idx = self.authordict.get(name.decode('utf-8'))\\n idx = self.authortitlesidx[idx]\\n years = [self.years[i] for i in idx]\\n years = np.array(years)\\n years = years.argsort()\\n idx = np.array(idx)[years]\\n idx = idx.tolist()\\n idx.reverse()\\n if int(self.years[idx[0]]) < self.nyear or len(idx) < self.npaper:\\n return resentpub\\n for i in idx:\\n authorsjson = []\\n for author in self.coathors[i]:\\n authorsjson.append(OrderedDict([('name', author)]))\\n date = datetime.datetime.fromtimestamp(self.years[i]).strftime(\\n '%Y-%m-%d %H:%M:%S')\\n resentpub.append(OrderedDict([('title', self.rawtitles[i]), (\\n 'authors', authorsjson), ('year', date), (\\n 'publicationVenue', self.booktitle[i])]))\\n return resentpub\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass recommendationsys:\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <function token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n <docstring token>\\n <function token>\\n\",\n \"<docstring token>\\n<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8678,"cells":{"index":{"kind":"number","value":8678,"string":"8,678"},"blob_id":{"kind":"string","value":"74028a7b317c02c90603ad24c1ddb35a1d5d0e9d"},"code":{"kind":"string","value":"student = []\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n student.append([name, [grade1, grade2], avgrade])\n resp = ' '\n while resp not in 'NnYy':\n resp = str(input('Another student? [Y/N]'))\n if resp == 'N':\n break\nprint('-=' * 15)\nprint(f'{\"No.\":<4}{\"Name:\":<10}{\"Average Grade:\":>8}')\nprint('-=' * 15)\nfor i, a in enumerate(student):\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\nwhile True:\n print('-=' * 20)\n opt = int(input('Enter the student ID to show the grades: (999 to exit) '))\n if opt == 999:\n print('Exiting...')\n break\n if opt <= len(student) - 1:\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\nprint('Have a nice day!!!')\n"},"steps":{"kind":"list like","value":["student = []\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n student.append([name, [grade1, grade2], avgrade])\n resp = ' '\n while resp not in 'NnYy':\n resp = str(input('Another student? [Y/N]'))\n if resp == 'N':\n break\nprint('-=' * 15)\nprint(f'{\"No.\":<4}{\"Name:\":<10}{\"Average Grade:\":>8}')\nprint('-=' * 15)\nfor i, a in enumerate(student):\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\nwhile True:\n print('-=' * 20)\n opt = int(input('Enter the student ID to show the grades: (999 to exit) '))\n if opt == 999:\n print('Exiting...')\n break\n if opt <= len(student) - 1:\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\nprint('Have a nice day!!!')\n","student = []\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n student.append([name, [grade1, grade2], avgrade])\n resp = ' '\n while resp not in 'NnYy':\n resp = str(input('Another student? [Y/N]'))\n if resp == 'N':\n break\nprint('-=' * 15)\nprint(f\"{'No.':<4}{'Name:':<10}{'Average Grade:':>8}\")\nprint('-=' * 15)\nfor i, a in enumerate(student):\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\nwhile True:\n print('-=' * 20)\n opt = int(input('Enter the student ID to show the grades: (999 to exit) ')\n )\n if opt == 999:\n print('Exiting...')\n break\n if opt <= len(student) - 1:\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\nprint('Have a nice day!!!')\n","<assignment token>\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n student.append([name, [grade1, grade2], avgrade])\n resp = ' '\n while resp not in 'NnYy':\n resp = str(input('Another student? [Y/N]'))\n if resp == 'N':\n break\nprint('-=' * 15)\nprint(f\"{'No.':<4}{'Name:':<10}{'Average Grade:':>8}\")\nprint('-=' * 15)\nfor i, a in enumerate(student):\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\nwhile True:\n print('-=' * 20)\n opt = int(input('Enter the student ID to show the grades: (999 to exit) ')\n )\n if opt == 999:\n print('Exiting...')\n break\n if opt <= len(student) - 1:\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\nprint('Have a nice day!!!')\n","<assignment token>\n<code token>\n"],"string":"[\n \"student = []\\nwhile True:\\n name = str(input('Name: ')).capitalize().strip()\\n grade1 = float(input('Grade 1: '))\\n grade2 = float(input('Grade 2: '))\\n avgrade = (grade1 + grade2) / 2\\n student.append([name, [grade1, grade2], avgrade])\\n resp = ' '\\n while resp not in 'NnYy':\\n resp = str(input('Another student? [Y/N]'))\\n if resp == 'N':\\n break\\nprint('-=' * 15)\\nprint(f'{\\\"No.\\\":<4}{\\\"Name:\\\":<10}{\\\"Average Grade:\\\":>8}')\\nprint('-=' * 15)\\nfor i, a in enumerate(student):\\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\\nwhile True:\\n print('-=' * 20)\\n opt = int(input('Enter the student ID to show the grades: (999 to exit) '))\\n if opt == 999:\\n print('Exiting...')\\n break\\n if opt <= len(student) - 1:\\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\\nprint('Have a nice day!!!')\\n\",\n \"student = []\\nwhile True:\\n name = str(input('Name: ')).capitalize().strip()\\n grade1 = float(input('Grade 1: '))\\n grade2 = float(input('Grade 2: '))\\n avgrade = (grade1 + grade2) / 2\\n student.append([name, [grade1, grade2], avgrade])\\n resp = ' '\\n while resp not in 'NnYy':\\n resp = str(input('Another student? [Y/N]'))\\n if resp == 'N':\\n break\\nprint('-=' * 15)\\nprint(f\\\"{'No.':<4}{'Name:':<10}{'Average Grade:':>8}\\\")\\nprint('-=' * 15)\\nfor i, a in enumerate(student):\\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\\nwhile True:\\n print('-=' * 20)\\n opt = int(input('Enter the student ID to show the grades: (999 to exit) ')\\n )\\n if opt == 999:\\n print('Exiting...')\\n break\\n if opt <= len(student) - 1:\\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\\nprint('Have a nice day!!!')\\n\",\n \"<assignment token>\\nwhile True:\\n name = str(input('Name: ')).capitalize().strip()\\n grade1 = float(input('Grade 1: '))\\n grade2 = float(input('Grade 2: '))\\n avgrade = (grade1 + grade2) / 2\\n student.append([name, [grade1, grade2], avgrade])\\n resp = ' '\\n while resp not in 'NnYy':\\n resp = str(input('Another student? [Y/N]'))\\n if resp == 'N':\\n break\\nprint('-=' * 15)\\nprint(f\\\"{'No.':<4}{'Name:':<10}{'Average Grade:':>8}\\\")\\nprint('-=' * 15)\\nfor i, a in enumerate(student):\\n print(f'{i:<4}{a[0]:<8}{a[2]:>8.1f}')\\nwhile True:\\n print('-=' * 20)\\n opt = int(input('Enter the student ID to show the grades: (999 to exit) ')\\n )\\n if opt == 999:\\n print('Exiting...')\\n break\\n if opt <= len(student) - 1:\\n print(f'Grades of {student[opt][0]} are {student[opt][1]}')\\nprint('Have a nice day!!!')\\n\",\n \"<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8679,"cells":{"index":{"kind":"number","value":8679,"string":"8,679"},"blob_id":{"kind":"string","value":"606abf8501d85c29051df4bf0276ed5b098ee6c5"},"code":{"kind":"string","value":"from django.contrib import admin\nfrom search.models import PrimaryCategory,PlaceCategory\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n \n list_display = ('primary_name','is_active','description','image',)\n actions = None\n \n def has_delete_permission(self,request,obj=None):\n return False\n \n \nclass PlaceCategoryAdmin(admin.ModelAdmin):\n \n list_display = ('category_name','is_paid','description','is_active','image','primary_category')\n actions = None\n \n \n def primary_category(self,obj):\n \n return obj.primary_category.primary_name\n \n def has_delete_permission(self,request,obj=None):\n return False\n\nadmin.site.register(PrimaryCategory,PrimaryCategoryAdmin) \nadmin.site.register(PlaceCategory,PlaceCategoryAdmin)\n\n \n"},"steps":{"kind":"list like","value":["from django.contrib import admin\nfrom search.models import PrimaryCategory,PlaceCategory\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n \n list_display = ('primary_name','is_active','description','image',)\n actions = None\n \n def has_delete_permission(self,request,obj=None):\n return False\n \n \nclass PlaceCategoryAdmin(admin.ModelAdmin):\n \n list_display = ('category_name','is_paid','description','is_active','image','primary_category')\n actions = None\n \n \n def primary_category(self,obj):\n \n return obj.primary_category.primary_name\n \n def has_delete_permission(self,request,obj=None):\n return False\n\nadmin.site.register(PrimaryCategory,PrimaryCategoryAdmin) \nadmin.site.register(PlaceCategory,PlaceCategoryAdmin)\n\n \n","from django.contrib import admin\nfrom search.models import PrimaryCategory, PlaceCategory\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n list_display = 'primary_name', 'is_active', 'description', 'image'\n actions = None\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nadmin.site.register(PrimaryCategory, PrimaryCategoryAdmin)\nadmin.site.register(PlaceCategory, PlaceCategoryAdmin)\n","<import token>\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n list_display = 'primary_name', 'is_active', 'description', 'image'\n actions = None\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nadmin.site.register(PrimaryCategory, PrimaryCategoryAdmin)\nadmin.site.register(PlaceCategory, PlaceCategoryAdmin)\n","<import token>\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n list_display = 'primary_name', 'is_active', 'description', 'image'\n actions = None\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\n<code token>\n","<import token>\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n <assignment token>\n <assignment token>\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\n<code token>\n","<import token>\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n <assignment token>\n <assignment token>\n <function token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\n<code token>\n","<import token>\n<class token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\n 'image', 'primary_category')\n actions = None\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\n<code token>\n","<import token>\n<class token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n <assignment token>\n <assignment token>\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n\n def has_delete_permission(self, request, obj=None):\n return False\n\n\n<code token>\n","<import token>\n<class token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n <assignment token>\n <assignment token>\n\n def primary_category(self, obj):\n return obj.primary_category.primary_name\n <function token>\n\n\n<code token>\n","<import token>\n<class token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n <assignment token>\n <assignment token>\n <function token>\n <function token>\n\n\n<code token>\n","<import token>\n<class token>\n<class token>\n<code token>\n"],"string":"[\n \"from django.contrib import admin\\nfrom search.models import PrimaryCategory,PlaceCategory\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n \\n list_display = ('primary_name','is_active','description','image',)\\n actions = None\\n \\n def has_delete_permission(self,request,obj=None):\\n return False\\n \\n \\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n \\n list_display = ('category_name','is_paid','description','is_active','image','primary_category')\\n actions = None\\n \\n \\n def primary_category(self,obj):\\n \\n return obj.primary_category.primary_name\\n \\n def has_delete_permission(self,request,obj=None):\\n return False\\n\\nadmin.site.register(PrimaryCategory,PrimaryCategoryAdmin) \\nadmin.site.register(PlaceCategory,PlaceCategoryAdmin)\\n\\n \\n\",\n \"from django.contrib import admin\\nfrom search.models import PrimaryCategory, PlaceCategory\\n\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n list_display = 'primary_name', 'is_active', 'description', 'image'\\n actions = None\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nadmin.site.register(PrimaryCategory, PrimaryCategoryAdmin)\\nadmin.site.register(PlaceCategory, PlaceCategoryAdmin)\\n\",\n \"<import token>\\n\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n list_display = 'primary_name', 'is_active', 'description', 'image'\\n actions = None\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nadmin.site.register(PrimaryCategory, PrimaryCategoryAdmin)\\nadmin.site.register(PlaceCategory, PlaceCategoryAdmin)\\n\",\n \"<import token>\\n\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n list_display = 'primary_name', 'is_active', 'description', 'image'\\n actions = None\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\n<code token>\\n\",\n \"<import token>\\n\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n <assignment token>\\n <assignment token>\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\n<code token>\\n\",\n \"<import token>\\n\\n\\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\\n <assignment token>\\n <assignment token>\\n <function token>\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n list_display = ('category_name', 'is_paid', 'description', 'is_active',\\n 'image', 'primary_category')\\n actions = None\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n <assignment token>\\n <assignment token>\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n\\n def has_delete_permission(self, request, obj=None):\\n return False\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n <assignment token>\\n <assignment token>\\n\\n def primary_category(self, obj):\\n return obj.primary_category.primary_name\\n <function token>\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass PlaceCategoryAdmin(admin.ModelAdmin):\\n <assignment token>\\n <assignment token>\\n <function token>\\n <function token>\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8680,"cells":{"index":{"kind":"number","value":8680,"string":"8,680"},"blob_id":{"kind":"string","value":"932502c93dd7dfc095adfe2ab88b4404396d9845"},"code":{"kind":"string","value":"# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\nimport contextlib\n\nimport mock\nfrom oslo_concurrency import processutils as putils\nimport six\n\nfrom cinder import context\nfrom cinder import exception\n\nfrom cinder.tests.unit.targets import targets_fixture as tf\nfrom cinder import utils\nfrom cinder.volume.targets import iet\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n' # noqa\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n' # noqa\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1',\n self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\n ))\n\n # Test the failure case: Failed to handle the config file\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError,\n self.target._get_target,\n '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = ('', '')\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(\n 0,\n self.target.create_iscsi_target(\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n\n # Test the failure case: Failed to chown the config file\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.create_iscsi_target,\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir)\n\n # Test the failure case: Failed to set new auth\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.create_iscsi_target,\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n # Test the failure case: conf file does not exist\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.update_config_file,\n self.test_vol,\n 0,\n self.fake_volumes_dir,\n \"foo bar\")\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n @mock.patch('cinder.utils.execute')\n def test_create_iscsi_target_already_exists(self, mock_execute,\n mock_get_targ):\n mock_execute.return_value = ('fake out', 'fake err')\n self.assertEqual(\n 1,\n self.target.create_iscsi_target(\n self.test_vol,\n 1,\n 0,\n self.fake_volumes_dir))\n self.assertTrue(mock_get_targ.called)\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n\n # Test the normal case\n self.target.remove_iscsi_target(1,\n 0,\n self.testvol['id'],\n self.testvol['name'])\n mock_execute.assert_any_call('ietadm',\n '--op',\n 'delete',\n '--tid=1',\n run_as_root=True)\n\n # Test the failure case: putils.ProcessExecutionError\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed,\n self.target.remove_iscsi_target,\n 1,\n 0,\n self.testvol['id'],\n self.testvol['name'])\n\n def test_find_sid_cid_for_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n' # noqa\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n' # noqa\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(('844427031282176', '0'),\n self.target._find_sid_cid_for_target(\n '1',\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45', # noqa\n 'volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\n ))\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute,\n mock_get_targ):\n mock_execute.return_value = ('', '')\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location': '10.9.8.7:3260,1 '\n 'iqn.2010-10.org.openstack:testvol 0',\n 'auth': 'CHAP '\n 'QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result,\n self.target.create_export(ctxt,\n self.testvol,\n self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt,\n self.testvol,\n self.fake_volumes_dir)\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol',\n 1, 0, self.fake_volumes_dir, None,\n portals_ips=[self.configuration.iscsi_ip_address],\n portals_port=int(self.configuration.iscsi_port),\n check_exit_code=False,\n old_name=None)\n"},"steps":{"kind":"list like","value":["# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\nimport contextlib\n\nimport mock\nfrom oslo_concurrency import processutils as putils\nimport six\n\nfrom cinder import context\nfrom cinder import exception\n\nfrom cinder.tests.unit.targets import targets_fixture as tf\nfrom cinder import utils\nfrom cinder.volume.targets import iet\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n' # noqa\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n' # noqa\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1',\n self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\n ))\n\n # Test the failure case: Failed to handle the config file\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError,\n self.target._get_target,\n '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = ('', '')\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(\n 0,\n self.target.create_iscsi_target(\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n\n # Test the failure case: Failed to chown the config file\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.create_iscsi_target,\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir)\n\n # Test the failure case: Failed to set new auth\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.create_iscsi_target,\n self.test_vol,\n 0,\n 0,\n self.fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n # Test the failure case: conf file does not exist\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed,\n self.target.update_config_file,\n self.test_vol,\n 0,\n self.fake_volumes_dir,\n \"foo bar\")\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n @mock.patch('cinder.utils.execute')\n def test_create_iscsi_target_already_exists(self, mock_execute,\n mock_get_targ):\n mock_execute.return_value = ('fake out', 'fake err')\n self.assertEqual(\n 1,\n self.target.create_iscsi_target(\n self.test_vol,\n 1,\n 0,\n self.fake_volumes_dir))\n self.assertTrue(mock_get_targ.called)\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n\n # Test the normal case\n self.target.remove_iscsi_target(1,\n 0,\n self.testvol['id'],\n self.testvol['name'])\n mock_execute.assert_any_call('ietadm',\n '--op',\n 'delete',\n '--tid=1',\n run_as_root=True)\n\n # Test the failure case: putils.ProcessExecutionError\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed,\n self.target.remove_iscsi_target,\n 1,\n 0,\n self.testvol['id'],\n self.testvol['name'])\n\n def test_find_sid_cid_for_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n' # noqa\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n' # noqa\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(('844427031282176', '0'),\n self.target._find_sid_cid_for_target(\n '1',\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45', # noqa\n 'volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\n ))\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute,\n mock_get_targ):\n mock_execute.return_value = ('', '')\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location': '10.9.8.7:3260,1 '\n 'iqn.2010-10.org.openstack:testvol 0',\n 'auth': 'CHAP '\n 'QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result,\n self.target.create_export(ctxt,\n self.testvol,\n self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\n return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt,\n self.testvol,\n self.fake_volumes_dir)\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol',\n 1, 0, self.fake_volumes_dir, None,\n portals_ips=[self.configuration.iscsi_ip_address],\n portals_port=int(self.configuration.iscsi_port),\n check_exit_code=False,\n old_name=None)\n","import contextlib\nimport mock\nfrom oslo_concurrency import processutils as putils\nimport six\nfrom cinder import context\nfrom cinder import exception\nfrom cinder.tests.unit.targets import targets_fixture as tf\nfrom cinder import utils\nfrom cinder.volume.targets import iet\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(0, self.target.create_iscsi_target(self.\n test_vol, 0, 0, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n def test_create_iscsi_target_already_exists(self, mock_execute,\n mock_get_targ):\n mock_execute.return_value = 'fake out', 'fake err'\n self.assertEqual(1, self.target.create_iscsi_target(self.test_vol, \n 1, 0, self.fake_volumes_dir))\n self.assertTrue(mock_get_targ.called)\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n\n def test_find_sid_cid_for_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(('844427031282176', '0'), self.target.\n _find_sid_cid_for_target('1',\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(0, self.target.create_iscsi_target(self.\n test_vol, 0, 0, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n def test_create_iscsi_target_already_exists(self, mock_execute,\n mock_get_targ):\n mock_execute.return_value = 'fake out', 'fake err'\n self.assertEqual(1, self.target.create_iscsi_target(self.test_vol, \n 1, 0, self.fake_volumes_dir))\n self.assertTrue(mock_get_targ.called)\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n\n def test_find_sid_cid_for_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(('844427031282176', '0'), self.target.\n _find_sid_cid_for_target('1',\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(0, self.target.create_iscsi_target(self.\n test_vol, 0, 0, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n\n def test_find_sid_cid_for_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(('844427031282176', '0'), self.target.\n _find_sid_cid_for_target('1',\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n\n def setUp(self):\n super(TestIetAdmDriver, self).setUp()\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\n configuration=self.configuration)\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(0, self.target.create_iscsi_target(self.\n test_vol, 0, 0, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n @mock.patch('cinder.utils.temporary_chown')\n @mock.patch.object(iet, 'LOG')\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\n mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n tmp_file = six.StringIO()\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual(0, self.target.create_iscsi_target(self.\n test_vol, 0, 0, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n self.assertTrue(mock_open.called)\n self.assertTrue(mock_get_targ.called)\n mock_open.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\n target.create_iscsi_target, self.test_vol, 0, 0, self.\n fake_volumes_dir)\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\"\"\"\n )\n tmp_file.seek(0)\n with mock.patch('six.moves.builtins.open') as mock_open:\n mock_open.return_value = contextlib.closing(tmp_file)\n self.assertEqual('1', self.target._get_target(\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\n ))\n mock_open.side_effect = MemoryError()\n self.assertRaises(MemoryError, self.target._get_target, '')\n <function token>\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n <function token>\n <function token>\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n @mock.patch('cinder.utils.execute')\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\n mock_execute.return_value = '', ''\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\n 'P68eE7u9eFqDGexd28DQ')\n expected_result = {'location':\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\n ctxt = context.get_admin_context()\n self.assertEqual(expected_result, self.target.create_export(ctxt,\n self.testvol, self.fake_volumes_dir))\n self.assertTrue(mock_execute.called)\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n <function token>\n <function token>\n\n @mock.patch('cinder.utils.execute')\n @mock.patch('os.path.exists', return_value=True)\n def test_update_config_file_failure(self, mock_exists, mock_execute):\n mock_exists.return_value = False\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\n 'foo bar')\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\n return_value=None)\n @mock.patch('os.path.exists', return_value=False)\n @mock.patch('cinder.utils.execute')\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\n testvol['name'])\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\n run_as_root=True)\n mock_execute.side_effect = putils.ProcessExecutionError\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\n )\n <function token>\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\n return_value=None)\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\n ctxt = context.get_admin_context()\n with mock.patch.object(self.target, 'create_iscsi_target'):\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\n )\n self.target.create_iscsi_target.assert_called_once_with(\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\n fake_volumes_dir, None, portals_ips=[self.configuration.\n iscsi_ip_address], portals_port=int(self.configuration.\n iscsi_port), check_exit_code=False, old_name=None)\n","<import token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n","<import token>\n<class token>\n"],"string":"[\n \"# Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); you may\\n# not use this file except in compliance with the License. You may obtain\\n# a copy of the License at\\n#\\n# http://www.apache.org/licenses/LICENSE-2.0\\n#\\n# Unless required by applicable law or agreed to in writing, software\\n# distributed under the License is distributed on an \\\"AS IS\\\" BASIS, WITHOUT\\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\\n# License for the specific language governing permissions and limitations\\n# under the License.\\n\\nimport contextlib\\n\\nimport mock\\nfrom oslo_concurrency import processutils as putils\\nimport six\\n\\nfrom cinder import context\\nfrom cinder import exception\\n\\nfrom cinder.tests.unit.targets import targets_fixture as tf\\nfrom cinder import utils\\nfrom cinder.volume.targets import iet\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n\\n def setUp(self):\\n super(TestIetAdmDriver, self).setUp()\\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\\n configuration=self.configuration)\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\\\n' # noqa\\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\\\n' # noqa\\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1',\\n self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\\n ))\\n\\n # Test the failure case: Failed to handle the config file\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError,\\n self.target._get_target,\\n '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\\n return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = ('', '')\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(\\n 0,\\n self.target.create_iscsi_target(\\n self.test_vol,\\n 0,\\n 0,\\n self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n\\n # Test the failure case: Failed to chown the config file\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed,\\n self.target.create_iscsi_target,\\n self.test_vol,\\n 0,\\n 0,\\n self.fake_volumes_dir)\\n\\n # Test the failure case: Failed to set new auth\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed,\\n self.target.create_iscsi_target,\\n self.test_vol,\\n 0,\\n 0,\\n self.fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n # Test the failure case: conf file does not exist\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed,\\n self.target.update_config_file,\\n self.test_vol,\\n 0,\\n self.fake_volumes_dir,\\n \\\"foo bar\\\")\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\\n return_value=1)\\n @mock.patch('cinder.utils.execute')\\n def test_create_iscsi_target_already_exists(self, mock_execute,\\n mock_get_targ):\\n mock_execute.return_value = ('fake out', 'fake err')\\n self.assertEqual(\\n 1,\\n self.target.create_iscsi_target(\\n self.test_vol,\\n 1,\\n 0,\\n self.fake_volumes_dir))\\n self.assertTrue(mock_get_targ.called)\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n\\n # Test the normal case\\n self.target.remove_iscsi_target(1,\\n 0,\\n self.testvol['id'],\\n self.testvol['name'])\\n mock_execute.assert_any_call('ietadm',\\n '--op',\\n 'delete',\\n '--tid=1',\\n run_as_root=True)\\n\\n # Test the failure case: putils.ProcessExecutionError\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed,\\n self.target.remove_iscsi_target,\\n 1,\\n 0,\\n self.testvol['id'],\\n self.testvol['name'])\\n\\n def test_find_sid_cid_for_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n 'tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\\\n' # noqa\\n ' sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\\\n' # noqa\\n ' cid:0 ip:10.9.8.7 state:active hd:none dd:none')\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(('844427031282176', '0'),\\n self.target._find_sid_cid_for_target(\\n '1',\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45', # noqa\\n 'volume-83c2e877-feed-46be-8435-77884fe55b45' # noqa\\n ))\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\\n return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute,\\n mock_get_targ):\\n mock_execute.return_value = ('', '')\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location': '10.9.8.7:3260,1 '\\n 'iqn.2010-10.org.openstack:testvol 0',\\n 'auth': 'CHAP '\\n 'QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result,\\n self.target.create_export(ctxt,\\n self.testvol,\\n self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target',\\n return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt,\\n self.testvol,\\n self.fake_volumes_dir)\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol',\\n 1, 0, self.fake_volumes_dir, None,\\n portals_ips=[self.configuration.iscsi_ip_address],\\n portals_port=int(self.configuration.iscsi_port),\\n check_exit_code=False,\\n old_name=None)\\n\",\n \"import contextlib\\nimport mock\\nfrom oslo_concurrency import processutils as putils\\nimport six\\nfrom cinder import context\\nfrom cinder import exception\\nfrom cinder.tests.unit.targets import targets_fixture as tf\\nfrom cinder import utils\\nfrom cinder.volume.targets import iet\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n\\n def setUp(self):\\n super(TestIetAdmDriver, self).setUp()\\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\\n configuration=self.configuration)\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(0, self.target.create_iscsi_target(self.\\n test_vol, 0, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n def test_create_iscsi_target_already_exists(self, mock_execute,\\n mock_get_targ):\\n mock_execute.return_value = 'fake out', 'fake err'\\n self.assertEqual(1, self.target.create_iscsi_target(self.test_vol, \\n 1, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_get_targ.called)\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n\\n def test_find_sid_cid_for_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(('844427031282176', '0'), self.target.\\n _find_sid_cid_for_target('1',\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n\\n def setUp(self):\\n super(TestIetAdmDriver, self).setUp()\\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\\n configuration=self.configuration)\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(0, self.target.create_iscsi_target(self.\\n test_vol, 0, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n def test_create_iscsi_target_already_exists(self, mock_execute,\\n mock_get_targ):\\n mock_execute.return_value = 'fake out', 'fake err'\\n self.assertEqual(1, self.target.create_iscsi_target(self.test_vol, \\n 1, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_get_targ.called)\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n\\n def test_find_sid_cid_for_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(('844427031282176', '0'), self.target.\\n _find_sid_cid_for_target('1',\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n\\n def setUp(self):\\n super(TestIetAdmDriver, self).setUp()\\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\\n configuration=self.configuration)\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(0, self.target.create_iscsi_target(self.\\n test_vol, 0, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n\\n def test_find_sid_cid_for_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(('844427031282176', '0'), self.target.\\n _find_sid_cid_for_target('1',\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n , 'volume-83c2e877-feed-46be-8435-77884fe55b45'))\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n\\n def setUp(self):\\n super(TestIetAdmDriver, self).setUp()\\n self.target = iet.IetAdm(root_helper=utils.get_root_helper(),\\n configuration=self.configuration)\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(0, self.target.create_iscsi_target(self.\\n test_vol, 0, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=0)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n @mock.patch('cinder.utils.temporary_chown')\\n @mock.patch.object(iet, 'LOG')\\n def test_create_iscsi_target(self, mock_log, mock_chown, mock_exists,\\n mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n tmp_file = six.StringIO()\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual(0, self.target.create_iscsi_target(self.\\n test_vol, 0, 0, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n self.assertTrue(mock_open.called)\\n self.assertTrue(mock_get_targ.called)\\n mock_open.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.\\n target.create_iscsi_target, self.test_vol, 0, 0, self.\\n fake_volumes_dir)\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n\\n def test_get_target(self):\\n tmp_file = six.StringIO()\\n tmp_file.write(\\n \\\"\\\"\\\"tid:1 name:iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45\\n sid:844427031282176 initiator:iqn.1994-05.com.redhat:5a6894679665\\n cid:0 ip:10.9.8.7 state:active hd:none dd:none\\\"\\\"\\\"\\n )\\n tmp_file.seek(0)\\n with mock.patch('six.moves.builtins.open') as mock_open:\\n mock_open.return_value = contextlib.closing(tmp_file)\\n self.assertEqual('1', self.target._get_target(\\n 'iqn.2010-10.org.openstack:volume-83c2e877-feed-46be-8435-77884fe55b45'\\n ))\\n mock_open.side_effect = MemoryError()\\n self.assertRaises(MemoryError, self.target._get_target, '')\\n <function token>\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n @mock.patch('cinder.utils.execute')\\n @mock.patch.object(iet.IetAdm, '_get_target_chap_auth')\\n def test_create_export(self, mock_get_chap, mock_execute, mock_get_targ):\\n mock_execute.return_value = '', ''\\n mock_get_chap.return_value = ('QZJbisGmn9AL954FNF4D',\\n 'P68eE7u9eFqDGexd28DQ')\\n expected_result = {'location':\\n '10.9.8.7:3260,1 iqn.2010-10.org.openstack:testvol 0', 'auth':\\n 'CHAP QZJbisGmn9AL954FNF4D P68eE7u9eFqDGexd28DQ'}\\n ctxt = context.get_admin_context()\\n self.assertEqual(expected_result, self.target.create_export(ctxt,\\n self.testvol, self.fake_volumes_dir))\\n self.assertTrue(mock_execute.called)\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.utils.execute')\\n @mock.patch('os.path.exists', return_value=True)\\n def test_update_config_file_failure(self, mock_exists, mock_execute):\\n mock_exists.return_value = False\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetCreateFailed, self.target.\\n update_config_file, self.test_vol, 0, self.fake_volumes_dir,\\n 'foo bar')\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._find_sid_cid_for_target',\\n return_value=None)\\n @mock.patch('os.path.exists', return_value=False)\\n @mock.patch('cinder.utils.execute')\\n def test_remove_iscsi_target(self, mock_execute, mock_exists, mock_find):\\n self.target.remove_iscsi_target(1, 0, self.testvol['id'], self.\\n testvol['name'])\\n mock_execute.assert_any_call('ietadm', '--op', 'delete', '--tid=1',\\n run_as_root=True)\\n mock_execute.side_effect = putils.ProcessExecutionError\\n self.assertRaises(exception.ISCSITargetRemoveFailed, self.target.\\n remove_iscsi_target, 1, 0, self.testvol['id'], self.testvol['name']\\n )\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target_chap_auth',\\n return_value=None)\\n @mock.patch('cinder.volume.targets.iet.IetAdm._get_target', return_value=1)\\n def test_ensure_export(self, mock_get_targetm, mock_get_chap):\\n ctxt = context.get_admin_context()\\n with mock.patch.object(self.target, 'create_iscsi_target'):\\n self.target.ensure_export(ctxt, self.testvol, self.fake_volumes_dir\\n )\\n self.target.create_iscsi_target.assert_called_once_with(\\n 'iqn.2010-10.org.openstack:testvol', 1, 0, self.\\n fake_volumes_dir, None, portals_ips=[self.configuration.\\n iscsi_ip_address], portals_port=int(self.configuration.\\n iscsi_port), check_exit_code=False, old_name=None)\\n\",\n \"<import token>\\n\\n\\nclass TestIetAdmDriver(tf.TargetDriverFixture):\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8681,"cells":{"index":{"kind":"number","value":8681,"string":"8,681"},"blob_id":{"kind":"string","value":"7c6ada250770e04b395dda774a78042da69e2854"},"code":{"kind":"string","value":"from collections import Counter\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n \n c = Counter(A).most_common()\n \n if c[0][0] == 0 and c[0][1] == N:\n print(\"Yes\")\n elif len(c) == 2 and c[0][1] == 2*N//3 and c[1][0] == 0 and c[1][1] == N//3:\n print(\"Yes\")\n elif len(c) == 3 and int(c[0][0])^int(c[1][0]) == int(c[2][0]) and c[0][1] == c[1][1] and c[1][1] == c[2][1]:\n print(\"Yes\")\n else:\n print(\"No\")\n\nif __name__ == \"__main__\":\n main()"},"steps":{"kind":"list like","value":["from collections import Counter\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n \n c = Counter(A).most_common()\n \n if c[0][0] == 0 and c[0][1] == N:\n print(\"Yes\")\n elif len(c) == 2 and c[0][1] == 2*N//3 and c[1][0] == 0 and c[1][1] == N//3:\n print(\"Yes\")\n elif len(c) == 3 and int(c[0][0])^int(c[1][0]) == int(c[2][0]) and c[0][1] == c[1][1] and c[1][1] == c[2][1]:\n print(\"Yes\")\n else:\n print(\"No\")\n\nif __name__ == \"__main__\":\n main()","from collections import Counter\n\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n c = Counter(A).most_common()\n if c[0][0] == 0 and c[0][1] == N:\n print('Yes')\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\n ] == N // 3:\n print('Yes')\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\n ] == c[1][1] and c[1][1] == c[2][1]:\n print('Yes')\n else:\n print('No')\n\n\nif __name__ == '__main__':\n main()\n","<import token>\n\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n c = Counter(A).most_common()\n if c[0][0] == 0 and c[0][1] == N:\n print('Yes')\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\n ] == N // 3:\n print('Yes')\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\n ] == c[1][1] and c[1][1] == c[2][1]:\n print('Yes')\n else:\n print('No')\n\n\nif __name__ == '__main__':\n main()\n","<import token>\n\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n c = Counter(A).most_common()\n if c[0][0] == 0 and c[0][1] == N:\n print('Yes')\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\n ] == N // 3:\n print('Yes')\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\n ] == c[1][1] and c[1][1] == c[2][1]:\n print('Yes')\n else:\n print('No')\n\n\n<code token>\n","<import token>\n<function token>\n<code token>\n"],"string":"[\n \"from collections import Counter\\n\\ndef main():\\n N = int(input())\\n A = tuple(map(int, input().split()))\\n \\n c = Counter(A).most_common()\\n \\n if c[0][0] == 0 and c[0][1] == N:\\n print(\\\"Yes\\\")\\n elif len(c) == 2 and c[0][1] == 2*N//3 and c[1][0] == 0 and c[1][1] == N//3:\\n print(\\\"Yes\\\")\\n elif len(c) == 3 and int(c[0][0])^int(c[1][0]) == int(c[2][0]) and c[0][1] == c[1][1] and c[1][1] == c[2][1]:\\n print(\\\"Yes\\\")\\n else:\\n print(\\\"No\\\")\\n\\nif __name__ == \\\"__main__\\\":\\n main()\",\n \"from collections import Counter\\n\\n\\ndef main():\\n N = int(input())\\n A = tuple(map(int, input().split()))\\n c = Counter(A).most_common()\\n if c[0][0] == 0 and c[0][1] == N:\\n print('Yes')\\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\\n ] == N // 3:\\n print('Yes')\\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\\n ] == c[1][1] and c[1][1] == c[2][1]:\\n print('Yes')\\n else:\\n print('No')\\n\\n\\nif __name__ == '__main__':\\n main()\\n\",\n \"<import token>\\n\\n\\ndef main():\\n N = int(input())\\n A = tuple(map(int, input().split()))\\n c = Counter(A).most_common()\\n if c[0][0] == 0 and c[0][1] == N:\\n print('Yes')\\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\\n ] == N // 3:\\n print('Yes')\\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\\n ] == c[1][1] and c[1][1] == c[2][1]:\\n print('Yes')\\n else:\\n print('No')\\n\\n\\nif __name__ == '__main__':\\n main()\\n\",\n \"<import token>\\n\\n\\ndef main():\\n N = int(input())\\n A = tuple(map(int, input().split()))\\n c = Counter(A).most_common()\\n if c[0][0] == 0 and c[0][1] == N:\\n print('Yes')\\n elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == 0 and c[1][1\\n ] == N // 3:\\n print('Yes')\\n elif len(c) == 3 and int(c[0][0]) ^ int(c[1][0]) == int(c[2][0]) and c[0][1\\n ] == c[1][1] and c[1][1] == c[2][1]:\\n print('Yes')\\n else:\\n print('No')\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8682,"cells":{"index":{"kind":"number","value":8682,"string":"8,682"},"blob_id":{"kind":"string","value":"130581ddb0394dcceabc316468385d4e21959b63"},"code":{"kind":"string","value":"import unittest\nfrom domain.Activity import Activity\nfrom domain.NABException import NABException\nfrom domain.Person import Person\nfrom domain.ActivityValidator import ActivityValidator\nfrom repository.PersonRepository import PersonRepository\nfrom repository.PersonFileRepository import PersonFileRepository\nfrom repository.ActivityRepository import ActivityRepository\nfrom repository.ActivityFileRepository import ActivityFileRepository\nfrom controller.StatsController import StatsController\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, \"John\", \"1\", \"A\")\n self.q = Person(2, \"Mary\", \"1\", \"B\")\n self.a1 = Activity(self.p, \"2015.12.20\", \"12:12\", \"Swimming\")\n self.a2 = Activity(self.p, \"2016.01.20\", \"12:12\", \"Mapping\")\n self.a3 = Activity(self.q, \"2015.12.21\", \"12:12\", \"Swimming\")\n self.a4 = Activity(self.q, \"2015.12.20\", \"10:12\", \"Reading\")\n\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n\n\n def test_activities_for_person_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_for_person_by_date(1) == [a1, a2]\n assert L.activities_for_person_by_date(2) == [a4, a3]\n assert L.activities_for_person_by_date(4) == []\n\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n\n assert L.people_with_activities_in_interval(\"2015.12.20\", \"2016.01.01\") == [p, q]\n assert L.people_with_activities_in_interval(\"2000.01.01\", \"2010.01.01\") == []\n assert L.people_with_activities_in_interval(\"2016.01.01\", \"2017.01.01\") == [p]\n assert L.people_with_activities_in_interval(\"2015.12.21\", \"2015.12.21\") == [q]\n\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_in_interval_alphabetically(\"2015.12.20\", \"2016.01.01\") == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically(\"2000.01.01\", \"2010.01.01\") == []\n assert L.activities_in_interval_alphabetically(\"2016.01.01\", \"2017.01.01\") == [a2]\n assert L.activities_in_interval_alphabetically(\"2015.12.21\", \"2015.12.21\") == [a3]\n\n\n def test_activities_in_interval_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_in_interval_by_date(\"2015.12.20\", \"2016.01.01\") == [a4, a1, a3]\n assert L.activities_in_interval_by_date(\"2000.01.01\", \"2010.01.01\") == []\n assert L.activities_in_interval_by_date(\"2016.01.01\", \"2017.01.01\") == [a2]\n assert L.activities_in_interval_by_date(\"2015.12.21\", \"2015.12.21\") == [a3]"},"steps":{"kind":"list like","value":["import unittest\nfrom domain.Activity import Activity\nfrom domain.NABException import NABException\nfrom domain.Person import Person\nfrom domain.ActivityValidator import ActivityValidator\nfrom repository.PersonRepository import PersonRepository\nfrom repository.PersonFileRepository import PersonFileRepository\nfrom repository.ActivityRepository import ActivityRepository\nfrom repository.ActivityFileRepository import ActivityFileRepository\nfrom controller.StatsController import StatsController\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, \"John\", \"1\", \"A\")\n self.q = Person(2, \"Mary\", \"1\", \"B\")\n self.a1 = Activity(self.p, \"2015.12.20\", \"12:12\", \"Swimming\")\n self.a2 = Activity(self.p, \"2016.01.20\", \"12:12\", \"Mapping\")\n self.a3 = Activity(self.q, \"2015.12.21\", \"12:12\", \"Swimming\")\n self.a4 = Activity(self.q, \"2015.12.20\", \"10:12\", \"Reading\")\n\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n\n\n def test_activities_for_person_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_for_person_by_date(1) == [a1, a2]\n assert L.activities_for_person_by_date(2) == [a4, a3]\n assert L.activities_for_person_by_date(4) == []\n\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n\n assert L.people_with_activities_in_interval(\"2015.12.20\", \"2016.01.01\") == [p, q]\n assert L.people_with_activities_in_interval(\"2000.01.01\", \"2010.01.01\") == []\n assert L.people_with_activities_in_interval(\"2016.01.01\", \"2017.01.01\") == [p]\n assert L.people_with_activities_in_interval(\"2015.12.21\", \"2015.12.21\") == [q]\n\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_in_interval_alphabetically(\"2015.12.20\", \"2016.01.01\") == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically(\"2000.01.01\", \"2010.01.01\") == []\n assert L.activities_in_interval_alphabetically(\"2016.01.01\", \"2017.01.01\") == [a2]\n assert L.activities_in_interval_alphabetically(\"2015.12.21\", \"2015.12.21\") == [a3]\n\n\n def test_activities_in_interval_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n\n assert L.activities_in_interval_by_date(\"2015.12.20\", \"2016.01.01\") == [a4, a1, a3]\n assert L.activities_in_interval_by_date(\"2000.01.01\", \"2010.01.01\") == []\n assert L.activities_in_interval_by_date(\"2016.01.01\", \"2017.01.01\") == [a2]\n assert L.activities_in_interval_by_date(\"2015.12.21\", \"2015.12.21\") == [a3]","import unittest\nfrom domain.Activity import Activity\nfrom domain.NABException import NABException\nfrom domain.Person import Person\nfrom domain.ActivityValidator import ActivityValidator\nfrom repository.PersonRepository import PersonRepository\nfrom repository.PersonFileRepository import PersonFileRepository\nfrom repository.ActivityRepository import ActivityRepository\nfrom repository.ActivityFileRepository import ActivityFileRepository\nfrom controller.StatsController import StatsController\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, 'John', '1', 'A')\n self.q = Person(2, 'Mary', '1', 'B')\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n\n def test_activities_for_person_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_by_date(1) == [a1, a2]\n assert L.activities_for_person_by_date(2) == [a4, a3]\n assert L.activities_for_person_by_date(4) == []\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_alphabetically('2015.12.20',\n '2016.01.01') == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically('2000.01.01',\n '2010.01.01') == []\n assert L.activities_in_interval_alphabetically('2016.01.01',\n '2017.01.01') == [a2]\n assert L.activities_in_interval_alphabetically('2015.12.21',\n '2015.12.21') == [a3]\n\n def test_activities_in_interval_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\n ) == [a4, a1, a3]\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\n ) == []\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\n ) == [a2]\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\n ) == [a3]\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, 'John', '1', 'A')\n self.q = Person(2, 'Mary', '1', 'B')\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n\n def test_activities_for_person_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_by_date(1) == [a1, a2]\n assert L.activities_for_person_by_date(2) == [a4, a3]\n assert L.activities_for_person_by_date(4) == []\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_alphabetically('2015.12.20',\n '2016.01.01') == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically('2000.01.01',\n '2010.01.01') == []\n assert L.activities_in_interval_alphabetically('2016.01.01',\n '2017.01.01') == [a2]\n assert L.activities_in_interval_alphabetically('2015.12.21',\n '2015.12.21') == [a3]\n\n def test_activities_in_interval_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\n ) == [a4, a1, a3]\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\n ) == []\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\n ) == [a2]\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\n ) == [a3]\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, 'John', '1', 'A')\n self.q = Person(2, 'Mary', '1', 'B')\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n <function token>\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_alphabetically('2015.12.20',\n '2016.01.01') == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically('2000.01.01',\n '2010.01.01') == []\n assert L.activities_in_interval_alphabetically('2016.01.01',\n '2017.01.01') == [a2]\n assert L.activities_in_interval_alphabetically('2015.12.21',\n '2015.12.21') == [a3]\n\n def test_activities_in_interval_by_date(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\n ) == [a4, a1, a3]\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\n ) == []\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\n ) == [a2]\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\n ) == [a3]\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, 'John', '1', 'A')\n self.q = Person(2, 'Mary', '1', 'B')\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n <function token>\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n\n def test_activities_in_interval_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_in_interval_alphabetically('2015.12.20',\n '2016.01.01') == [a4, a1, a3]\n assert L.activities_in_interval_alphabetically('2000.01.01',\n '2010.01.01') == []\n assert L.activities_in_interval_alphabetically('2016.01.01',\n '2017.01.01') == [a2]\n assert L.activities_in_interval_alphabetically('2015.12.21',\n '2015.12.21') == [a3]\n <function token>\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n\n def setUp(self):\n pR = PersonRepository()\n aR = ActivityRepository()\n self.L = StatsController(pR, aR)\n self.p = Person(1, 'John', '1', 'A')\n self.q = Person(2, 'Mary', '1', 'B')\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\n pR.add(self.p)\n pR.add(self.q)\n aR.add(self.a1)\n aR.add(self.a2)\n aR.add(self.a3)\n aR.add(self.a4)\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n <function token>\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n <function token>\n <function token>\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n <function token>\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n <function token>\n\n def test_people_with_activities_in_interval(self):\n L = self.L\n p = self.p\n q = self.q\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\n ) == [p, q]\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\n ) == []\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\n ) == [p]\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\n ) == [q]\n <function token>\n <function token>\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n <function token>\n\n def test_activities_for_person_alphabetically(self):\n L = self.L\n a1 = self.a1\n a2 = self.a2\n a3 = self.a3\n a4 = self.a4\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\n assert L.activities_for_person_alphabetically(4) == []\n <function token>\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass StatsControllerTestCase(unittest.TestCase):\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n","<import token>\n<class token>\n"],"string":"[\n \"import unittest\\nfrom domain.Activity import Activity\\nfrom domain.NABException import NABException\\nfrom domain.Person import Person\\nfrom domain.ActivityValidator import ActivityValidator\\nfrom repository.PersonRepository import PersonRepository\\nfrom repository.PersonFileRepository import PersonFileRepository\\nfrom repository.ActivityRepository import ActivityRepository\\nfrom repository.ActivityFileRepository import ActivityFileRepository\\nfrom controller.StatsController import StatsController\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, \\\"John\\\", \\\"1\\\", \\\"A\\\")\\n self.q = Person(2, \\\"Mary\\\", \\\"1\\\", \\\"B\\\")\\n self.a1 = Activity(self.p, \\\"2015.12.20\\\", \\\"12:12\\\", \\\"Swimming\\\")\\n self.a2 = Activity(self.p, \\\"2016.01.20\\\", \\\"12:12\\\", \\\"Mapping\\\")\\n self.a3 = Activity(self.q, \\\"2015.12.21\\\", \\\"12:12\\\", \\\"Swimming\\\")\\n self.a4 = Activity(self.q, \\\"2015.12.20\\\", \\\"10:12\\\", \\\"Reading\\\")\\n\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n\\n\\n def test_activities_for_person_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n\\n assert L.activities_for_person_by_date(1) == [a1, a2]\\n assert L.activities_for_person_by_date(2) == [a4, a3]\\n assert L.activities_for_person_by_date(4) == []\\n\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n\\n assert L.people_with_activities_in_interval(\\\"2015.12.20\\\", \\\"2016.01.01\\\") == [p, q]\\n assert L.people_with_activities_in_interval(\\\"2000.01.01\\\", \\\"2010.01.01\\\") == []\\n assert L.people_with_activities_in_interval(\\\"2016.01.01\\\", \\\"2017.01.01\\\") == [p]\\n assert L.people_with_activities_in_interval(\\\"2015.12.21\\\", \\\"2015.12.21\\\") == [q]\\n\\n\\n def test_activities_in_interval_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n\\n assert L.activities_in_interval_alphabetically(\\\"2015.12.20\\\", \\\"2016.01.01\\\") == [a4, a1, a3]\\n assert L.activities_in_interval_alphabetically(\\\"2000.01.01\\\", \\\"2010.01.01\\\") == []\\n assert L.activities_in_interval_alphabetically(\\\"2016.01.01\\\", \\\"2017.01.01\\\") == [a2]\\n assert L.activities_in_interval_alphabetically(\\\"2015.12.21\\\", \\\"2015.12.21\\\") == [a3]\\n\\n\\n def test_activities_in_interval_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n\\n assert L.activities_in_interval_by_date(\\\"2015.12.20\\\", \\\"2016.01.01\\\") == [a4, a1, a3]\\n assert L.activities_in_interval_by_date(\\\"2000.01.01\\\", \\\"2010.01.01\\\") == []\\n assert L.activities_in_interval_by_date(\\\"2016.01.01\\\", \\\"2017.01.01\\\") == [a2]\\n assert L.activities_in_interval_by_date(\\\"2015.12.21\\\", \\\"2015.12.21\\\") == [a3]\",\n \"import unittest\\nfrom domain.Activity import Activity\\nfrom domain.NABException import NABException\\nfrom domain.Person import Person\\nfrom domain.ActivityValidator import ActivityValidator\\nfrom repository.PersonRepository import PersonRepository\\nfrom repository.PersonFileRepository import PersonFileRepository\\nfrom repository.ActivityRepository import ActivityRepository\\nfrom repository.ActivityFileRepository import ActivityFileRepository\\nfrom controller.StatsController import StatsController\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, 'John', '1', 'A')\\n self.q = Person(2, 'Mary', '1', 'B')\\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n\\n def test_activities_for_person_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_by_date(1) == [a1, a2]\\n assert L.activities_for_person_by_date(2) == [a4, a3]\\n assert L.activities_for_person_by_date(4) == []\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n\\n def test_activities_in_interval_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_alphabetically('2015.12.20',\\n '2016.01.01') == [a4, a1, a3]\\n assert L.activities_in_interval_alphabetically('2000.01.01',\\n '2010.01.01') == []\\n assert L.activities_in_interval_alphabetically('2016.01.01',\\n '2017.01.01') == [a2]\\n assert L.activities_in_interval_alphabetically('2015.12.21',\\n '2015.12.21') == [a3]\\n\\n def test_activities_in_interval_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\\n ) == [a4, a1, a3]\\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\\n ) == [a2]\\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\\n ) == [a3]\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, 'John', '1', 'A')\\n self.q = Person(2, 'Mary', '1', 'B')\\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n\\n def test_activities_for_person_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_by_date(1) == [a1, a2]\\n assert L.activities_for_person_by_date(2) == [a4, a3]\\n assert L.activities_for_person_by_date(4) == []\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n\\n def test_activities_in_interval_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_alphabetically('2015.12.20',\\n '2016.01.01') == [a4, a1, a3]\\n assert L.activities_in_interval_alphabetically('2000.01.01',\\n '2010.01.01') == []\\n assert L.activities_in_interval_alphabetically('2016.01.01',\\n '2017.01.01') == [a2]\\n assert L.activities_in_interval_alphabetically('2015.12.21',\\n '2015.12.21') == [a3]\\n\\n def test_activities_in_interval_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\\n ) == [a4, a1, a3]\\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\\n ) == [a2]\\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\\n ) == [a3]\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, 'John', '1', 'A')\\n self.q = Person(2, 'Mary', '1', 'B')\\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n <function token>\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n\\n def test_activities_in_interval_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_alphabetically('2015.12.20',\\n '2016.01.01') == [a4, a1, a3]\\n assert L.activities_in_interval_alphabetically('2000.01.01',\\n '2010.01.01') == []\\n assert L.activities_in_interval_alphabetically('2016.01.01',\\n '2017.01.01') == [a2]\\n assert L.activities_in_interval_alphabetically('2015.12.21',\\n '2015.12.21') == [a3]\\n\\n def test_activities_in_interval_by_date(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_by_date('2015.12.20', '2016.01.01'\\n ) == [a4, a1, a3]\\n assert L.activities_in_interval_by_date('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.activities_in_interval_by_date('2016.01.01', '2017.01.01'\\n ) == [a2]\\n assert L.activities_in_interval_by_date('2015.12.21', '2015.12.21'\\n ) == [a3]\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, 'John', '1', 'A')\\n self.q = Person(2, 'Mary', '1', 'B')\\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n <function token>\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n\\n def test_activities_in_interval_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_in_interval_alphabetically('2015.12.20',\\n '2016.01.01') == [a4, a1, a3]\\n assert L.activities_in_interval_alphabetically('2000.01.01',\\n '2010.01.01') == []\\n assert L.activities_in_interval_alphabetically('2016.01.01',\\n '2017.01.01') == [a2]\\n assert L.activities_in_interval_alphabetically('2015.12.21',\\n '2015.12.21') == [a3]\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n\\n def setUp(self):\\n pR = PersonRepository()\\n aR = ActivityRepository()\\n self.L = StatsController(pR, aR)\\n self.p = Person(1, 'John', '1', 'A')\\n self.q = Person(2, 'Mary', '1', 'B')\\n self.a1 = Activity(self.p, '2015.12.20', '12:12', 'Swimming')\\n self.a2 = Activity(self.p, '2016.01.20', '12:12', 'Mapping')\\n self.a3 = Activity(self.q, '2015.12.21', '12:12', 'Swimming')\\n self.a4 = Activity(self.q, '2015.12.20', '10:12', 'Reading')\\n pR.add(self.p)\\n pR.add(self.q)\\n aR.add(self.a1)\\n aR.add(self.a2)\\n aR.add(self.a3)\\n aR.add(self.a4)\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n <function token>\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n <function token>\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n <function token>\\n\\n def test_people_with_activities_in_interval(self):\\n L = self.L\\n p = self.p\\n q = self.q\\n assert L.people_with_activities_in_interval('2015.12.20', '2016.01.01'\\n ) == [p, q]\\n assert L.people_with_activities_in_interval('2000.01.01', '2010.01.01'\\n ) == []\\n assert L.people_with_activities_in_interval('2016.01.01', '2017.01.01'\\n ) == [p]\\n assert L.people_with_activities_in_interval('2015.12.21', '2015.12.21'\\n ) == [q]\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n <function token>\\n\\n def test_activities_for_person_alphabetically(self):\\n L = self.L\\n a1 = self.a1\\n a2 = self.a2\\n a3 = self.a3\\n a4 = self.a4\\n assert L.activities_for_person_alphabetically(1) == [a2, a1]\\n assert L.activities_for_person_alphabetically(2) == [a4, a3]\\n assert L.activities_for_person_alphabetically(4) == []\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass StatsControllerTestCase(unittest.TestCase):\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8683,"cells":{"index":{"kind":"number","value":8683,"string":"8,683"},"blob_id":{"kind":"string","value":"e7d63c3b56459297eb67c56e93a3c640d93e5f6d"},"code":{"kind":"string","value":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport tensorflow\nfrom pyspark.sql.functions import split\nfrom pyspark.ml.fpm import FPGrowth\nfrom pyspark.sql import SparkSession\nfrom pyspark import SparkConf\nfrom pyspark.sql.functions import udf, array\nimport re\nfrom pyspark.sql.types import *\nimport pyspark.sql.functions as F\nprice_pattern = re.compile(r'^\\d+\\.\\d\\d$')\nmyconf = SparkConf()\nmyconf.setAppName(\"test\").setMaster(\"local[40]\")\nmyconf.set('spark.executor.instances','40')\nmyconf.set('spark.driver.memory','6G')\n#myconf.set('spark.executor.memory','1G')\nmyconf.set('spark.executor.cores','40')\nmyconf.set('spark.task.cpus','40')\n\n# 指定连接器对应的spark-package\nmyconf.set(\"spark.jars.packages\",\"org.mongodb.spark:mongo-spark-connector_2.11:2.4.1\")\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\nlogger = spark._jvm.org.apache.log4j\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\n\nfilter_hosts=[\"vivo\",\"google.com\",\"google.cn\",\"oppomobile\",\"baidu.com\",\"hicloud\"]\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\ncontains_hosts=[\"jd.com\"]\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\ndf=spark.read.format(\"mongo\").option(\"uri\",\"mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420\").option(\"spark.mongodb.input.partitioner\",\"MongoSplitVectorPartitioner\").load()\ndf=df.filter(filter_host('host')).select(['app_id','host','session_id'])\n\nhosts=df.select(['host']).distinct().rdd.map(lambda r : r['host']).collect()\nhosts.sort()\n\ndf1=df.groupBy('app_id','session_id') \\\n .pivot('host', hosts) \\\n .agg(F.count('host')).fillna(0)\ndf2=df1.toPandas()\ndf2.to_csv(\"tf22.csv\")"},"steps":{"kind":"list like","value":["#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport tensorflow\nfrom pyspark.sql.functions import split\nfrom pyspark.ml.fpm import FPGrowth\nfrom pyspark.sql import SparkSession\nfrom pyspark import SparkConf\nfrom pyspark.sql.functions import udf, array\nimport re\nfrom pyspark.sql.types import *\nimport pyspark.sql.functions as F\nprice_pattern = re.compile(r'^\\d+\\.\\d\\d$')\nmyconf = SparkConf()\nmyconf.setAppName(\"test\").setMaster(\"local[40]\")\nmyconf.set('spark.executor.instances','40')\nmyconf.set('spark.driver.memory','6G')\n#myconf.set('spark.executor.memory','1G')\nmyconf.set('spark.executor.cores','40')\nmyconf.set('spark.task.cpus','40')\n\n# 指定连接器对应的spark-package\nmyconf.set(\"spark.jars.packages\",\"org.mongodb.spark:mongo-spark-connector_2.11:2.4.1\")\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\nlogger = spark._jvm.org.apache.log4j\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\n\nfilter_hosts=[\"vivo\",\"google.com\",\"google.cn\",\"oppomobile\",\"baidu.com\",\"hicloud\"]\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\ncontains_hosts=[\"jd.com\"]\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\ndf=spark.read.format(\"mongo\").option(\"uri\",\"mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420\").option(\"spark.mongodb.input.partitioner\",\"MongoSplitVectorPartitioner\").load()\ndf=df.filter(filter_host('host')).select(['app_id','host','session_id'])\n\nhosts=df.select(['host']).distinct().rdd.map(lambda r : r['host']).collect()\nhosts.sort()\n\ndf1=df.groupBy('app_id','session_id') \\\n .pivot('host', hosts) \\\n .agg(F.count('host')).fillna(0)\ndf2=df1.toPandas()\ndf2.to_csv(\"tf22.csv\")","import tensorflow\nfrom pyspark.sql.functions import split\nfrom pyspark.ml.fpm import FPGrowth\nfrom pyspark.sql import SparkSession\nfrom pyspark import SparkConf\nfrom pyspark.sql.functions import udf, array\nimport re\nfrom pyspark.sql.types import *\nimport pyspark.sql.functions as F\nprice_pattern = re.compile('^\\\\d+\\\\.\\\\d\\\\d$')\nmyconf = SparkConf()\nmyconf.setAppName('test').setMaster('local[40]')\nmyconf.set('spark.executor.instances', '40')\nmyconf.set('spark.driver.memory', '6G')\nmyconf.set('spark.executor.cores', '40')\nmyconf.set('spark.task.cpus', '40')\nmyconf.set('spark.jars.packages',\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\nlogger = spark._jvm.org.apache.log4j\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\nfilter_hosts = ['vivo', 'google.com', 'google.cn', 'oppomobile',\n 'baidu.com', 'hicloud']\n\n\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\n\ncontains_hosts = ['jd.com']\n\n\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\n\ndf = spark.read.format('mongo').option('uri',\n 'mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420').option(\n 'spark.mongodb.input.partitioner', 'MongoSplitVectorPartitioner').load()\ndf = df.filter(filter_host('host')).select(['app_id', 'host', 'session_id'])\nhosts = df.select(['host']).distinct().rdd.map(lambda r: r['host']).collect()\nhosts.sort()\ndf1 = df.groupBy('app_id', 'session_id').pivot('host', hosts).agg(F.count(\n 'host')).fillna(0)\ndf2 = df1.toPandas()\ndf2.to_csv('tf22.csv')\n","<import token>\nprice_pattern = re.compile('^\\\\d+\\\\.\\\\d\\\\d$')\nmyconf = SparkConf()\nmyconf.setAppName('test').setMaster('local[40]')\nmyconf.set('spark.executor.instances', '40')\nmyconf.set('spark.driver.memory', '6G')\nmyconf.set('spark.executor.cores', '40')\nmyconf.set('spark.task.cpus', '40')\nmyconf.set('spark.jars.packages',\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\nlogger = spark._jvm.org.apache.log4j\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\nfilter_hosts = ['vivo', 'google.com', 'google.cn', 'oppomobile',\n 'baidu.com', 'hicloud']\n\n\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\n\ncontains_hosts = ['jd.com']\n\n\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\n\ndf = spark.read.format('mongo').option('uri',\n 'mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420').option(\n 'spark.mongodb.input.partitioner', 'MongoSplitVectorPartitioner').load()\ndf = df.filter(filter_host('host')).select(['app_id', 'host', 'session_id'])\nhosts = df.select(['host']).distinct().rdd.map(lambda r: r['host']).collect()\nhosts.sort()\ndf1 = df.groupBy('app_id', 'session_id').pivot('host', hosts).agg(F.count(\n 'host')).fillna(0)\ndf2 = df1.toPandas()\ndf2.to_csv('tf22.csv')\n","<import token>\n<assignment token>\nmyconf.setAppName('test').setMaster('local[40]')\nmyconf.set('spark.executor.instances', '40')\nmyconf.set('spark.driver.memory', '6G')\nmyconf.set('spark.executor.cores', '40')\nmyconf.set('spark.task.cpus', '40')\nmyconf.set('spark.jars.packages',\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\n<assignment token>\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\n<assignment token>\n\n\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\n\n<assignment token>\n\n\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\n\n<assignment token>\nhosts.sort()\n<assignment token>\ndf2.to_csv('tf22.csv')\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n\n\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\n\n<assignment token>\n\n\n@udf(returnType=BooleanType())\ndef contains_host(item):\n for i in contains_hosts:\n if item.find(i) != -1:\n return True\n return False\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n\n\n@udf(returnType=BooleanType())\ndef filter_host(item):\n for i in filter_hosts:\n if item.find(i) != -1:\n return False\n return True\n\n\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<function token>\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n"],"string":"[\n \"#!/usr/bin/env python3\\n# -*- coding: utf-8 -*-\\nimport tensorflow\\nfrom pyspark.sql.functions import split\\nfrom pyspark.ml.fpm import FPGrowth\\nfrom pyspark.sql import SparkSession\\nfrom pyspark import SparkConf\\nfrom pyspark.sql.functions import udf, array\\nimport re\\nfrom pyspark.sql.types import *\\nimport pyspark.sql.functions as F\\nprice_pattern = re.compile(r'^\\\\d+\\\\.\\\\d\\\\d$')\\nmyconf = SparkConf()\\nmyconf.setAppName(\\\"test\\\").setMaster(\\\"local[40]\\\")\\nmyconf.set('spark.executor.instances','40')\\nmyconf.set('spark.driver.memory','6G')\\n#myconf.set('spark.executor.memory','1G')\\nmyconf.set('spark.executor.cores','40')\\nmyconf.set('spark.task.cpus','40')\\n\\n# 指定连接器对应的spark-package\\nmyconf.set(\\\"spark.jars.packages\\\",\\\"org.mongodb.spark:mongo-spark-connector_2.11:2.4.1\\\")\\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\\nlogger = spark._jvm.org.apache.log4j\\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\\n\\nfilter_hosts=[\\\"vivo\\\",\\\"google.com\\\",\\\"google.cn\\\",\\\"oppomobile\\\",\\\"baidu.com\\\",\\\"hicloud\\\"]\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\ncontains_hosts=[\\\"jd.com\\\"]\\n@udf(returnType=BooleanType())\\ndef contains_host(item):\\n for i in contains_hosts:\\n if item.find(i) != -1:\\n return True\\n return False\\n\\ndf=spark.read.format(\\\"mongo\\\").option(\\\"uri\\\",\\\"mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420\\\").option(\\\"spark.mongodb.input.partitioner\\\",\\\"MongoSplitVectorPartitioner\\\").load()\\ndf=df.filter(filter_host('host')).select(['app_id','host','session_id'])\\n\\nhosts=df.select(['host']).distinct().rdd.map(lambda r : r['host']).collect()\\nhosts.sort()\\n\\ndf1=df.groupBy('app_id','session_id') \\\\\\n .pivot('host', hosts) \\\\\\n .agg(F.count('host')).fillna(0)\\ndf2=df1.toPandas()\\ndf2.to_csv(\\\"tf22.csv\\\")\",\n \"import tensorflow\\nfrom pyspark.sql.functions import split\\nfrom pyspark.ml.fpm import FPGrowth\\nfrom pyspark.sql import SparkSession\\nfrom pyspark import SparkConf\\nfrom pyspark.sql.functions import udf, array\\nimport re\\nfrom pyspark.sql.types import *\\nimport pyspark.sql.functions as F\\nprice_pattern = re.compile('^\\\\\\\\d+\\\\\\\\.\\\\\\\\d\\\\\\\\d$')\\nmyconf = SparkConf()\\nmyconf.setAppName('test').setMaster('local[40]')\\nmyconf.set('spark.executor.instances', '40')\\nmyconf.set('spark.driver.memory', '6G')\\nmyconf.set('spark.executor.cores', '40')\\nmyconf.set('spark.task.cpus', '40')\\nmyconf.set('spark.jars.packages',\\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\\nlogger = spark._jvm.org.apache.log4j\\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\\nfilter_hosts = ['vivo', 'google.com', 'google.cn', 'oppomobile',\\n 'baidu.com', 'hicloud']\\n\\n\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\n\\ncontains_hosts = ['jd.com']\\n\\n\\n@udf(returnType=BooleanType())\\ndef contains_host(item):\\n for i in contains_hosts:\\n if item.find(i) != -1:\\n return True\\n return False\\n\\n\\ndf = spark.read.format('mongo').option('uri',\\n 'mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420').option(\\n 'spark.mongodb.input.partitioner', 'MongoSplitVectorPartitioner').load()\\ndf = df.filter(filter_host('host')).select(['app_id', 'host', 'session_id'])\\nhosts = df.select(['host']).distinct().rdd.map(lambda r: r['host']).collect()\\nhosts.sort()\\ndf1 = df.groupBy('app_id', 'session_id').pivot('host', hosts).agg(F.count(\\n 'host')).fillna(0)\\ndf2 = df1.toPandas()\\ndf2.to_csv('tf22.csv')\\n\",\n \"<import token>\\nprice_pattern = re.compile('^\\\\\\\\d+\\\\\\\\.\\\\\\\\d\\\\\\\\d$')\\nmyconf = SparkConf()\\nmyconf.setAppName('test').setMaster('local[40]')\\nmyconf.set('spark.executor.instances', '40')\\nmyconf.set('spark.driver.memory', '6G')\\nmyconf.set('spark.executor.cores', '40')\\nmyconf.set('spark.task.cpus', '40')\\nmyconf.set('spark.jars.packages',\\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\\nspark = SparkSession.builder.config(conf=myconf).getOrCreate()\\nlogger = spark._jvm.org.apache.log4j\\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\\nfilter_hosts = ['vivo', 'google.com', 'google.cn', 'oppomobile',\\n 'baidu.com', 'hicloud']\\n\\n\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\n\\ncontains_hosts = ['jd.com']\\n\\n\\n@udf(returnType=BooleanType())\\ndef contains_host(item):\\n for i in contains_hosts:\\n if item.find(i) != -1:\\n return True\\n return False\\n\\n\\ndf = spark.read.format('mongo').option('uri',\\n 'mongodb://192.168.0.13:27017/jicheng.autopkgcatpure20210420').option(\\n 'spark.mongodb.input.partitioner', 'MongoSplitVectorPartitioner').load()\\ndf = df.filter(filter_host('host')).select(['app_id', 'host', 'session_id'])\\nhosts = df.select(['host']).distinct().rdd.map(lambda r: r['host']).collect()\\nhosts.sort()\\ndf1 = df.groupBy('app_id', 'session_id').pivot('host', hosts).agg(F.count(\\n 'host')).fillna(0)\\ndf2 = df1.toPandas()\\ndf2.to_csv('tf22.csv')\\n\",\n \"<import token>\\n<assignment token>\\nmyconf.setAppName('test').setMaster('local[40]')\\nmyconf.set('spark.executor.instances', '40')\\nmyconf.set('spark.driver.memory', '6G')\\nmyconf.set('spark.executor.cores', '40')\\nmyconf.set('spark.task.cpus', '40')\\nmyconf.set('spark.jars.packages',\\n 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.1')\\n<assignment token>\\nlogger.LogManager.getRootLogger().setLevel(logger.Level.FATAL)\\n<assignment token>\\n\\n\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\n\\n<assignment token>\\n\\n\\n@udf(returnType=BooleanType())\\ndef contains_host(item):\\n for i in contains_hosts:\\n if item.find(i) != -1:\\n return True\\n return False\\n\\n\\n<assignment token>\\nhosts.sort()\\n<assignment token>\\ndf2.to_csv('tf22.csv')\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\n\\n<assignment token>\\n\\n\\n@udf(returnType=BooleanType())\\ndef contains_host(item):\\n for i in contains_hosts:\\n if item.find(i) != -1:\\n return True\\n return False\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\\n\\n@udf(returnType=BooleanType())\\ndef filter_host(item):\\n for i in filter_hosts:\\n if item.find(i) != -1:\\n return False\\n return True\\n\\n\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8684,"cells":{"index":{"kind":"number","value":8684,"string":"8,684"},"blob_id":{"kind":"string","value":"e403be68894ba283d71a0b71bb0bfd0adfab8c41"},"code":{"kind":"string","value":"import logging\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method(\"%d %s %s (%s) %s %s %.2fms\",\n handler.get_status(), handler.request.method,\n handler.request.uri, handler.request.remote_ip,\n handler.request.arguments,\n request_time)\n\n\nconfigs = dict(\n LOG_LEVEL=logging.INFO, # 日志等级\n debug=True, # Debug\n log_function=log_func, # 日志处理方法\n template_path='views', # html文件\n static_path='statics', # 静态文件（css,js,img）\n static_url_prefix='/statics/', # 静态文件前缀\n cookie_secret='suoning', # cookie自定义字符串加盐\n xsrf_cookies=True, # 防止跨站伪造\n)\n"},"steps":{"kind":"list like","value":["import logging\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method(\"%d %s %s (%s) %s %s %.2fms\",\n handler.get_status(), handler.request.method,\n handler.request.uri, handler.request.remote_ip,\n handler.request.arguments,\n request_time)\n\n\nconfigs = dict(\n LOG_LEVEL=logging.INFO, # 日志等级\n debug=True, # Debug\n log_function=log_func, # 日志处理方法\n template_path='views', # html文件\n static_path='statics', # 静态文件（css,js,img）\n static_url_prefix='/statics/', # 静态文件前缀\n cookie_secret='suoning', # cookie自定义字符串加盐\n xsrf_cookies=True, # 防止跨站伪造\n)\n","import logging\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\n request.method, handler.request.uri, handler.request.remote_ip,\n handler.request.arguments, request_time)\n\n\nconfigs = dict(LOG_LEVEL=logging.INFO, debug=True, log_function=log_func,\n template_path='views', static_path='statics', static_url_prefix=\n '/statics/', cookie_secret='suoning', xsrf_cookies=True)\n","<import token>\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\n request.method, handler.request.uri, handler.request.remote_ip,\n handler.request.arguments, request_time)\n\n\nconfigs = dict(LOG_LEVEL=logging.INFO, debug=True, log_function=log_func,\n template_path='views', static_path='statics', static_url_prefix=\n '/statics/', cookie_secret='suoning', xsrf_cookies=True)\n","<import token>\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\n request.method, handler.request.uri, handler.request.remote_ip,\n handler.request.arguments, request_time)\n\n\n<assignment token>\n","<import token>\n<function token>\n<assignment token>\n"],"string":"[\n \"import logging\\n\\n\\ndef log_func(handler):\\n if handler.get_status() < 400:\\n log_method = logging.info\\n elif handler.get_status() < 500:\\n log_method = logging.warning\\n else:\\n log_method = logging.error\\n request_time = 1000.0 * handler.request.request_time()\\n log_method(\\\"%d %s %s (%s) %s %s %.2fms\\\",\\n handler.get_status(), handler.request.method,\\n handler.request.uri, handler.request.remote_ip,\\n handler.request.arguments,\\n request_time)\\n\\n\\nconfigs = dict(\\n LOG_LEVEL=logging.INFO, # 日志等级\\n debug=True, # Debug\\n log_function=log_func, # 日志处理方法\\n template_path='views', # html文件\\n static_path='statics', # 静态文件（css,js,img）\\n static_url_prefix='/statics/', # 静态文件前缀\\n cookie_secret='suoning', # cookie自定义字符串加盐\\n xsrf_cookies=True, # 防止跨站伪造\\n)\\n\",\n \"import logging\\n\\n\\ndef log_func(handler):\\n if handler.get_status() < 400:\\n log_method = logging.info\\n elif handler.get_status() < 500:\\n log_method = logging.warning\\n else:\\n log_method = logging.error\\n request_time = 1000.0 * handler.request.request_time()\\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\\n request.method, handler.request.uri, handler.request.remote_ip,\\n handler.request.arguments, request_time)\\n\\n\\nconfigs = dict(LOG_LEVEL=logging.INFO, debug=True, log_function=log_func,\\n template_path='views', static_path='statics', static_url_prefix=\\n '/statics/', cookie_secret='suoning', xsrf_cookies=True)\\n\",\n \"<import token>\\n\\n\\ndef log_func(handler):\\n if handler.get_status() < 400:\\n log_method = logging.info\\n elif handler.get_status() < 500:\\n log_method = logging.warning\\n else:\\n log_method = logging.error\\n request_time = 1000.0 * handler.request.request_time()\\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\\n request.method, handler.request.uri, handler.request.remote_ip,\\n handler.request.arguments, request_time)\\n\\n\\nconfigs = dict(LOG_LEVEL=logging.INFO, debug=True, log_function=log_func,\\n template_path='views', static_path='statics', static_url_prefix=\\n '/statics/', cookie_secret='suoning', xsrf_cookies=True)\\n\",\n \"<import token>\\n\\n\\ndef log_func(handler):\\n if handler.get_status() < 400:\\n log_method = logging.info\\n elif handler.get_status() < 500:\\n log_method = logging.warning\\n else:\\n log_method = logging.error\\n request_time = 1000.0 * handler.request.request_time()\\n log_method('%d %s %s (%s) %s %s %.2fms', handler.get_status(), handler.\\n request.method, handler.request.uri, handler.request.remote_ip,\\n handler.request.arguments, request_time)\\n\\n\\n<assignment token>\\n\",\n \"<import token>\\n<function token>\\n<assignment token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8685,"cells":{"index":{"kind":"number","value":8685,"string":"8,685"},"blob_id":{"kind":"string","value":"5c179752f4c4e1d693346c6edddd79211a895735"},"code":{"kind":"string","value":"valor1=input(\"Ingrese Primera Cantidad \")\nvalor2=input(\"Ingrese Segunda Cantidad \")\nTotal = valor1 + valor2\nprint \"El total es: \" + str(Total)\n"},"steps":{"kind":"list like","value":["valor1=input(\"Ingrese Primera Cantidad \")\nvalor2=input(\"Ingrese Segunda Cantidad \")\nTotal = valor1 + valor2\nprint \"El total es: \" + str(Total)\n"],"string":"[\n \"valor1=input(\\\"Ingrese Primera Cantidad \\\")\\nvalor2=input(\\\"Ingrese Segunda Cantidad \\\")\\nTotal = valor1 + valor2\\nprint \\\"El total es: \\\" + str(Total)\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":true,"string":"true"}}},{"rowIdx":8686,"cells":{"index":{"kind":"number","value":8686,"string":"8,686"},"blob_id":{"kind":"string","value":"ec2d3bbfce06c498790afd491931df3f391dafbe"},"code":{"kind":"string","value":"../PyFoam/bin/pyFoamPlotWatcher.py"},"steps":{"kind":"list like","value":["../PyFoam/bin/pyFoamPlotWatcher.py"],"string":"[\n \"../PyFoam/bin/pyFoamPlotWatcher.py\"\n]","isConversational":false},"error":{"kind":"bool","value":true,"string":"true"}}},{"rowIdx":8687,"cells":{"index":{"kind":"number","value":8687,"string":"8,687"},"blob_id":{"kind":"string","value":"022f588455d8624d0b0107180417f65816254cb1"},"code":{"kind":"string","value":"class car:\r\n\r\n def info(self):\r\n print(self.speed,self. color,self.model)\r\n def increment(self):\r\n print('increment')\r\n def decrement(self):\r\n print ('decrement')\r\n\r\nBMW = car()\r\nBMW.speed = 320\r\nBMW.color = 'red'\r\nBMW.model = 1982\r\nBMW.info()\r\n\r\nCamry = car()\r\nCamry.speed = 220\r\nCamry.color = 'blue'\r\n\r\n\r\n\r\n"},"steps":{"kind":"list like","value":["class car:\r\n\r\n def info(self):\r\n print(self.speed,self. color,self.model)\r\n def increment(self):\r\n print('increment')\r\n def decrement(self):\r\n print ('decrement')\r\n\r\nBMW = car()\r\nBMW.speed = 320\r\nBMW.color = 'red'\r\nBMW.model = 1982\r\nBMW.info()\r\n\r\nCamry = car()\r\nCamry.speed = 220\r\nCamry.color = 'blue'\r\n\r\n\r\n\r\n","class car:\n\n def info(self):\n print(self.speed, self.color, self.model)\n\n def increment(self):\n print('increment')\n\n def decrement(self):\n print('decrement')\n\n\nBMW = car()\nBMW.speed = 320\nBMW.color = 'red'\nBMW.model = 1982\nBMW.info()\nCamry = car()\nCamry.speed = 220\nCamry.color = 'blue'\n","class car:\n\n def info(self):\n print(self.speed, self.color, self.model)\n\n def increment(self):\n print('increment')\n\n def decrement(self):\n print('decrement')\n\n\n<assignment token>\nBMW.info()\n<assignment token>\n","class car:\n\n def info(self):\n print(self.speed, self.color, self.model)\n\n def increment(self):\n print('increment')\n\n def decrement(self):\n print('decrement')\n\n\n<assignment token>\n<code token>\n<assignment token>\n","class car:\n\n def info(self):\n print(self.speed, self.color, self.model)\n\n def increment(self):\n print('increment')\n <function token>\n\n\n<assignment token>\n<code token>\n<assignment token>\n","class car:\n\n def info(self):\n print(self.speed, self.color, self.model)\n <function token>\n <function token>\n\n\n<assignment token>\n<code token>\n<assignment token>\n","class car:\n <function token>\n <function token>\n <function token>\n\n\n<assignment token>\n<code token>\n<assignment token>\n","<class token>\n<assignment token>\n<code token>\n<assignment token>\n"],"string":"[\n \"class car:\\r\\n\\r\\n def info(self):\\r\\n print(self.speed,self. color,self.model)\\r\\n def increment(self):\\r\\n print('increment')\\r\\n def decrement(self):\\r\\n print ('decrement')\\r\\n\\r\\nBMW = car()\\r\\nBMW.speed = 320\\r\\nBMW.color = 'red'\\r\\nBMW.model = 1982\\r\\nBMW.info()\\r\\n\\r\\nCamry = car()\\r\\nCamry.speed = 220\\r\\nCamry.color = 'blue'\\r\\n\\r\\n\\r\\n\\r\\n\",\n \"class car:\\n\\n def info(self):\\n print(self.speed, self.color, self.model)\\n\\n def increment(self):\\n print('increment')\\n\\n def decrement(self):\\n print('decrement')\\n\\n\\nBMW = car()\\nBMW.speed = 320\\nBMW.color = 'red'\\nBMW.model = 1982\\nBMW.info()\\nCamry = car()\\nCamry.speed = 220\\nCamry.color = 'blue'\\n\",\n \"class car:\\n\\n def info(self):\\n print(self.speed, self.color, self.model)\\n\\n def increment(self):\\n print('increment')\\n\\n def decrement(self):\\n print('decrement')\\n\\n\\n<assignment token>\\nBMW.info()\\n<assignment token>\\n\",\n \"class car:\\n\\n def info(self):\\n print(self.speed, self.color, self.model)\\n\\n def increment(self):\\n print('increment')\\n\\n def decrement(self):\\n print('decrement')\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n\",\n \"class car:\\n\\n def info(self):\\n print(self.speed, self.color, self.model)\\n\\n def increment(self):\\n print('increment')\\n <function token>\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n\",\n \"class car:\\n\\n def info(self):\\n print(self.speed, self.color, self.model)\\n <function token>\\n <function token>\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n\",\n \"class car:\\n <function token>\\n <function token>\\n <function token>\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n\",\n \"<class token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8688,"cells":{"index":{"kind":"number","value":8688,"string":"8,688"},"blob_id":{"kind":"string","value":"a494b3469682a909b76e67e1b78ad25affe99f24"},"code":{"kind":"string","value":"# Your code here\nd = dict()\ncount = 0\nfave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor i in range(1, 11):\n if fave_fast_food in d:\n d[fave_fast_food] += 1\n else:\n d[fave_fast_food] = 1\n count+= 1\n fave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor k,v in d.items():\n print('Fast Food Resturants that are ' + k + \": \" + str(v))\n\nmaximum = max(d, key=d.get) # Just use 'min' instead of 'max' for minimum.\nprint(\"The fast food restaurant \" + maximum + \" has this many votes:\", d[maximum])"},"steps":{"kind":"list like","value":["# Your code here\nd = dict()\ncount = 0\nfave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor i in range(1, 11):\n if fave_fast_food in d:\n d[fave_fast_food] += 1\n else:\n d[fave_fast_food] = 1\n count+= 1\n fave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor k,v in d.items():\n print('Fast Food Resturants that are ' + k + \": \" + str(v))\n\nmaximum = max(d, key=d.get) # Just use 'min' instead of 'max' for minimum.\nprint(\"The fast food restaurant \" + maximum + \" has this many votes:\", d[maximum])","d = dict()\ncount = 0\nfave_fast_food = input('Fave fast food restaurant: ')\nfor i in range(1, 11):\n if fave_fast_food in d:\n d[fave_fast_food] += 1\n else:\n d[fave_fast_food] = 1\n count += 1\n fave_fast_food = input('Fave fast food restaurant: ')\nfor k, v in d.items():\n print('Fast Food Resturants that are ' + k + ': ' + str(v))\nmaximum = max(d, key=d.get)\nprint('The fast food restaurant ' + maximum + ' has this many votes:', d[\n maximum])\n","<assignment token>\nfor i in range(1, 11):\n if fave_fast_food in d:\n d[fave_fast_food] += 1\n else:\n d[fave_fast_food] = 1\n count += 1\n fave_fast_food = input('Fave fast food restaurant: ')\nfor k, v in d.items():\n print('Fast Food Resturants that are ' + k + ': ' + str(v))\n<assignment token>\nprint('The fast food restaurant ' + maximum + ' has this many votes:', d[\n maximum])\n","<assignment token>\n<code token>\n<assignment token>\n<code token>\n"],"string":"[\n \"# Your code here\\nd = dict()\\ncount = 0\\nfave_fast_food = input(\\\"Fave fast food restaurant: \\\")\\n\\nfor i in range(1, 11):\\n if fave_fast_food in d:\\n d[fave_fast_food] += 1\\n else:\\n d[fave_fast_food] = 1\\n count+= 1\\n fave_fast_food = input(\\\"Fave fast food restaurant: \\\")\\n\\nfor k,v in d.items():\\n print('Fast Food Resturants that are ' + k + \\\": \\\" + str(v))\\n\\nmaximum = max(d, key=d.get) # Just use 'min' instead of 'max' for minimum.\\nprint(\\\"The fast food restaurant \\\" + maximum + \\\" has this many votes:\\\", d[maximum])\",\n \"d = dict()\\ncount = 0\\nfave_fast_food = input('Fave fast food restaurant: ')\\nfor i in range(1, 11):\\n if fave_fast_food in d:\\n d[fave_fast_food] += 1\\n else:\\n d[fave_fast_food] = 1\\n count += 1\\n fave_fast_food = input('Fave fast food restaurant: ')\\nfor k, v in d.items():\\n print('Fast Food Resturants that are ' + k + ': ' + str(v))\\nmaximum = max(d, key=d.get)\\nprint('The fast food restaurant ' + maximum + ' has this many votes:', d[\\n maximum])\\n\",\n \"<assignment token>\\nfor i in range(1, 11):\\n if fave_fast_food in d:\\n d[fave_fast_food] += 1\\n else:\\n d[fave_fast_food] = 1\\n count += 1\\n fave_fast_food = input('Fave fast food restaurant: ')\\nfor k, v in d.items():\\n print('Fast Food Resturants that are ' + k + ': ' + str(v))\\n<assignment token>\\nprint('The fast food restaurant ' + maximum + ' has this many votes:', d[\\n maximum])\\n\",\n \"<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8689,"cells":{"index":{"kind":"number","value":8689,"string":"8,689"},"blob_id":{"kind":"string","value":"a87ab07bb1502a75a7e705cd5c92db829ebdd966"},"code":{"kind":"string","value":"#!/usr/bin/python\r\n# -*- coding: utf-8 -*-\r\n\r\nimport json\r\n\r\nfrom flask import jsonify\r\nfrom flask import make_response\r\nfrom MultipleInterfaceManager.settings import STATUS_CODE\r\n\r\n\r\ndef _render(resp):\r\n response = make_response(jsonify(resp))\r\n# response.headers[\"Access-Control-Allow-Origin\"] = \"*\"\r\n return response\r\n\r\n\r\n\r\ndef json_list_render(code, data, limit, offset, message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n limit = limit,\r\n offset = offset,\r\n message = message,\r\n data = data\r\n )\r\n return _render(resp)\r\n\r\n\r\n\r\ndef json_detail_render(code, data = [], message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n message = message,\r\n data = data\r\n )\r\n return _render(resp)\r\n\r\n\r\ndef json_token_render(code, token, message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n token = token,\r\n message = message\r\n )\r\n return _render(resp)\r\n\r\ndef json_detail_render_sse(code, data = [], message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(code=code, message=message, data=data)\r\n return json.dumps(resp)\r\n"},"steps":{"kind":"list like","value":["#!/usr/bin/python\r\n# -*- coding: utf-8 -*-\r\n\r\nimport json\r\n\r\nfrom flask import jsonify\r\nfrom flask import make_response\r\nfrom MultipleInterfaceManager.settings import STATUS_CODE\r\n\r\n\r\ndef _render(resp):\r\n response = make_response(jsonify(resp))\r\n# response.headers[\"Access-Control-Allow-Origin\"] = \"*\"\r\n return response\r\n\r\n\r\n\r\ndef json_list_render(code, data, limit, offset, message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n limit = limit,\r\n offset = offset,\r\n message = message,\r\n data = data\r\n )\r\n return _render(resp)\r\n\r\n\r\n\r\ndef json_detail_render(code, data = [], message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n message = message,\r\n data = data\r\n )\r\n return _render(resp)\r\n\r\n\r\ndef json_token_render(code, token, message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(\r\n code = code,\r\n token = token,\r\n message = message\r\n )\r\n return _render(resp)\r\n\r\ndef json_detail_render_sse(code, data = [], message = None):\r\n if message is None:\r\n message = STATUS_CODE.get(code)\r\n resp = dict(code=code, message=message, data=data)\r\n return json.dumps(resp)\r\n","import json\nfrom flask import jsonify\nfrom flask import make_response\nfrom MultipleInterfaceManager.settings import STATUS_CODE\n\n\ndef _render(resp):\n response = make_response(jsonify(resp))\n return response\n\n\ndef json_list_render(code, data, limit, offset, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, limit=limit, offset=offset, message=message,\n data=data)\n return _render(resp)\n\n\ndef json_detail_render(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return _render(resp)\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\ndef json_detail_render_sse(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return json.dumps(resp)\n","<import token>\n\n\ndef _render(resp):\n response = make_response(jsonify(resp))\n return response\n\n\ndef json_list_render(code, data, limit, offset, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, limit=limit, offset=offset, message=message,\n data=data)\n return _render(resp)\n\n\ndef json_detail_render(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return _render(resp)\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\ndef json_detail_render_sse(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return json.dumps(resp)\n","<import token>\n\n\ndef _render(resp):\n response = make_response(jsonify(resp))\n return response\n\n\n<function token>\n\n\ndef json_detail_render(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return _render(resp)\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\ndef json_detail_render_sse(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return json.dumps(resp)\n","<import token>\n<function token>\n<function token>\n\n\ndef json_detail_render(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return _render(resp)\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\ndef json_detail_render_sse(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return json.dumps(resp)\n","<import token>\n<function token>\n<function token>\n<function token>\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\ndef json_detail_render_sse(code, data=[], message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, message=message, data=data)\n return json.dumps(resp)\n","<import token>\n<function token>\n<function token>\n<function token>\n\n\ndef json_token_render(code, token, message=None):\n if message is None:\n message = STATUS_CODE.get(code)\n resp = dict(code=code, token=token, message=message)\n return _render(resp)\n\n\n<function token>\n","<import token>\n<function token>\n<function token>\n<function token>\n<function token>\n<function token>\n"],"string":"[\n \"#!/usr/bin/python\\r\\n# -*- coding: utf-8 -*-\\r\\n\\r\\nimport json\\r\\n\\r\\nfrom flask import jsonify\\r\\nfrom flask import make_response\\r\\nfrom MultipleInterfaceManager.settings import STATUS_CODE\\r\\n\\r\\n\\r\\ndef _render(resp):\\r\\n response = make_response(jsonify(resp))\\r\\n# response.headers[\\\"Access-Control-Allow-Origin\\\"] = \\\"*\\\"\\r\\n return response\\r\\n\\r\\n\\r\\n\\r\\ndef json_list_render(code, data, limit, offset, message = None):\\r\\n if message is None:\\r\\n message = STATUS_CODE.get(code)\\r\\n resp = dict(\\r\\n code = code,\\r\\n limit = limit,\\r\\n offset = offset,\\r\\n message = message,\\r\\n data = data\\r\\n )\\r\\n return _render(resp)\\r\\n\\r\\n\\r\\n\\r\\ndef json_detail_render(code, data = [], message = None):\\r\\n if message is None:\\r\\n message = STATUS_CODE.get(code)\\r\\n resp = dict(\\r\\n code = code,\\r\\n message = message,\\r\\n data = data\\r\\n )\\r\\n return _render(resp)\\r\\n\\r\\n\\r\\ndef json_token_render(code, token, message = None):\\r\\n if message is None:\\r\\n message = STATUS_CODE.get(code)\\r\\n resp = dict(\\r\\n code = code,\\r\\n token = token,\\r\\n message = message\\r\\n )\\r\\n return _render(resp)\\r\\n\\r\\ndef json_detail_render_sse(code, data = [], message = None):\\r\\n if message is None:\\r\\n message = STATUS_CODE.get(code)\\r\\n resp = dict(code=code, message=message, data=data)\\r\\n return json.dumps(resp)\\r\\n\",\n \"import json\\nfrom flask import jsonify\\nfrom flask import make_response\\nfrom MultipleInterfaceManager.settings import STATUS_CODE\\n\\n\\ndef _render(resp):\\n response = make_response(jsonify(resp))\\n return response\\n\\n\\ndef json_list_render(code, data, limit, offset, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, limit=limit, offset=offset, message=message,\\n data=data)\\n return _render(resp)\\n\\n\\ndef json_detail_render(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return _render(resp)\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\ndef json_detail_render_sse(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return json.dumps(resp)\\n\",\n \"<import token>\\n\\n\\ndef _render(resp):\\n response = make_response(jsonify(resp))\\n return response\\n\\n\\ndef json_list_render(code, data, limit, offset, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, limit=limit, offset=offset, message=message,\\n data=data)\\n return _render(resp)\\n\\n\\ndef json_detail_render(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return _render(resp)\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\ndef json_detail_render_sse(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return json.dumps(resp)\\n\",\n \"<import token>\\n\\n\\ndef _render(resp):\\n response = make_response(jsonify(resp))\\n return response\\n\\n\\n<function token>\\n\\n\\ndef json_detail_render(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return _render(resp)\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\ndef json_detail_render_sse(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return json.dumps(resp)\\n\",\n \"<import token>\\n<function token>\\n<function token>\\n\\n\\ndef json_detail_render(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return _render(resp)\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\ndef json_detail_render_sse(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return json.dumps(resp)\\n\",\n \"<import token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\ndef json_detail_render_sse(code, data=[], message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, message=message, data=data)\\n return json.dumps(resp)\\n\",\n \"<import token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\ndef json_token_render(code, token, message=None):\\n if message is None:\\n message = STATUS_CODE.get(code)\\n resp = dict(code=code, token=token, message=message)\\n return _render(resp)\\n\\n\\n<function token>\\n\",\n \"<import token>\\n<function token>\\n<function token>\\n<function token>\\n<function token>\\n<function token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8690,"cells":{"index":{"kind":"number","value":8690,"string":"8,690"},"blob_id":{"kind":"string","value":"24891cdefcd061f04e7b7768b1bde4e32b78adcc"},"code":{"kind":"string","value":"import heapq\nfrom util import edit_distance\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by their Levenshtein distance to words in the\n BK-tree (where nearby words are weighted higher).\"\"\"\n completion_weights = suggest_tree.completion_weights(prefix)\n if completion_weights:\n weight = lambda completion: completion_weights[completion]\n proximity = lambda completion: completion_proximity_score(\n prefix, completion)\n selection_criteria = lambda completion: (\n weight(completion), proximity(completion))\n completions = completion_weights.keys()\n return heapq.nlargest(count, completions, key=selection_criteria)\n else:\n matches = bktree.search(prefix)\n proximity = lambda completion: edit_distance(prefix, completion)\n return heapq.nsmallest(count, matches, key=proximity)\n\n \ndef completion_proximity_score(prefix, completion):\n \"\"\"Calculate a score based on suffix length where a shorter length always\n yields a higher score.\"\"\"\n if prefix == completion:\n return float(\"inf\")\n else:\n return 1.0 / float(len(completion))\n"},"steps":{"kind":"list like","value":["import heapq\nfrom util import edit_distance\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by their Levenshtein distance to words in the\n BK-tree (where nearby words are weighted higher).\"\"\"\n completion_weights = suggest_tree.completion_weights(prefix)\n if completion_weights:\n weight = lambda completion: completion_weights[completion]\n proximity = lambda completion: completion_proximity_score(\n prefix, completion)\n selection_criteria = lambda completion: (\n weight(completion), proximity(completion))\n completions = completion_weights.keys()\n return heapq.nlargest(count, completions, key=selection_criteria)\n else:\n matches = bktree.search(prefix)\n proximity = lambda completion: edit_distance(prefix, completion)\n return heapq.nsmallest(count, matches, key=proximity)\n\n \ndef completion_proximity_score(prefix, completion):\n \"\"\"Calculate a score based on suffix length where a shorter length always\n yields a higher score.\"\"\"\n if prefix == completion:\n return float(\"inf\")\n else:\n return 1.0 / float(len(completion))\n","import heapq\nfrom util import edit_distance\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by their Levenshtein distance to words in the\n BK-tree (where nearby words are weighted higher).\"\"\"\n completion_weights = suggest_tree.completion_weights(prefix)\n if completion_weights:\n weight = lambda completion: completion_weights[completion]\n proximity = lambda completion: completion_proximity_score(prefix,\n completion)\n selection_criteria = lambda completion: (weight(completion),\n proximity(completion))\n completions = completion_weights.keys()\n return heapq.nlargest(count, completions, key=selection_criteria)\n else:\n matches = bktree.search(prefix)\n proximity = lambda completion: edit_distance(prefix, completion)\n return heapq.nsmallest(count, matches, key=proximity)\n\n\ndef completion_proximity_score(prefix, completion):\n \"\"\"Calculate a score based on suffix length where a shorter length always\n yields a higher score.\"\"\"\n if prefix == completion:\n return float('inf')\n else:\n return 1.0 / float(len(completion))\n","<import token>\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by their Levenshtein distance to words in the\n BK-tree (where nearby words are weighted higher).\"\"\"\n completion_weights = suggest_tree.completion_weights(prefix)\n if completion_weights:\n weight = lambda completion: completion_weights[completion]\n proximity = lambda completion: completion_proximity_score(prefix,\n completion)\n selection_criteria = lambda completion: (weight(completion),\n proximity(completion))\n completions = completion_weights.keys()\n return heapq.nlargest(count, completions, key=selection_criteria)\n else:\n matches = bktree.search(prefix)\n proximity = lambda completion: edit_distance(prefix, completion)\n return heapq.nsmallest(count, matches, key=proximity)\n\n\ndef completion_proximity_score(prefix, completion):\n \"\"\"Calculate a score based on suffix length where a shorter length always\n yields a higher score.\"\"\"\n if prefix == completion:\n return float('inf')\n else:\n return 1.0 / float(len(completion))\n","<import token>\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by their Levenshtein distance to words in the\n BK-tree (where nearby words are weighted higher).\"\"\"\n completion_weights = suggest_tree.completion_weights(prefix)\n if completion_weights:\n weight = lambda completion: completion_weights[completion]\n proximity = lambda completion: completion_proximity_score(prefix,\n completion)\n selection_criteria = lambda completion: (weight(completion),\n proximity(completion))\n completions = completion_weights.keys()\n return heapq.nlargest(count, completions, key=selection_criteria)\n else:\n matches = bktree.search(prefix)\n proximity = lambda completion: edit_distance(prefix, completion)\n return heapq.nsmallest(count, matches, key=proximity)\n\n\n<function token>\n","<import token>\n<function token>\n<function token>\n"],"string":"[\n \"import heapq\\nfrom util import edit_distance\\n\\n\\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\\n \\\"\\\"\\\"Suggest top completions for a prefix given a SuggestTree and BKTree.\\n \\n Completions for a given prefix are weighted primarily by their weight in the \\n suggest tree, and secondarily by their Levenshtein distance to words in the\\n BK-tree (where nearby words are weighted higher).\\\"\\\"\\\"\\n completion_weights = suggest_tree.completion_weights(prefix)\\n if completion_weights:\\n weight = lambda completion: completion_weights[completion]\\n proximity = lambda completion: completion_proximity_score(\\n prefix, completion)\\n selection_criteria = lambda completion: (\\n weight(completion), proximity(completion))\\n completions = completion_weights.keys()\\n return heapq.nlargest(count, completions, key=selection_criteria)\\n else:\\n matches = bktree.search(prefix)\\n proximity = lambda completion: edit_distance(prefix, completion)\\n return heapq.nsmallest(count, matches, key=proximity)\\n\\n \\ndef completion_proximity_score(prefix, completion):\\n \\\"\\\"\\\"Calculate a score based on suffix length where a shorter length always\\n yields a higher score.\\\"\\\"\\\"\\n if prefix == completion:\\n return float(\\\"inf\\\")\\n else:\\n return 1.0 / float(len(completion))\\n\",\n \"import heapq\\nfrom util import edit_distance\\n\\n\\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\\n \\\"\\\"\\\"Suggest top completions for a prefix given a SuggestTree and BKTree.\\n \\n Completions for a given prefix are weighted primarily by their weight in the \\n suggest tree, and secondarily by their Levenshtein distance to words in the\\n BK-tree (where nearby words are weighted higher).\\\"\\\"\\\"\\n completion_weights = suggest_tree.completion_weights(prefix)\\n if completion_weights:\\n weight = lambda completion: completion_weights[completion]\\n proximity = lambda completion: completion_proximity_score(prefix,\\n completion)\\n selection_criteria = lambda completion: (weight(completion),\\n proximity(completion))\\n completions = completion_weights.keys()\\n return heapq.nlargest(count, completions, key=selection_criteria)\\n else:\\n matches = bktree.search(prefix)\\n proximity = lambda completion: edit_distance(prefix, completion)\\n return heapq.nsmallest(count, matches, key=proximity)\\n\\n\\ndef completion_proximity_score(prefix, completion):\\n \\\"\\\"\\\"Calculate a score based on suffix length where a shorter length always\\n yields a higher score.\\\"\\\"\\\"\\n if prefix == completion:\\n return float('inf')\\n else:\\n return 1.0 / float(len(completion))\\n\",\n \"<import token>\\n\\n\\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\\n \\\"\\\"\\\"Suggest top completions for a prefix given a SuggestTree and BKTree.\\n \\n Completions for a given prefix are weighted primarily by their weight in the \\n suggest tree, and secondarily by their Levenshtein distance to words in the\\n BK-tree (where nearby words are weighted higher).\\\"\\\"\\\"\\n completion_weights = suggest_tree.completion_weights(prefix)\\n if completion_weights:\\n weight = lambda completion: completion_weights[completion]\\n proximity = lambda completion: completion_proximity_score(prefix,\\n completion)\\n selection_criteria = lambda completion: (weight(completion),\\n proximity(completion))\\n completions = completion_weights.keys()\\n return heapq.nlargest(count, completions, key=selection_criteria)\\n else:\\n matches = bktree.search(prefix)\\n proximity = lambda completion: edit_distance(prefix, completion)\\n return heapq.nsmallest(count, matches, key=proximity)\\n\\n\\ndef completion_proximity_score(prefix, completion):\\n \\\"\\\"\\\"Calculate a score based on suffix length where a shorter length always\\n yields a higher score.\\\"\\\"\\\"\\n if prefix == completion:\\n return float('inf')\\n else:\\n return 1.0 / float(len(completion))\\n\",\n \"<import token>\\n\\n\\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\\n \\\"\\\"\\\"Suggest top completions for a prefix given a SuggestTree and BKTree.\\n \\n Completions for a given prefix are weighted primarily by their weight in the \\n suggest tree, and secondarily by their Levenshtein distance to words in the\\n BK-tree (where nearby words are weighted higher).\\\"\\\"\\\"\\n completion_weights = suggest_tree.completion_weights(prefix)\\n if completion_weights:\\n weight = lambda completion: completion_weights[completion]\\n proximity = lambda completion: completion_proximity_score(prefix,\\n completion)\\n selection_criteria = lambda completion: (weight(completion),\\n proximity(completion))\\n completions = completion_weights.keys()\\n return heapq.nlargest(count, completions, key=selection_criteria)\\n else:\\n matches = bktree.search(prefix)\\n proximity = lambda completion: edit_distance(prefix, completion)\\n return heapq.nsmallest(count, matches, key=proximity)\\n\\n\\n<function token>\\n\",\n \"<import token>\\n<function token>\\n<function token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8691,"cells":{"index":{"kind":"number","value":8691,"string":"8,691"},"blob_id":{"kind":"string","value":"b934770e9e57a0ead124e245f394433ce853dec9"},"code":{"kind":"string","value":"import time\nimport machine\nfrom machine import Timer\nimport network\nimport onewire, ds18x20\nimport ujson\nimport ubinascii\nfrom umqtt.simple import MQTTClient\nimport ntptime\nimport errno\n\n#Thrown if an error that is fatal occurs,\n#stop measurement cycle.\nclass Error(Exception):\n pass\n\n#Thrown if an error that is not fatal occurs,\n#goes to deep sleep and continues as normal.\n#For example no wifi connection at this time.\nclass Warning(Exception):\n pass\n \ndef gettimestr():\n rtc=machine.RTC()\n curtime=rtc.datetime()\n _time=\"%04d\" % curtime[0]+ \"%02d\" % curtime[1]+ \"%02d\" % curtime[2]+\" \"+ \"%02d\" % curtime[4]+ \"%02d\" % curtime[5]\n return _time\n\ndef deepsleep():\n # configure RTC.ALARM0 to be able to wake the device\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n\n # set RTC.ALARM0 to fire after 60 seconds (waking the device)\n rtc.alarm(rtc.ALARM0, 60000)\n\n # put the device to sleep\n machine.deepsleep()\n\ntimer_index=20\n\ndef timercallback(tim):\n global timer_index\n if timer_index==0:\n print(\"Timer reached 0, something went wrong -> sleep.\")\n deepsleep()\n print(\"Timer index \"+str(timer_index))\n timer_index=timer_index-1\n \n#check if gpio4 is pulled down\nstoppin = machine.Pin(4,mode=machine.Pin.IN,pull=machine.Pin.PULL_UP)\nif stoppin.value()==0:\n print(\"Pin down, stop\")\nelse:\n try:\n #normal loop\n\n tim = Timer(-1)\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\n\n try:\n f = open('config.json', 'r')\n config = ujson.loads(f.readall())\n except OSError as e:\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\n print(\"I/O error({0}): {1}\".format(e.args[0], e.args[1]))\n raise Error\n\n # the device is on GPIOxx\n ONEWIREPIN = config['ONEWIREPIN']\n dat = machine.Pin(ONEWIREPIN)\n\n # create the onewire object\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\n\n # scan for devices on the bus\n roms = ds.scan()\n print('found devices:', roms)\n if (len(roms)>0):\n ds.convert_temp()\n time.sleep_ms(750)\n\n # Check if we have wifi, and wait for connection if not.\n print(\"Check wifi connection.\")\n wifi = network.WLAN(network.STA_IF)\n i = 0\n while not wifi.isconnected():\n if (i>10):\n print(\"No wifi connection.\")\n raise Warning\n print(\".\")\n time.sleep(1)\n i=i+1\n\n try:\n print(\"Get time.\")\n ntptime.settime()\n except OSError as e:\n if e.args[0] == errno.ETIMEDOUT: #OSError: [Errno 110] ETIMEDOUT\n print(\"Timeout error, didn't get ntptime.\")\n #if we did not wake up from deep sleep\n #we cannot continue until we get correct time\n if (machine.reset_cause()!=machine.DEEPSLEEP):\n raise Warning\n if e.args[0] == -2: #OSError: dns error\n print(\"DNS error, didn't get ntptime.\")\n #if we did not wake up from deep sleep\n #we cannot continue until we get correct time\n if (machine.reset_cause()!=machine.DEEPSLEEP):\n raise Warning\n else:\n raise\n _time=gettimestr()\n \n\n print(\"Open MQTT connection.\")\n c = MQTTClient(\"umqtt_client\", config['MQTT_BROKER'])\n c.connect()\n\n #check battery voltage?\n if (config['MEASURE_VOLTAGE']):\n adc = machine.ADC(0)\n voltage = adc.read();\n topic=\"raw/esp8266/\"+ubinascii.hexlify(machine.unique_id()).decode()+\"/voltage\"\n message=_time+\" \"+str(voltage)\n c.publish(topic,message)\n\n #loop ds18b20 and send results to mqtt broker\n for rom in roms:\n print(\"topic \"+config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode())\n topic=config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode()+\"/temperature\"\n print(_time)\n print(ds.read_temp(rom))\n message=_time+' '+str(ds.read_temp(rom))\n c.publish(topic,message)\n\n c.disconnect()\n\n deepsleep()\n except Warning:\n deepsleep()\n except Error:\n print(\"Error({0}): {1}\".format(e.args[0], e.args[1]))\n \n"},"steps":{"kind":"list like","value":["import time\nimport machine\nfrom machine import Timer\nimport network\nimport onewire, ds18x20\nimport ujson\nimport ubinascii\nfrom umqtt.simple import MQTTClient\nimport ntptime\nimport errno\n\n#Thrown if an error that is fatal occurs,\n#stop measurement cycle.\nclass Error(Exception):\n pass\n\n#Thrown if an error that is not fatal occurs,\n#goes to deep sleep and continues as normal.\n#For example no wifi connection at this time.\nclass Warning(Exception):\n pass\n \ndef gettimestr():\n rtc=machine.RTC()\n curtime=rtc.datetime()\n _time=\"%04d\" % curtime[0]+ \"%02d\" % curtime[1]+ \"%02d\" % curtime[2]+\" \"+ \"%02d\" % curtime[4]+ \"%02d\" % curtime[5]\n return _time\n\ndef deepsleep():\n # configure RTC.ALARM0 to be able to wake the device\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n\n # set RTC.ALARM0 to fire after 60 seconds (waking the device)\n rtc.alarm(rtc.ALARM0, 60000)\n\n # put the device to sleep\n machine.deepsleep()\n\ntimer_index=20\n\ndef timercallback(tim):\n global timer_index\n if timer_index==0:\n print(\"Timer reached 0, something went wrong -> sleep.\")\n deepsleep()\n print(\"Timer index \"+str(timer_index))\n timer_index=timer_index-1\n \n#check if gpio4 is pulled down\nstoppin = machine.Pin(4,mode=machine.Pin.IN,pull=machine.Pin.PULL_UP)\nif stoppin.value()==0:\n print(\"Pin down, stop\")\nelse:\n try:\n #normal loop\n\n tim = Timer(-1)\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\n\n try:\n f = open('config.json', 'r')\n config = ujson.loads(f.readall())\n except OSError as e:\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\n print(\"I/O error({0}): {1}\".format(e.args[0], e.args[1]))\n raise Error\n\n # the device is on GPIOxx\n ONEWIREPIN = config['ONEWIREPIN']\n dat = machine.Pin(ONEWIREPIN)\n\n # create the onewire object\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\n\n # scan for devices on the bus\n roms = ds.scan()\n print('found devices:', roms)\n if (len(roms)>0):\n ds.convert_temp()\n time.sleep_ms(750)\n\n # Check if we have wifi, and wait for connection if not.\n print(\"Check wifi connection.\")\n wifi = network.WLAN(network.STA_IF)\n i = 0\n while not wifi.isconnected():\n if (i>10):\n print(\"No wifi connection.\")\n raise Warning\n print(\".\")\n time.sleep(1)\n i=i+1\n\n try:\n print(\"Get time.\")\n ntptime.settime()\n except OSError as e:\n if e.args[0] == errno.ETIMEDOUT: #OSError: [Errno 110] ETIMEDOUT\n print(\"Timeout error, didn't get ntptime.\")\n #if we did not wake up from deep sleep\n #we cannot continue until we get correct time\n if (machine.reset_cause()!=machine.DEEPSLEEP):\n raise Warning\n if e.args[0] == -2: #OSError: dns error\n print(\"DNS error, didn't get ntptime.\")\n #if we did not wake up from deep sleep\n #we cannot continue until we get correct time\n if (machine.reset_cause()!=machine.DEEPSLEEP):\n raise Warning\n else:\n raise\n _time=gettimestr()\n \n\n print(\"Open MQTT connection.\")\n c = MQTTClient(\"umqtt_client\", config['MQTT_BROKER'])\n c.connect()\n\n #check battery voltage?\n if (config['MEASURE_VOLTAGE']):\n adc = machine.ADC(0)\n voltage = adc.read();\n topic=\"raw/esp8266/\"+ubinascii.hexlify(machine.unique_id()).decode()+\"/voltage\"\n message=_time+\" \"+str(voltage)\n c.publish(topic,message)\n\n #loop ds18b20 and send results to mqtt broker\n for rom in roms:\n print(\"topic \"+config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode())\n topic=config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode()+\"/temperature\"\n print(_time)\n print(ds.read_temp(rom))\n message=_time+' '+str(ds.read_temp(rom))\n c.publish(topic,message)\n\n c.disconnect()\n\n deepsleep()\n except Warning:\n deepsleep()\n except Error:\n print(\"Error({0}): {1}\".format(e.args[0], e.args[1]))\n \n","import time\nimport machine\nfrom machine import Timer\nimport network\nimport onewire, ds18x20\nimport ujson\nimport ubinascii\nfrom umqtt.simple import MQTTClient\nimport ntptime\nimport errno\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\n return _time\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\ntimer_index = 20\n\n\ndef timercallback(tim):\n global timer_index\n if timer_index == 0:\n print('Timer reached 0, something went wrong -> sleep.')\n deepsleep()\n print('Timer index ' + str(timer_index))\n timer_index = timer_index - 1\n\n\nstoppin = machine.Pin(4, mode=machine.Pin.IN, pull=machine.Pin.PULL_UP)\nif stoppin.value() == 0:\n print('Pin down, stop')\nelse:\n try:\n tim = Timer(-1)\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\n try:\n f = open('config.json', 'r')\n config = ujson.loads(f.readall())\n except OSError as e:\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\n raise Error\n ONEWIREPIN = config['ONEWIREPIN']\n dat = machine.Pin(ONEWIREPIN)\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\n roms = ds.scan()\n print('found devices:', roms)\n if len(roms) > 0:\n ds.convert_temp()\n time.sleep_ms(750)\n print('Check wifi connection.')\n wifi = network.WLAN(network.STA_IF)\n i = 0\n while not wifi.isconnected():\n if i > 10:\n print('No wifi connection.')\n raise Warning\n print('.')\n time.sleep(1)\n i = i + 1\n try:\n print('Get time.')\n ntptime.settime()\n except OSError as e:\n if e.args[0] == errno.ETIMEDOUT:\n print(\"Timeout error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n if e.args[0] == -2:\n print(\"DNS error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n else:\n raise\n _time = gettimestr()\n print('Open MQTT connection.')\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\n c.connect()\n if config['MEASURE_VOLTAGE']:\n adc = machine.ADC(0)\n voltage = adc.read()\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\n ).decode() + '/voltage'\n message = _time + ' ' + str(voltage)\n c.publish(topic, message)\n for rom in roms:\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\n decode())\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\n ) + '/temperature'\n print(_time)\n print(ds.read_temp(rom))\n message = _time + ' ' + str(ds.read_temp(rom))\n c.publish(topic, message)\n c.disconnect()\n deepsleep()\n except Warning:\n deepsleep()\n except Error:\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\n return _time\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\ntimer_index = 20\n\n\ndef timercallback(tim):\n global timer_index\n if timer_index == 0:\n print('Timer reached 0, something went wrong -> sleep.')\n deepsleep()\n print('Timer index ' + str(timer_index))\n timer_index = timer_index - 1\n\n\nstoppin = machine.Pin(4, mode=machine.Pin.IN, pull=machine.Pin.PULL_UP)\nif stoppin.value() == 0:\n print('Pin down, stop')\nelse:\n try:\n tim = Timer(-1)\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\n try:\n f = open('config.json', 'r')\n config = ujson.loads(f.readall())\n except OSError as e:\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\n raise Error\n ONEWIREPIN = config['ONEWIREPIN']\n dat = machine.Pin(ONEWIREPIN)\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\n roms = ds.scan()\n print('found devices:', roms)\n if len(roms) > 0:\n ds.convert_temp()\n time.sleep_ms(750)\n print('Check wifi connection.')\n wifi = network.WLAN(network.STA_IF)\n i = 0\n while not wifi.isconnected():\n if i > 10:\n print('No wifi connection.')\n raise Warning\n print('.')\n time.sleep(1)\n i = i + 1\n try:\n print('Get time.')\n ntptime.settime()\n except OSError as e:\n if e.args[0] == errno.ETIMEDOUT:\n print(\"Timeout error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n if e.args[0] == -2:\n print(\"DNS error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n else:\n raise\n _time = gettimestr()\n print('Open MQTT connection.')\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\n c.connect()\n if config['MEASURE_VOLTAGE']:\n adc = machine.ADC(0)\n voltage = adc.read()\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\n ).decode() + '/voltage'\n message = _time + ' ' + str(voltage)\n c.publish(topic, message)\n for rom in roms:\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\n decode())\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\n ) + '/temperature'\n print(_time)\n print(ds.read_temp(rom))\n message = _time + ' ' + str(ds.read_temp(rom))\n c.publish(topic, message)\n c.disconnect()\n deepsleep()\n except Warning:\n deepsleep()\n except Error:\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\n return _time\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\n<assignment token>\n\n\ndef timercallback(tim):\n global timer_index\n if timer_index == 0:\n print('Timer reached 0, something went wrong -> sleep.')\n deepsleep()\n print('Timer index ' + str(timer_index))\n timer_index = timer_index - 1\n\n\n<assignment token>\nif stoppin.value() == 0:\n print('Pin down, stop')\nelse:\n try:\n tim = Timer(-1)\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\n try:\n f = open('config.json', 'r')\n config = ujson.loads(f.readall())\n except OSError as e:\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\n raise Error\n ONEWIREPIN = config['ONEWIREPIN']\n dat = machine.Pin(ONEWIREPIN)\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\n roms = ds.scan()\n print('found devices:', roms)\n if len(roms) > 0:\n ds.convert_temp()\n time.sleep_ms(750)\n print('Check wifi connection.')\n wifi = network.WLAN(network.STA_IF)\n i = 0\n while not wifi.isconnected():\n if i > 10:\n print('No wifi connection.')\n raise Warning\n print('.')\n time.sleep(1)\n i = i + 1\n try:\n print('Get time.')\n ntptime.settime()\n except OSError as e:\n if e.args[0] == errno.ETIMEDOUT:\n print(\"Timeout error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n if e.args[0] == -2:\n print(\"DNS error, didn't get ntptime.\")\n if machine.reset_cause() != machine.DEEPSLEEP:\n raise Warning\n else:\n raise\n _time = gettimestr()\n print('Open MQTT connection.')\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\n c.connect()\n if config['MEASURE_VOLTAGE']:\n adc = machine.ADC(0)\n voltage = adc.read()\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\n ).decode() + '/voltage'\n message = _time + ' ' + str(voltage)\n c.publish(topic, message)\n for rom in roms:\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\n decode())\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\n ) + '/temperature'\n print(_time)\n print(ds.read_temp(rom))\n message = _time + ' ' + str(ds.read_temp(rom))\n c.publish(topic, message)\n c.disconnect()\n deepsleep()\n except Warning:\n deepsleep()\n except Error:\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\n return _time\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\n<assignment token>\n\n\ndef timercallback(tim):\n global timer_index\n if timer_index == 0:\n print('Timer reached 0, something went wrong -> sleep.')\n deepsleep()\n print('Timer index ' + str(timer_index))\n timer_index = timer_index - 1\n\n\n<assignment token>\n<code token>\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\n return _time\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\n<function token>\n\n\ndef deepsleep():\n rtc = machine.RTC()\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\n rtc.alarm(rtc.ALARM0, 60000)\n machine.deepsleep()\n\n\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n","<import token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\n<function token>\n<function token>\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n","<import token>\n<class token>\n\n\nclass Warning(Exception):\n pass\n\n\n<function token>\n<function token>\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n","<import token>\n<class token>\n<class token>\n<function token>\n<function token>\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n"],"string":"[\n \"import time\\nimport machine\\nfrom machine import Timer\\nimport network\\nimport onewire, ds18x20\\nimport ujson\\nimport ubinascii\\nfrom umqtt.simple import MQTTClient\\nimport ntptime\\nimport errno\\n\\n#Thrown if an error that is fatal occurs,\\n#stop measurement cycle.\\nclass Error(Exception):\\n pass\\n\\n#Thrown if an error that is not fatal occurs,\\n#goes to deep sleep and continues as normal.\\n#For example no wifi connection at this time.\\nclass Warning(Exception):\\n pass\\n \\ndef gettimestr():\\n rtc=machine.RTC()\\n curtime=rtc.datetime()\\n _time=\\\"%04d\\\" % curtime[0]+ \\\"%02d\\\" % curtime[1]+ \\\"%02d\\\" % curtime[2]+\\\" \\\"+ \\\"%02d\\\" % curtime[4]+ \\\"%02d\\\" % curtime[5]\\n return _time\\n\\ndef deepsleep():\\n # configure RTC.ALARM0 to be able to wake the device\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n\\n # set RTC.ALARM0 to fire after 60 seconds (waking the device)\\n rtc.alarm(rtc.ALARM0, 60000)\\n\\n # put the device to sleep\\n machine.deepsleep()\\n\\ntimer_index=20\\n\\ndef timercallback(tim):\\n global timer_index\\n if timer_index==0:\\n print(\\\"Timer reached 0, something went wrong -> sleep.\\\")\\n deepsleep()\\n print(\\\"Timer index \\\"+str(timer_index))\\n timer_index=timer_index-1\\n \\n#check if gpio4 is pulled down\\nstoppin = machine.Pin(4,mode=machine.Pin.IN,pull=machine.Pin.PULL_UP)\\nif stoppin.value()==0:\\n print(\\\"Pin down, stop\\\")\\nelse:\\n try:\\n #normal loop\\n\\n tim = Timer(-1)\\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\\n\\n try:\\n f = open('config.json', 'r')\\n config = ujson.loads(f.readall())\\n except OSError as e:\\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\\n print(\\\"I/O error({0}): {1}\\\".format(e.args[0], e.args[1]))\\n raise Error\\n\\n # the device is on GPIOxx\\n ONEWIREPIN = config['ONEWIREPIN']\\n dat = machine.Pin(ONEWIREPIN)\\n\\n # create the onewire object\\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\\n\\n # scan for devices on the bus\\n roms = ds.scan()\\n print('found devices:', roms)\\n if (len(roms)>0):\\n ds.convert_temp()\\n time.sleep_ms(750)\\n\\n # Check if we have wifi, and wait for connection if not.\\n print(\\\"Check wifi connection.\\\")\\n wifi = network.WLAN(network.STA_IF)\\n i = 0\\n while not wifi.isconnected():\\n if (i>10):\\n print(\\\"No wifi connection.\\\")\\n raise Warning\\n print(\\\".\\\")\\n time.sleep(1)\\n i=i+1\\n\\n try:\\n print(\\\"Get time.\\\")\\n ntptime.settime()\\n except OSError as e:\\n if e.args[0] == errno.ETIMEDOUT: #OSError: [Errno 110] ETIMEDOUT\\n print(\\\"Timeout error, didn't get ntptime.\\\")\\n #if we did not wake up from deep sleep\\n #we cannot continue until we get correct time\\n if (machine.reset_cause()!=machine.DEEPSLEEP):\\n raise Warning\\n if e.args[0] == -2: #OSError: dns error\\n print(\\\"DNS error, didn't get ntptime.\\\")\\n #if we did not wake up from deep sleep\\n #we cannot continue until we get correct time\\n if (machine.reset_cause()!=machine.DEEPSLEEP):\\n raise Warning\\n else:\\n raise\\n _time=gettimestr()\\n \\n\\n print(\\\"Open MQTT connection.\\\")\\n c = MQTTClient(\\\"umqtt_client\\\", config['MQTT_BROKER'])\\n c.connect()\\n\\n #check battery voltage?\\n if (config['MEASURE_VOLTAGE']):\\n adc = machine.ADC(0)\\n voltage = adc.read();\\n topic=\\\"raw/esp8266/\\\"+ubinascii.hexlify(machine.unique_id()).decode()+\\\"/voltage\\\"\\n message=_time+\\\" \\\"+str(voltage)\\n c.publish(topic,message)\\n\\n #loop ds18b20 and send results to mqtt broker\\n for rom in roms:\\n print(\\\"topic \\\"+config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode())\\n topic=config['MQTT_TOPIC']+ubinascii.hexlify(rom).decode()+\\\"/temperature\\\"\\n print(_time)\\n print(ds.read_temp(rom))\\n message=_time+' '+str(ds.read_temp(rom))\\n c.publish(topic,message)\\n\\n c.disconnect()\\n\\n deepsleep()\\n except Warning:\\n deepsleep()\\n except Error:\\n print(\\\"Error({0}): {1}\\\".format(e.args[0], e.args[1]))\\n \\n\",\n \"import time\\nimport machine\\nfrom machine import Timer\\nimport network\\nimport onewire, ds18x20\\nimport ujson\\nimport ubinascii\\nfrom umqtt.simple import MQTTClient\\nimport ntptime\\nimport errno\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\ndef gettimestr():\\n rtc = machine.RTC()\\n curtime = rtc.datetime()\\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\\n return _time\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\ntimer_index = 20\\n\\n\\ndef timercallback(tim):\\n global timer_index\\n if timer_index == 0:\\n print('Timer reached 0, something went wrong -> sleep.')\\n deepsleep()\\n print('Timer index ' + str(timer_index))\\n timer_index = timer_index - 1\\n\\n\\nstoppin = machine.Pin(4, mode=machine.Pin.IN, pull=machine.Pin.PULL_UP)\\nif stoppin.value() == 0:\\n print('Pin down, stop')\\nelse:\\n try:\\n tim = Timer(-1)\\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\\n try:\\n f = open('config.json', 'r')\\n config = ujson.loads(f.readall())\\n except OSError as e:\\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\\n raise Error\\n ONEWIREPIN = config['ONEWIREPIN']\\n dat = machine.Pin(ONEWIREPIN)\\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\\n roms = ds.scan()\\n print('found devices:', roms)\\n if len(roms) > 0:\\n ds.convert_temp()\\n time.sleep_ms(750)\\n print('Check wifi connection.')\\n wifi = network.WLAN(network.STA_IF)\\n i = 0\\n while not wifi.isconnected():\\n if i > 10:\\n print('No wifi connection.')\\n raise Warning\\n print('.')\\n time.sleep(1)\\n i = i + 1\\n try:\\n print('Get time.')\\n ntptime.settime()\\n except OSError as e:\\n if e.args[0] == errno.ETIMEDOUT:\\n print(\\\"Timeout error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n if e.args[0] == -2:\\n print(\\\"DNS error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n else:\\n raise\\n _time = gettimestr()\\n print('Open MQTT connection.')\\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\\n c.connect()\\n if config['MEASURE_VOLTAGE']:\\n adc = machine.ADC(0)\\n voltage = adc.read()\\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\\n ).decode() + '/voltage'\\n message = _time + ' ' + str(voltage)\\n c.publish(topic, message)\\n for rom in roms:\\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\\n decode())\\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\\n ) + '/temperature'\\n print(_time)\\n print(ds.read_temp(rom))\\n message = _time + ' ' + str(ds.read_temp(rom))\\n c.publish(topic, message)\\n c.disconnect()\\n deepsleep()\\n except Warning:\\n deepsleep()\\n except Error:\\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\ndef gettimestr():\\n rtc = machine.RTC()\\n curtime = rtc.datetime()\\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\\n return _time\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\ntimer_index = 20\\n\\n\\ndef timercallback(tim):\\n global timer_index\\n if timer_index == 0:\\n print('Timer reached 0, something went wrong -> sleep.')\\n deepsleep()\\n print('Timer index ' + str(timer_index))\\n timer_index = timer_index - 1\\n\\n\\nstoppin = machine.Pin(4, mode=machine.Pin.IN, pull=machine.Pin.PULL_UP)\\nif stoppin.value() == 0:\\n print('Pin down, stop')\\nelse:\\n try:\\n tim = Timer(-1)\\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\\n try:\\n f = open('config.json', 'r')\\n config = ujson.loads(f.readall())\\n except OSError as e:\\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\\n raise Error\\n ONEWIREPIN = config['ONEWIREPIN']\\n dat = machine.Pin(ONEWIREPIN)\\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\\n roms = ds.scan()\\n print('found devices:', roms)\\n if len(roms) > 0:\\n ds.convert_temp()\\n time.sleep_ms(750)\\n print('Check wifi connection.')\\n wifi = network.WLAN(network.STA_IF)\\n i = 0\\n while not wifi.isconnected():\\n if i > 10:\\n print('No wifi connection.')\\n raise Warning\\n print('.')\\n time.sleep(1)\\n i = i + 1\\n try:\\n print('Get time.')\\n ntptime.settime()\\n except OSError as e:\\n if e.args[0] == errno.ETIMEDOUT:\\n print(\\\"Timeout error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n if e.args[0] == -2:\\n print(\\\"DNS error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n else:\\n raise\\n _time = gettimestr()\\n print('Open MQTT connection.')\\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\\n c.connect()\\n if config['MEASURE_VOLTAGE']:\\n adc = machine.ADC(0)\\n voltage = adc.read()\\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\\n ).decode() + '/voltage'\\n message = _time + ' ' + str(voltage)\\n c.publish(topic, message)\\n for rom in roms:\\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\\n decode())\\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\\n ) + '/temperature'\\n print(_time)\\n print(ds.read_temp(rom))\\n message = _time + ' ' + str(ds.read_temp(rom))\\n c.publish(topic, message)\\n c.disconnect()\\n deepsleep()\\n except Warning:\\n deepsleep()\\n except Error:\\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\ndef gettimestr():\\n rtc = machine.RTC()\\n curtime = rtc.datetime()\\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\\n return _time\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\n<assignment token>\\n\\n\\ndef timercallback(tim):\\n global timer_index\\n if timer_index == 0:\\n print('Timer reached 0, something went wrong -> sleep.')\\n deepsleep()\\n print('Timer index ' + str(timer_index))\\n timer_index = timer_index - 1\\n\\n\\n<assignment token>\\nif stoppin.value() == 0:\\n print('Pin down, stop')\\nelse:\\n try:\\n tim = Timer(-1)\\n tim.init(period=1000, mode=Timer.PERIODIC, callback=timercallback)\\n try:\\n f = open('config.json', 'r')\\n config = ujson.loads(f.readall())\\n except OSError as e:\\n if e.args[0] == errno.MP_ENOENT or e.args[0] == errno.MP_EIO:\\n print('I/O error({0}): {1}'.format(e.args[0], e.args[1]))\\n raise Error\\n ONEWIREPIN = config['ONEWIREPIN']\\n dat = machine.Pin(ONEWIREPIN)\\n ds = ds18x20.DS18X20(onewire.OneWire(dat))\\n roms = ds.scan()\\n print('found devices:', roms)\\n if len(roms) > 0:\\n ds.convert_temp()\\n time.sleep_ms(750)\\n print('Check wifi connection.')\\n wifi = network.WLAN(network.STA_IF)\\n i = 0\\n while not wifi.isconnected():\\n if i > 10:\\n print('No wifi connection.')\\n raise Warning\\n print('.')\\n time.sleep(1)\\n i = i + 1\\n try:\\n print('Get time.')\\n ntptime.settime()\\n except OSError as e:\\n if e.args[0] == errno.ETIMEDOUT:\\n print(\\\"Timeout error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n if e.args[0] == -2:\\n print(\\\"DNS error, didn't get ntptime.\\\")\\n if machine.reset_cause() != machine.DEEPSLEEP:\\n raise Warning\\n else:\\n raise\\n _time = gettimestr()\\n print('Open MQTT connection.')\\n c = MQTTClient('umqtt_client', config['MQTT_BROKER'])\\n c.connect()\\n if config['MEASURE_VOLTAGE']:\\n adc = machine.ADC(0)\\n voltage = adc.read()\\n topic = 'raw/esp8266/' + ubinascii.hexlify(machine.unique_id()\\n ).decode() + '/voltage'\\n message = _time + ' ' + str(voltage)\\n c.publish(topic, message)\\n for rom in roms:\\n print('topic ' + config['MQTT_TOPIC'] + ubinascii.hexlify(rom).\\n decode())\\n topic = config['MQTT_TOPIC'] + ubinascii.hexlify(rom).decode(\\n ) + '/temperature'\\n print(_time)\\n print(ds.read_temp(rom))\\n message = _time + ' ' + str(ds.read_temp(rom))\\n c.publish(topic, message)\\n c.disconnect()\\n deepsleep()\\n except Warning:\\n deepsleep()\\n except Error:\\n print('Error({0}): {1}'.format(e.args[0], e.args[1]))\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\ndef gettimestr():\\n rtc = machine.RTC()\\n curtime = rtc.datetime()\\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\\n return _time\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\n<assignment token>\\n\\n\\ndef timercallback(tim):\\n global timer_index\\n if timer_index == 0:\\n print('Timer reached 0, something went wrong -> sleep.')\\n deepsleep()\\n print('Timer index ' + str(timer_index))\\n timer_index = timer_index - 1\\n\\n\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\ndef gettimestr():\\n rtc = machine.RTC()\\n curtime = rtc.datetime()\\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2\\n ] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]\\n return _time\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\n<function token>\\n\\n\\ndef deepsleep():\\n rtc = machine.RTC()\\n rtc.irq(trigger=rtc.ALARM0, wake=machine.DEEPSLEEP)\\n rtc.alarm(rtc.ALARM0, 60000)\\n machine.deepsleep()\\n\\n\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n\\n\\nclass Error(Exception):\\n pass\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\n<function token>\\n<function token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass Warning(Exception):\\n pass\\n\\n\\n<function token>\\n<function token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8692,"cells":{"index":{"kind":"number","value":8692,"string":"8,692"},"blob_id":{"kind":"string","value":"5d3b9005b8924da36a5885201339aa41082034cd"},"code":{"kind":"string","value":"from selenium.webdriver.common.by import By\n\n\nclass BasePageLocators:\n LOGIN_LINK = (By.CSS_SELECTOR, \"#login_link\")\n BASKET_LINK = (By.CSS_SELECTOR, '[class=\"btn btn-default\"]:nth-child(1)')\n USER_ICON = (By.CSS_SELECTOR, \".icon-user\")\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = (By.CSS_SELECTOR, \"#login_form\")\n REGISTER_FORM = (By.CSS_SELECTOR, \"#register_form\")\n REGISTRATION_EMAIL = (By.CSS_SELECTOR, '#id_registration-email')\n REGISTRATION_PASSWORD = (By.CSS_SELECTOR, '#id_registration-password1')\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR, '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR, '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = (By.CSS_SELECTOR, '#content_inner')\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = (By.CSS_SELECTOR, '.btn-add-to-basket')\n SHIPMENT_PRICE = (By.CSS_SELECTOR, '.product_main .price_color')\n SHIPMENT_NAME = (By.CSS_SELECTOR, '.product_main h1')\n\n"},"steps":{"kind":"list like","value":["from selenium.webdriver.common.by import By\n\n\nclass BasePageLocators:\n LOGIN_LINK = (By.CSS_SELECTOR, \"#login_link\")\n BASKET_LINK = (By.CSS_SELECTOR, '[class=\"btn btn-default\"]:nth-child(1)')\n USER_ICON = (By.CSS_SELECTOR, \".icon-user\")\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = (By.CSS_SELECTOR, \"#login_form\")\n REGISTER_FORM = (By.CSS_SELECTOR, \"#register_form\")\n REGISTRATION_EMAIL = (By.CSS_SELECTOR, '#id_registration-email')\n REGISTRATION_PASSWORD = (By.CSS_SELECTOR, '#id_registration-password1')\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR, '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR, '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = (By.CSS_SELECTOR, '#content_inner')\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = (By.CSS_SELECTOR, '.btn-add-to-basket')\n SHIPMENT_PRICE = (By.CSS_SELECTOR, '.product_main .price_color')\n SHIPMENT_NAME = (By.CSS_SELECTOR, '.product_main h1')\n\n","from selenium.webdriver.common.by import By\n\n\nclass BasePageLocators:\n LOGIN_LINK = By.CSS_SELECTOR, '#login_link'\n BASKET_LINK = By.CSS_SELECTOR, '[class=\"btn btn-default\"]:nth-child(1)'\n USER_ICON = By.CSS_SELECTOR, '.icon-user'\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\n '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\n '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n\n\nclass BasePageLocators:\n LOGIN_LINK = By.CSS_SELECTOR, '#login_link'\n BASKET_LINK = By.CSS_SELECTOR, '[class=\"btn btn-default\"]:nth-child(1)'\n USER_ICON = By.CSS_SELECTOR, '.icon-user'\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\n '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\n '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n\n\nclass BasePageLocators:\n <assignment token>\n <assignment token>\n <assignment token>\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\n '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\n '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\n '#id_registration-password2')\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\n '[name=\"registration_submit\"]')\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n\n\nclass LoginPageLocators:\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n <assignment token>\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n<class token>\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(3) > .alertinner strong')\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n<class token>\n\n\nclass BasketPageLocators:\n <assignment token>\n <assignment token>\n <assignment token>\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n<class token>\n<class token>\n\n\nclass ProductPageLocators:\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\n","<import token>\n<class token>\n<class token>\n<class token>\n\n\nclass ProductPageLocators:\n <assignment token>\n <assignment token>\n <assignment token>\n","<import token>\n<class token>\n<class token>\n<class token>\n<class token>\n"],"string":"[\n \"from selenium.webdriver.common.by import By\\n\\n\\nclass BasePageLocators:\\n LOGIN_LINK = (By.CSS_SELECTOR, \\\"#login_link\\\")\\n BASKET_LINK = (By.CSS_SELECTOR, '[class=\\\"btn btn-default\\\"]:nth-child(1)')\\n USER_ICON = (By.CSS_SELECTOR, \\\".icon-user\\\")\\n\\n\\nclass LoginPageLocators:\\n LOG_IN_FORM = (By.CSS_SELECTOR, \\\"#login_form\\\")\\n REGISTER_FORM = (By.CSS_SELECTOR, \\\"#register_form\\\")\\n REGISTRATION_EMAIL = (By.CSS_SELECTOR, '#id_registration-email')\\n REGISTRATION_PASSWORD = (By.CSS_SELECTOR, '#id_registration-password1')\\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR, '#id_registration-password2')\\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR, '[name=\\\"registration_submit\\\"]')\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = (By.CSS_SELECTOR, '#content_inner')\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR, '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = (By.CSS_SELECTOR, '.btn-add-to-basket')\\n SHIPMENT_PRICE = (By.CSS_SELECTOR, '.product_main .price_color')\\n SHIPMENT_NAME = (By.CSS_SELECTOR, '.product_main h1')\\n\\n\",\n \"from selenium.webdriver.common.by import By\\n\\n\\nclass BasePageLocators:\\n LOGIN_LINK = By.CSS_SELECTOR, '#login_link'\\n BASKET_LINK = By.CSS_SELECTOR, '[class=\\\"btn btn-default\\\"]:nth-child(1)'\\n USER_ICON = By.CSS_SELECTOR, '.icon-user'\\n\\n\\nclass LoginPageLocators:\\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\\n '#id_registration-password2')\\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\\n '[name=\\\"registration_submit\\\"]')\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n\\n\\nclass BasePageLocators:\\n LOGIN_LINK = By.CSS_SELECTOR, '#login_link'\\n BASKET_LINK = By.CSS_SELECTOR, '[class=\\\"btn btn-default\\\"]:nth-child(1)'\\n USER_ICON = By.CSS_SELECTOR, '.icon-user'\\n\\n\\nclass LoginPageLocators:\\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\\n '#id_registration-password2')\\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\\n '[name=\\\"registration_submit\\\"]')\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n\\n\\nclass BasePageLocators:\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n\\n\\nclass LoginPageLocators:\\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\\n '#id_registration-password2')\\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\\n '[name=\\\"registration_submit\\\"]')\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass LoginPageLocators:\\n LOG_IN_FORM = By.CSS_SELECTOR, '#login_form'\\n REGISTER_FORM = By.CSS_SELECTOR, '#register_form'\\n REGISTRATION_EMAIL = By.CSS_SELECTOR, '#id_registration-email'\\n REGISTRATION_PASSWORD = By.CSS_SELECTOR, '#id_registration-password1'\\n REGISTRATION_PASSWORD_CONFIRM = (By.CSS_SELECTOR,\\n '#id_registration-password2')\\n REGISTRATION_SUBMIT_BUTTON = (By.CSS_SELECTOR,\\n '[name=\\\"registration_submit\\\"]')\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n\\n\\nclass LoginPageLocators:\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n\\n\\nclass BasketPageLocators:\\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(1) > .alertinner strong')\\n PRICE_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\\n '#messages .alert:nth-child(3) > .alertinner strong')\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n\\n\\nclass BasketPageLocators:\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n<class token>\\n\\n\\nclass ProductPageLocators:\\n ADD_IN_BASKET = By.CSS_SELECTOR, '.btn-add-to-basket'\\n SHIPMENT_PRICE = By.CSS_SELECTOR, '.product_main .price_color'\\n SHIPMENT_NAME = By.CSS_SELECTOR, '.product_main h1'\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n<class token>\\n\\n\\nclass ProductPageLocators:\\n <assignment token>\\n <assignment token>\\n <assignment token>\\n\",\n \"<import token>\\n<class token>\\n<class token>\\n<class token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8693,"cells":{"index":{"kind":"number","value":8693,"string":"8,693"},"blob_id":{"kind":"string","value":"252a6b97f108b7fdc165ccb2a7f61ce31f129d3d"},"code":{"kind":"string","value":"import sys\nfrom collections import namedtuple\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \\\n QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\nfrom PyQt5.QtCore import Qt, QSize\n\nfrom runWidget import RunWidget\nfrom recordWidget import RecordWidget\n\n\ndef QListWidget_qss():\n return '''\n QListWidget{\n outline: 0px;\n }\n\n QListWidget {\n min-width: 30px;\n max-width: 50px;\n color: Black;\n background: #CCCCCC;\n }\n\n QListWidget::Item:selected {\n background: #888888;\n border-left: 5px solid red;\n }\n HistoryPanel:hover {\n background: rgb(52, 52, 52);\n }\n '''\n\n\nclass MainCentralWidget(QWidget):\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n \n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n main_window = MainWindow()\n sys.exit(app.exec_())"},"steps":{"kind":"list like","value":["import sys\nfrom collections import namedtuple\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \\\n QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\nfrom PyQt5.QtCore import Qt, QSize\n\nfrom runWidget import RunWidget\nfrom recordWidget import RecordWidget\n\n\ndef QListWidget_qss():\n return '''\n QListWidget{\n outline: 0px;\n }\n\n QListWidget {\n min-width: 30px;\n max-width: 50px;\n color: Black;\n background: #CCCCCC;\n }\n\n QListWidget::Item:selected {\n background: #888888;\n border-left: 5px solid red;\n }\n HistoryPanel:hover {\n background: rgb(52, 52, 52);\n }\n '''\n\n\nclass MainCentralWidget(QWidget):\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n \n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n main_window = MainWindow()\n sys.exit(app.exec_())","import sys\nfrom collections import namedtuple\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\nfrom PyQt5.QtCore import Qt, QSize\nfrom runWidget import RunWidget\nfrom recordWidget import RecordWidget\n\n\ndef QListWidget_qss():\n return \"\"\"\n QListWidget{\n outline: 0px;\n }\n\n QListWidget {\n min-width: 30px;\n max-width: 50px;\n color: Black;\n background: #CCCCCC;\n }\n\n QListWidget::Item:selected {\n background: #888888;\n border-left: 5px solid red;\n }\n HistoryPanel:hover {\n background: rgb(52, 52, 52);\n }\n \"\"\"\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n main_window = MainWindow()\n sys.exit(app.exec_())\n","<import token>\n\n\ndef QListWidget_qss():\n return \"\"\"\n QListWidget{\n outline: 0px;\n }\n\n QListWidget {\n min-width: 30px;\n max-width: 50px;\n color: Black;\n background: #CCCCCC;\n }\n\n QListWidget::Item:selected {\n background: #888888;\n border-left: 5px solid red;\n }\n HistoryPanel:hover {\n background: rgb(52, 52, 52);\n }\n \"\"\"\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n main_window = MainWindow()\n sys.exit(app.exec_())\n","<import token>\n\n\ndef QListWidget_qss():\n return \"\"\"\n QListWidget{\n outline: 0px;\n }\n\n QListWidget {\n min-width: 30px;\n max-width: 50px;\n color: Black;\n background: #CCCCCC;\n }\n\n QListWidget::Item:selected {\n background: #888888;\n border-left: 5px solid red;\n }\n HistoryPanel:hover {\n background: rgb(52, 52, 52);\n }\n \"\"\"\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n\n def getTabPage(self):\n tab_page = QStackedWidget()\n tab_page.addWidget(RecordWidget())\n tab_page.addWidget(RunWidget())\n return tab_page\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\n hbox = QHBoxLayout(spacing=0)\n hbox.setContentsMargins(0, 0, 0, 0)\n hbox.addWidget(tab_bar)\n hbox.addWidget(tab_page)\n self.setLayout(hbox)\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n <function token>\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n\n\nclass MainCentralWidget(QWidget):\n <function token>\n\n def getTabBar(self, names):\n tab_bar = QListWidget()\n tab_bar.setStyleSheet(QListWidget_qss())\n tab_bar.setFrameShape(QListWidget.NoFrame)\n tab_bar.setItemAlignment(Qt.AlignCenter)\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\n for name in names:\n item = QListWidgetItem(name)\n item.setTextAlignment(Qt.AlignCenter)\n item.setSizeHint(QSize(50, 50))\n tab_bar.addItem(item)\n tab_bar.setCurrentRow(0)\n return tab_bar\n <function token>\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n\n\nclass MainCentralWidget(QWidget):\n <function token>\n <function token>\n <function token>\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n<class token>\n\n\nclass MainWindow(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.setGeometry(50, 50, 900, 300)\n self.setWindowTitle('AutoMouse')\n self.setCentralWidget(MainCentralWidget())\n self.show()\n\n\n<code token>\n","<import token>\n<function token>\n<class token>\n\n\nclass MainWindow(QMainWindow):\n <function token>\n\n\n<code token>\n","<import token>\n<function token>\n<class token>\n<class token>\n<code token>\n"],"string":"[\n \"import sys\\nfrom collections import namedtuple\\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \\\\\\n QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\\nfrom PyQt5.QtCore import Qt, QSize\\n\\nfrom runWidget import RunWidget\\nfrom recordWidget import RecordWidget\\n\\n\\ndef QListWidget_qss():\\n return '''\\n QListWidget{\\n outline: 0px;\\n }\\n\\n QListWidget {\\n min-width: 30px;\\n max-width: 50px;\\n color: Black;\\n background: #CCCCCC;\\n }\\n\\n QListWidget::Item:selected {\\n background: #888888;\\n border-left: 5px solid red;\\n }\\n HistoryPanel:hover {\\n background: rgb(52, 52, 52);\\n }\\n '''\\n\\n\\nclass MainCentralWidget(QWidget):\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n \\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n\\n def getTabPage(self):\\n tab_page = QStackedWidget()\\n tab_page.addWidget(RecordWidget())\\n tab_page.addWidget(RunWidget())\\n return tab_page\\n\\n\\nclass MainWindow(QMainWindow):\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\nif __name__ == '__main__':\\n app = QApplication(sys.argv)\\n main_window = MainWindow()\\n sys.exit(app.exec_())\",\n \"import sys\\nfrom collections import namedtuple\\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\\nfrom PyQt5.QtCore import Qt, QSize\\nfrom runWidget import RunWidget\\nfrom recordWidget import RecordWidget\\n\\n\\ndef QListWidget_qss():\\n return \\\"\\\"\\\"\\n QListWidget{\\n outline: 0px;\\n }\\n\\n QListWidget {\\n min-width: 30px;\\n max-width: 50px;\\n color: Black;\\n background: #CCCCCC;\\n }\\n\\n QListWidget::Item:selected {\\n background: #888888;\\n border-left: 5px solid red;\\n }\\n HistoryPanel:hover {\\n background: rgb(52, 52, 52);\\n }\\n \\\"\\\"\\\"\\n\\n\\nclass MainCentralWidget(QWidget):\\n\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n\\n def getTabPage(self):\\n tab_page = QStackedWidget()\\n tab_page.addWidget(RecordWidget())\\n tab_page.addWidget(RunWidget())\\n return tab_page\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\nif __name__ == '__main__':\\n app = QApplication(sys.argv)\\n main_window = MainWindow()\\n sys.exit(app.exec_())\\n\",\n \"<import token>\\n\\n\\ndef QListWidget_qss():\\n return \\\"\\\"\\\"\\n QListWidget{\\n outline: 0px;\\n }\\n\\n QListWidget {\\n min-width: 30px;\\n max-width: 50px;\\n color: Black;\\n background: #CCCCCC;\\n }\\n\\n QListWidget::Item:selected {\\n background: #888888;\\n border-left: 5px solid red;\\n }\\n HistoryPanel:hover {\\n background: rgb(52, 52, 52);\\n }\\n \\\"\\\"\\\"\\n\\n\\nclass MainCentralWidget(QWidget):\\n\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n\\n def getTabPage(self):\\n tab_page = QStackedWidget()\\n tab_page.addWidget(RecordWidget())\\n tab_page.addWidget(RunWidget())\\n return tab_page\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\nif __name__ == '__main__':\\n app = QApplication(sys.argv)\\n main_window = MainWindow()\\n sys.exit(app.exec_())\\n\",\n \"<import token>\\n\\n\\ndef QListWidget_qss():\\n return \\\"\\\"\\\"\\n QListWidget{\\n outline: 0px;\\n }\\n\\n QListWidget {\\n min-width: 30px;\\n max-width: 50px;\\n color: Black;\\n background: #CCCCCC;\\n }\\n\\n QListWidget::Item:selected {\\n background: #888888;\\n border-left: 5px solid red;\\n }\\n HistoryPanel:hover {\\n background: rgb(52, 52, 52);\\n }\\n \\\"\\\"\\\"\\n\\n\\nclass MainCentralWidget(QWidget):\\n\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n\\n def getTabPage(self):\\n tab_page = QStackedWidget()\\n tab_page.addWidget(RecordWidget())\\n tab_page.addWidget(RunWidget())\\n return tab_page\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n\\n\\nclass MainCentralWidget(QWidget):\\n\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n\\n def getTabPage(self):\\n tab_page = QStackedWidget()\\n tab_page.addWidget(RecordWidget())\\n tab_page.addWidget(RunWidget())\\n return tab_page\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n\\n\\nclass MainCentralWidget(QWidget):\\n\\n def __init__(self):\\n super().__init__()\\n tab_bar = self.getTabBar(('录制', '运行'))\\n tab_page = self.getTabPage()\\n tab_bar.currentRowChanged.connect(tab_page.setCurrentIndex)\\n hbox = QHBoxLayout(spacing=0)\\n hbox.setContentsMargins(0, 0, 0, 0)\\n hbox.addWidget(tab_bar)\\n hbox.addWidget(tab_page)\\n self.setLayout(hbox)\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n <function token>\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n\\n\\nclass MainCentralWidget(QWidget):\\n <function token>\\n\\n def getTabBar(self, names):\\n tab_bar = QListWidget()\\n tab_bar.setStyleSheet(QListWidget_qss())\\n tab_bar.setFrameShape(QListWidget.NoFrame)\\n tab_bar.setItemAlignment(Qt.AlignCenter)\\n tab_bar.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)\\n for name in names:\\n item = QListWidgetItem(name)\\n item.setTextAlignment(Qt.AlignCenter)\\n item.setSizeHint(QSize(50, 50))\\n tab_bar.addItem(item)\\n tab_bar.setCurrentRow(0)\\n return tab_bar\\n <function token>\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n\\n\\nclass MainCentralWidget(QWidget):\\n <function token>\\n <function token>\\n <function token>\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n<class token>\\n\\n\\nclass MainWindow(QMainWindow):\\n\\n def __init__(self):\\n super().__init__()\\n self.setGeometry(50, 50, 900, 300)\\n self.setWindowTitle('AutoMouse')\\n self.setCentralWidget(MainCentralWidget())\\n self.show()\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n<class token>\\n\\n\\nclass MainWindow(QMainWindow):\\n <function token>\\n\\n\\n<code token>\\n\",\n \"<import token>\\n<function token>\\n<class token>\\n<class token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8694,"cells":{"index":{"kind":"number","value":8694,"string":"8,694"},"blob_id":{"kind":"string","value":"57bc34c6a23c98fd031ea6634441d4d135c06590"},"code":{"kind":"string","value":"import sys\nsys.path.append(\"./\")\nfrom torchtext.datasets import Multi30k\nfrom torchtext.data import Field\nfrom torchtext import data\nimport pickle\nimport models.transformer as h\nimport torch\nfrom datasets import load_dataset\nfrom torch.utils.data import DataLoader\nfrom metrics.metrics import bleu\nimport numpy as np\nfrom torch.autograd import Variable\nfrom utils import plot_training_curve,plot_loss_curves\nfrom torch import nn\nimport torch\nimport time\nimport matplotlib.pyplot as plt\nimport seaborn\n\nglobal max_src_in_batch, max_tgt_in_batch\ndef batch_size_fn(new, count, sofar):\n \"Keep augmenting batch and calculate total number of tokens + padding.\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)[\"src\"]))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)[\"trg\"]) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\nclass Batch:\n \"Object for holding a batch of data with mask during training.\"\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = \\\n self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n \n @staticmethod\n def make_std_mask(tgt, pad):\n \"Create a mask to hide padding and future words.\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(\n subsequent_mask(tgt.size(-1)).type_as(tgt_mask.data))\n return tgt_mask\nclass MyIterator(data.Iterator):\n def create_batches(self):\n if self.train:\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(\n sorted(p, key=self.sort_key),\n self.batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n \n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size,\n self.batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\ndef subsequent_mask(size):\n \"Mask out subsequent positions.\"\n attn_shape = (1, size, size)\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len-1):\n out = model.decode(memory, src_mask, \n Variable(ys), \n Variable(subsequent_mask(ys.size(1))\n .type_as(src.data)))\n prob = model.generator(out[:, -1])\n # vals, idxs = torch.topk(torch.softmax(prob, dim=1).flatten(), 10, largest=True)\n # print((vals*100).tolist())\n # print([TRG.vocab.itos[idx] for idx in idxs])\n _, next_word = torch.max(prob, dim = 1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, \n torch.ones(1, 1).type_as(src.data).fill_(next_word)], dim=1)\n return ys\ndef visualise_attention(tgt_sent, sent):\n def draw(data, x, y, ax):\n seaborn.heatmap(data, \n xticklabels=x, square=True, yticklabels=y, vmin=0.0, vmax=1.0, \n cbar=False, ax=ax)\n # bottom, top = ax.get_ylim()\n # ax.set_ylim(bottom + 0.5, top - 0.5)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n print(\"Encoder Layer\", layer+1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h ==0 else [], ax=axs[h])\n plt.show()\n \n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n print(\"Decoder Self Layer\", layer+1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h ==0 else [], ax=axs[h])\n plt.show()\n print(\"Decoder Src Layer\", layer+1)\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h ==0 else [], ax=axs[h])\n plt.show()\nclass SimpleLossCompute:\n \"A simple loss compute and train function.\"\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n \n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), \n y.contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\ndef rebatch(pad_idx, batch):\n \"Fix order in torchtext to match ours\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter), model, \n SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\ndef run_epoch(data_iter, model, loss_compute):\n \"Standard Training and Logging Function\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, \n batch.src_mask, batch.trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens) #/ batch.ntokens\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print(\"Epoch Step: %d Loss: %f Tokens per Sec: %f\" %\n (i, loss, tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\nSRC = Field(tokenize = \"spacy\",\n tokenizer_language=\"de_core_news_sm\",\n init_token = '<sos>',\n eos_token = '<eos>',\n lower = True)\n\nTRG = Field(tokenize = \"spacy\",\n tokenizer_language=\"en_core_web_sm\",\n init_token = '<sos>',\n eos_token = '<eos>',\n lower = True)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n\nMAX_LEN = 100\ntrain_data, valid_data, test_data = Multi30k.splits(exts = ('.de', '.en'),fields = (SRC, TRG)\n ,filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and len(vars(x)['trg']) <= MAX_LEN)\nSRC.build_vocab(train_data.src, min_freq=2)\nTRG.build_vocab(train_data.trg, min_freq=2)\nINPUT_DIM = len(SRC.vocab)\nOUTPUT_DIM = len(TRG.vocab)\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\nBATCH_SIZE = 64\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=True)\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\n\nmodel_name = \"harvard_transformer2_state\"\nargs = (INPUT_DIM, OUTPUT_DIM)\nkwargs = {\"N\" : 6}\nmodel = h.make_model(*args, **kwargs).to(device)\n\nstate = torch.load(model_name + \".pt\", map_location=device)\nmodel.load_state_dict(state[\"state_dict\"])\nlosses = state[\"loss\"]\n\npad_idx = TRG.vocab.stoi[\"<pad>\"]\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\n\ntest_losses = evaluate(test_iter, model, criterion_test)\nlosses[\"test\"].append(test_losses)\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\nprint(test_loss)\nprint('Perplexity:', torch.exp(test_loss))\n\n# sentence = [SRC.preprocess(\"eine gruppe von menschen steht vor einem iglu .\")]\n# real_translation = TRG.preprocess(\"a man in a blue shirt is standing on a ladder and cleaning a window\")\n# sentence = [SRC.preprocess(\"eine gruppe von menschen steht vor einem iglu .\")]\n# real_translation = TRG.preprocess(\"a group of people stands in front of an igloo.\")\nsentence = [SRC.preprocess(\"ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .\")]\nreal_translation = TRG.preprocess(\"a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .\")\n\nsrc = SRC.process(sentence).to(device).T\nsrc_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\nmodel.eval()\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\ntranslation = [\"<sos>\"]\nfor i in range(1, out.size(1)):\n sym = TRG.vocab.itos[out[0, i]]\n translation.append(sym)\n if sym == \"<eos>\":\n break\nprint(' '.join(translation))\nprint(' '.join(real_translation))\n\n# plot_loss_curves(losses[\"train\"], losses[\"val\"])\n\nvisualise_attention(translation, [\"<sos>\"] + sentence[0] + [\"<eos>\"])\n\n# candidate = []\n# reference = []\n# for i, batch in enumerate(test_iter):\n# src = batch.src.transpose(0, 1)[:1]\n# src_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\n# model.eval()\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\n\n# translation = []\n# for i in range(1, out.size(1)):\n# sym = TRG.vocab.itos[out[0, i]]\n# if sym == \"<eos>\": break\n# translation.append(sym)\n# print(\"Translation: \\t\", ' '.join(translation))\n# target = []\n# for i in range(1, batch.trg.size(0)):\n# sym = TRG.vocab.itos[batch.trg.data[i, 0]]\n# if sym == \"<eos>\": break\n# target.append(sym)\n# print(\"Target: \\t\", ' '.join(target))\n# print()\n\n# candidate.append(translation)\n# reference.append([target])\n\n# score = bleu(candidate, reference)\n# print(score)\n# # state[\"bleu\"] = bleu\n# # save_model_state(\"harvard_transformer2_state.pt\", model, {\"args\" : args, \"kwargs\" : kwargs}, epoch+1, state[\"loss\"], state[\"bleu\"])\n\n\n# dataset = load_dataset('wmt14', 'de-en', 'test')['test']['translation']\n# trainloader = DataLoader(dataset, batch_size=1, shuffle=True)\n\n# model.eval()\n\n# candidate = []\n# reference = []\n# for val in trainloader:\n# de=val['de']\n# en=val['en']\n\n# de_tokens = [SRC.preprocess(sentence) for sentence in de]\n# en_tokens = [TRG.preprocess(sentence) for sentence in en]\n# src = SRC.process(de_tokens).to(device).T[:1]\n# trg = TRG.process(en_tokens).to(device).T[:1]\n# src_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\n\n# translation = []\n# for i in range(1, out.size(1)):\n# sym = TRG.vocab.itos[out[0, i]]\n# if sym == \"<eos>\": break\n# translation.append(sym)\n# target = []\n# for i in range(1, trg.size(1)):\n# sym = TRG.vocab.itos[trg[0, i]]\n# if sym == \"<eos>\": break\n# target.append(sym)\n# candidate.append(translation)\n# reference.append([target])\n\n# print(bleu(candidate, reference))\n"},"steps":{"kind":"list like","value":["import sys\nsys.path.append(\"./\")\nfrom torchtext.datasets import Multi30k\nfrom torchtext.data import Field\nfrom torchtext import data\nimport pickle\nimport models.transformer as h\nimport torch\nfrom datasets import load_dataset\nfrom torch.utils.data import DataLoader\nfrom metrics.metrics import bleu\nimport numpy as np\nfrom torch.autograd import Variable\nfrom utils import plot_training_curve,plot_loss_curves\nfrom torch import nn\nimport torch\nimport time\nimport matplotlib.pyplot as plt\nimport seaborn\n\nglobal max_src_in_batch, max_tgt_in_batch\ndef batch_size_fn(new, count, sofar):\n \"Keep augmenting batch and calculate total number of tokens + padding.\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)[\"src\"]))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)[\"trg\"]) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\nclass Batch:\n \"Object for holding a batch of data with mask during training.\"\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = \\\n self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n \n @staticmethod\n def make_std_mask(tgt, pad):\n \"Create a mask to hide padding and future words.\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(\n subsequent_mask(tgt.size(-1)).type_as(tgt_mask.data))\n return tgt_mask\nclass MyIterator(data.Iterator):\n def create_batches(self):\n if self.train:\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(\n sorted(p, key=self.sort_key),\n self.batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n \n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size,\n self.batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\ndef subsequent_mask(size):\n \"Mask out subsequent positions.\"\n attn_shape = (1, size, size)\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len-1):\n out = model.decode(memory, src_mask, \n Variable(ys), \n Variable(subsequent_mask(ys.size(1))\n .type_as(src.data)))\n prob = model.generator(out[:, -1])\n # vals, idxs = torch.topk(torch.softmax(prob, dim=1).flatten(), 10, largest=True)\n # print((vals*100).tolist())\n # print([TRG.vocab.itos[idx] for idx in idxs])\n _, next_word = torch.max(prob, dim = 1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, \n torch.ones(1, 1).type_as(src.data).fill_(next_word)], dim=1)\n return ys\ndef visualise_attention(tgt_sent, sent):\n def draw(data, x, y, ax):\n seaborn.heatmap(data, \n xticklabels=x, square=True, yticklabels=y, vmin=0.0, vmax=1.0, \n cbar=False, ax=ax)\n # bottom, top = ax.get_ylim()\n # ax.set_ylim(bottom + 0.5, top - 0.5)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n print(\"Encoder Layer\", layer+1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h ==0 else [], ax=axs[h])\n plt.show()\n \n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n print(\"Decoder Self Layer\", layer+1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h ==0 else [], ax=axs[h])\n plt.show()\n print(\"Decoder Src Layer\", layer+1)\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h ==0 else [], ax=axs[h])\n plt.show()\nclass SimpleLossCompute:\n \"A simple loss compute and train function.\"\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n \n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), \n y.contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\ndef rebatch(pad_idx, batch):\n \"Fix order in torchtext to match ours\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter), model, \n SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\ndef run_epoch(data_iter, model, loss_compute):\n \"Standard Training and Logging Function\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, \n batch.src_mask, batch.trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens) #/ batch.ntokens\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print(\"Epoch Step: %d Loss: %f Tokens per Sec: %f\" %\n (i, loss, tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\nSRC = Field(tokenize = \"spacy\",\n tokenizer_language=\"de_core_news_sm\",\n init_token = '<sos>',\n eos_token = '<eos>',\n lower = True)\n\nTRG = Field(tokenize = \"spacy\",\n tokenizer_language=\"en_core_web_sm\",\n init_token = '<sos>',\n eos_token = '<eos>',\n lower = True)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n\nMAX_LEN = 100\ntrain_data, valid_data, test_data = Multi30k.splits(exts = ('.de', '.en'),fields = (SRC, TRG)\n ,filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and len(vars(x)['trg']) <= MAX_LEN)\nSRC.build_vocab(train_data.src, min_freq=2)\nTRG.build_vocab(train_data.trg, min_freq=2)\nINPUT_DIM = len(SRC.vocab)\nOUTPUT_DIM = len(TRG.vocab)\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\nBATCH_SIZE = 64\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=True)\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\n\nmodel_name = \"harvard_transformer2_state\"\nargs = (INPUT_DIM, OUTPUT_DIM)\nkwargs = {\"N\" : 6}\nmodel = h.make_model(*args, **kwargs).to(device)\n\nstate = torch.load(model_name + \".pt\", map_location=device)\nmodel.load_state_dict(state[\"state_dict\"])\nlosses = state[\"loss\"]\n\npad_idx = TRG.vocab.stoi[\"<pad>\"]\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\n\ntest_losses = evaluate(test_iter, model, criterion_test)\nlosses[\"test\"].append(test_losses)\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\nprint(test_loss)\nprint('Perplexity:', torch.exp(test_loss))\n\n# sentence = [SRC.preprocess(\"eine gruppe von menschen steht vor einem iglu .\")]\n# real_translation = TRG.preprocess(\"a man in a blue shirt is standing on a ladder and cleaning a window\")\n# sentence = [SRC.preprocess(\"eine gruppe von menschen steht vor einem iglu .\")]\n# real_translation = TRG.preprocess(\"a group of people stands in front of an igloo.\")\nsentence = [SRC.preprocess(\"ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .\")]\nreal_translation = TRG.preprocess(\"a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .\")\n\nsrc = SRC.process(sentence).to(device).T\nsrc_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\nmodel.eval()\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\ntranslation = [\"<sos>\"]\nfor i in range(1, out.size(1)):\n sym = TRG.vocab.itos[out[0, i]]\n translation.append(sym)\n if sym == \"<eos>\":\n break\nprint(' '.join(translation))\nprint(' '.join(real_translation))\n\n# plot_loss_curves(losses[\"train\"], losses[\"val\"])\n\nvisualise_attention(translation, [\"<sos>\"] + sentence[0] + [\"<eos>\"])\n\n# candidate = []\n# reference = []\n# for i, batch in enumerate(test_iter):\n# src = batch.src.transpose(0, 1)[:1]\n# src_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\n# model.eval()\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\n\n# translation = []\n# for i in range(1, out.size(1)):\n# sym = TRG.vocab.itos[out[0, i]]\n# if sym == \"<eos>\": break\n# translation.append(sym)\n# print(\"Translation: \\t\", ' '.join(translation))\n# target = []\n# for i in range(1, batch.trg.size(0)):\n# sym = TRG.vocab.itos[batch.trg.data[i, 0]]\n# if sym == \"<eos>\": break\n# target.append(sym)\n# print(\"Target: \\t\", ' '.join(target))\n# print()\n\n# candidate.append(translation)\n# reference.append([target])\n\n# score = bleu(candidate, reference)\n# print(score)\n# # state[\"bleu\"] = bleu\n# # save_model_state(\"harvard_transformer2_state.pt\", model, {\"args\" : args, \"kwargs\" : kwargs}, epoch+1, state[\"loss\"], state[\"bleu\"])\n\n\n# dataset = load_dataset('wmt14', 'de-en', 'test')['test']['translation']\n# trainloader = DataLoader(dataset, batch_size=1, shuffle=True)\n\n# model.eval()\n\n# candidate = []\n# reference = []\n# for val in trainloader:\n# de=val['de']\n# en=val['en']\n\n# de_tokens = [SRC.preprocess(sentence) for sentence in de]\n# en_tokens = [TRG.preprocess(sentence) for sentence in en]\n# src = SRC.process(de_tokens).to(device).T[:1]\n# trg = TRG.process(en_tokens).to(device).T[:1]\n# src_mask = (src != SRC.vocab.stoi[\"<pad>\"]).unsqueeze(-2)\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\"<sos>\"])\n\n# translation = []\n# for i in range(1, out.size(1)):\n# sym = TRG.vocab.itos[out[0, i]]\n# if sym == \"<eos>\": break\n# translation.append(sym)\n# target = []\n# for i in range(1, trg.size(1)):\n# sym = TRG.vocab.itos[trg[0, i]]\n# if sym == \"<eos>\": break\n# target.append(sym)\n# candidate.append(translation)\n# reference.append([target])\n\n# print(bleu(candidate, reference))\n","import sys\nsys.path.append('./')\nfrom torchtext.datasets import Multi30k\nfrom torchtext.data import Field\nfrom torchtext import data\nimport pickle\nimport models.transformer as h\nimport torch\nfrom datasets import load_dataset\nfrom torch.utils.data import DataLoader\nfrom metrics.metrics import bleu\nimport numpy as np\nfrom torch.autograd import Variable\nfrom utils import plot_training_curve, plot_loss_curves\nfrom torch import nn\nimport torch\nimport time\nimport matplotlib.pyplot as plt\nimport seaborn\nglobal max_src_in_batch, max_tgt_in_batch\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\ndef subsequent_mask(size):\n \"\"\"Mask out subsequent positions.\"\"\"\n attn_shape = 1, size, size\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\ndef rebatch(pad_idx, batch):\n \"\"\"Fix order in torchtext to match ours\"\"\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\nSRC = Field(tokenize='spacy', tokenizer_language='de_core_news_sm',\n init_token='<sos>', eos_token='<eos>', lower=True)\nTRG = Field(tokenize='spacy', tokenizer_language='en_core_web_sm',\n init_token='<sos>', eos_token='<eos>', lower=True)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nMAX_LEN = 100\ntrain_data, valid_data, test_data = Multi30k.splits(exts=('.de', '.en'),\n fields=(SRC, TRG), filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and\n len(vars(x)['trg']) <= MAX_LEN)\nSRC.build_vocab(train_data.src, min_freq=2)\nTRG.build_vocab(train_data.trg, min_freq=2)\nINPUT_DIM = len(SRC.vocab)\nOUTPUT_DIM = len(TRG.vocab)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nBATCH_SIZE = 64\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=True)\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\nmodel_name = 'harvard_transformer2_state'\nargs = INPUT_DIM, OUTPUT_DIM\nkwargs = {'N': 6}\nmodel = h.make_model(*args, **kwargs).to(device)\nstate = torch.load(model_name + '.pt', map_location=device)\nmodel.load_state_dict(state['state_dict'])\nlosses = state['loss']\npad_idx = TRG.vocab.stoi['<pad>']\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\ntest_losses = evaluate(test_iter, model, criterion_test)\nlosses['test'].append(test_losses)\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\nprint(test_loss)\nprint('Perplexity:', torch.exp(test_loss))\nsentence = [SRC.preprocess(\n 'ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .'\n )]\nreal_translation = TRG.preprocess(\n 'a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .'\n )\nsrc = SRC.process(sentence).to(device).T\nsrc_mask = (src != SRC.vocab.stoi['<pad>']).unsqueeze(-2)\nmodel.eval()\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.\n vocab.stoi['<sos>'])\ntranslation = ['<sos>']\nfor i in range(1, out.size(1)):\n sym = TRG.vocab.itos[out[0, i]]\n translation.append(sym)\n if sym == '<eos>':\n break\nprint(' '.join(translation))\nprint(' '.join(real_translation))\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\n","<import token>\nsys.path.append('./')\n<import token>\nglobal max_src_in_batch, max_tgt_in_batch\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\ndef subsequent_mask(size):\n \"\"\"Mask out subsequent positions.\"\"\"\n attn_shape = 1, size, size\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\ndef rebatch(pad_idx, batch):\n \"\"\"Fix order in torchtext to match ours\"\"\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\nSRC = Field(tokenize='spacy', tokenizer_language='de_core_news_sm',\n init_token='<sos>', eos_token='<eos>', lower=True)\nTRG = Field(tokenize='spacy', tokenizer_language='en_core_web_sm',\n init_token='<sos>', eos_token='<eos>', lower=True)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nMAX_LEN = 100\ntrain_data, valid_data, test_data = Multi30k.splits(exts=('.de', '.en'),\n fields=(SRC, TRG), filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and\n len(vars(x)['trg']) <= MAX_LEN)\nSRC.build_vocab(train_data.src, min_freq=2)\nTRG.build_vocab(train_data.trg, min_freq=2)\nINPUT_DIM = len(SRC.vocab)\nOUTPUT_DIM = len(TRG.vocab)\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nBATCH_SIZE = 64\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=True)\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\n batch_size_fn=batch_size_fn, train=False)\nmodel_name = 'harvard_transformer2_state'\nargs = INPUT_DIM, OUTPUT_DIM\nkwargs = {'N': 6}\nmodel = h.make_model(*args, **kwargs).to(device)\nstate = torch.load(model_name + '.pt', map_location=device)\nmodel.load_state_dict(state['state_dict'])\nlosses = state['loss']\npad_idx = TRG.vocab.stoi['<pad>']\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\ntest_losses = evaluate(test_iter, model, criterion_test)\nlosses['test'].append(test_losses)\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\nprint(test_loss)\nprint('Perplexity:', torch.exp(test_loss))\nsentence = [SRC.preprocess(\n 'ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .'\n )]\nreal_translation = TRG.preprocess(\n 'a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .'\n )\nsrc = SRC.process(sentence).to(device).T\nsrc_mask = (src != SRC.vocab.stoi['<pad>']).unsqueeze(-2)\nmodel.eval()\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.\n vocab.stoi['<sos>'])\ntranslation = ['<sos>']\nfor i in range(1, out.size(1)):\n sym = TRG.vocab.itos[out[0, i]]\n translation.append(sym)\n if sym == '<eos>':\n break\nprint(' '.join(translation))\nprint(' '.join(real_translation))\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\n","<import token>\nsys.path.append('./')\n<import token>\nglobal max_src_in_batch, max_tgt_in_batch\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\ndef subsequent_mask(size):\n \"\"\"Mask out subsequent positions.\"\"\"\n attn_shape = 1, size, size\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\ndef rebatch(pad_idx, batch):\n \"\"\"Fix order in torchtext to match ours\"\"\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\nSRC.build_vocab(train_data.src, min_freq=2)\nTRG.build_vocab(train_data.trg, min_freq=2)\n<assignment token>\nmodel.load_state_dict(state['state_dict'])\n<assignment token>\nlosses['test'].append(test_losses)\n<assignment token>\nprint(test_loss)\nprint('Perplexity:', torch.exp(test_loss))\n<assignment token>\nmodel.eval()\n<assignment token>\nfor i in range(1, out.size(1)):\n sym = TRG.vocab.itos[out[0, i]]\n translation.append(sym)\n if sym == '<eos>':\n break\nprint(' '.join(translation))\nprint(' '.join(real_translation))\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\ndef subsequent_mask(size):\n \"\"\"Mask out subsequent positions.\"\"\"\n attn_shape = 1, size, size\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\ndef rebatch(pad_idx, batch):\n \"\"\"Fix order in torchtext to match ours\"\"\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\ndef rebatch(pad_idx, batch):\n \"\"\"Fix order in torchtext to match ours\"\"\"\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\n return Batch(src, trg, pad_idx)\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n\n\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\n memory = model.encode(src, src_mask)\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\n for i in range(max_len - 1):\n out = model.decode(memory, src_mask, Variable(ys), Variable(\n subsequent_mask(ys.size(1)).type_as(src.data)))\n prob = model.generator(out[:, -1])\n _, next_word = torch.max(prob, dim=1)\n next_word = next_word.data[0]\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\n next_word)], dim=1)\n return ys\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n\n\ndef evaluate(data_iter, model, criterion):\n model.eval()\n with torch.no_grad():\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\n model, SimpleLossCompute(model.generator, criterion, opt=None))\n return eval_loss\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n\n\ndef run_epoch(data_iter, model, loss_compute):\n \"\"\"Standard Training and Logging Function\"\"\"\n start = time.time()\n total_tokens = 0\n total_loss = []\n tokens = 0\n for i, batch in enumerate(data_iter):\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\n trg_mask)\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\n total_loss.append(loss.item())\n total_tokens += batch.ntokens\n tokens += batch.ntokens\n if i % 50 == 1:\n elapsed = time.time() - start\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \n tokens / elapsed))\n start = time.time()\n tokens = 0\n return total_loss\n\n\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n\n\ndef batch_size_fn(new, count, sofar):\n \"\"\"Keep augmenting batch and calculate total number of tokens + padding.\"\"\"\n global max_src_in_batch, max_tgt_in_batch\n if count == 1:\n max_src_in_batch = 0\n max_tgt_in_batch = 0\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\n src_elements = count * max_src_in_batch\n tgt_elements = count * max_tgt_in_batch\n return max(src_elements, tgt_elements)\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n\n\ndef visualise_attention(tgt_sent, sent):\n\n def draw(data, x, y, ax):\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Encoder Layer', layer + 1)\n for h in range(4):\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\n plt.show()\n for layer in range(1, 6, 2):\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n print('Decoder Self Layer', layer + 1)\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(tgt_sent)].cpu()\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n print('Decoder Src Layer', layer + 1)\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\n for h in range(4):\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\n len(tgt_sent), :len(sent)].cpu()\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\n plt.show()\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n\n\nclass Batch:\n \"\"\"Object for holding a batch of data with mask during training.\"\"\"\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n\n\nclass Batch:\n <docstring token>\n\n def __init__(self, src, trg=None, pad=0):\n self.src = src\n self.src_mask = (src != pad).unsqueeze(-2)\n if trg is not None:\n self.trg = trg[:, :-1]\n self.trg_y = trg[:, 1:]\n self.trg_mask = self.make_std_mask(self.trg, pad)\n self.ntokens = (self.trg_y != pad).data.sum()\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n\n\nclass Batch:\n <docstring token>\n <function token>\n\n @staticmethod\n def make_std_mask(tgt, pad):\n \"\"\"Create a mask to hide padding and future words.\"\"\"\n tgt_mask = (tgt != pad).unsqueeze(-2)\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\n type_as(tgt_mask.data))\n return tgt_mask\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n\n\nclass Batch:\n <docstring token>\n <function token>\n <function token>\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n\n\nclass MyIterator(data.Iterator):\n\n def create_batches(self):\n if self.train:\n\n def pool(d, random_shuffler):\n for p in data.batch(d, self.batch_size * 100):\n p_batch = data.batch(sorted(p, key=self.sort_key), self\n .batch_size, self.batch_size_fn)\n for b in random_shuffler(list(p_batch)):\n yield b\n self.batches = pool(self.data(), self.random_shuffler)\n else:\n self.batches = []\n for b in data.batch(self.data(), self.batch_size, self.\n batch_size_fn):\n self.batches.append(sorted(b, key=self.sort_key))\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n\n\nclass MyIterator(data.Iterator):\n <function token>\n\n\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n<class token>\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n \"\"\"A simple loss compute and train function.\"\"\"\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n<class token>\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n <docstring token>\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n\n def __call__(self, x, y, norm):\n x = self.generator(x)\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\n contiguous().view(-1)) / norm\n if self.opt is not None:\n loss.backward()\n self.opt.step()\n self.opt.optimizer.zero_grad()\n return loss.data.item() * norm\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n<class token>\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n <docstring token>\n\n def __init__(self, generator, criterion, opt=None):\n self.generator = generator\n self.criterion = criterion\n self.opt = opt\n <function token>\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n<class token>\n<function token>\n<function token>\n<function token>\n\n\nclass SimpleLossCompute:\n <docstring token>\n <function token>\n <function token>\n\n\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<code token>\n<function token>\n<class token>\n<class token>\n<function token>\n<function token>\n<function token>\n<class token>\n<function token>\n<function token>\n<function token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n<assignment token>\n<code token>\n"],"string":"[\n \"import sys\\nsys.path.append(\\\"./\\\")\\nfrom torchtext.datasets import Multi30k\\nfrom torchtext.data import Field\\nfrom torchtext import data\\nimport pickle\\nimport models.transformer as h\\nimport torch\\nfrom datasets import load_dataset\\nfrom torch.utils.data import DataLoader\\nfrom metrics.metrics import bleu\\nimport numpy as np\\nfrom torch.autograd import Variable\\nfrom utils import plot_training_curve,plot_loss_curves\\nfrom torch import nn\\nimport torch\\nimport time\\nimport matplotlib.pyplot as plt\\nimport seaborn\\n\\nglobal max_src_in_batch, max_tgt_in_batch\\ndef batch_size_fn(new, count, sofar):\\n \\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)[\\\"src\\\"]))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)[\\\"trg\\\"]) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\nclass Batch:\\n \\\"Object for holding a batch of data with mask during training.\\\"\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = \\\\\\n self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n \\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"Create a mask to hide padding and future words.\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(\\n subsequent_mask(tgt.size(-1)).type_as(tgt_mask.data))\\n return tgt_mask\\nclass MyIterator(data.Iterator):\\n def create_batches(self):\\n if self.train:\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(\\n sorted(p, key=self.sort_key),\\n self.batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n \\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size,\\n self.batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\ndef subsequent_mask(size):\\n \\\"Mask out subsequent positions.\\\"\\n attn_shape = (1, size, size)\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len-1):\\n out = model.decode(memory, src_mask, \\n Variable(ys), \\n Variable(subsequent_mask(ys.size(1))\\n .type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n # vals, idxs = torch.topk(torch.softmax(prob, dim=1).flatten(), 10, largest=True)\\n # print((vals*100).tolist())\\n # print([TRG.vocab.itos[idx] for idx in idxs])\\n _, next_word = torch.max(prob, dim = 1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, \\n torch.ones(1, 1).type_as(src.data).fill_(next_word)], dim=1)\\n return ys\\ndef visualise_attention(tgt_sent, sent):\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, \\n xticklabels=x, square=True, yticklabels=y, vmin=0.0, vmax=1.0, \\n cbar=False, ax=ax)\\n # bottom, top = ax.get_ylim()\\n # ax.set_ylim(bottom + 0.5, top - 0.5)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\\n print(\\\"Encoder Layer\\\", layer+1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h ==0 else [], ax=axs[h])\\n plt.show()\\n \\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\\n print(\\\"Decoder Self Layer\\\", layer+1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h ==0 else [], ax=axs[h])\\n plt.show()\\n print(\\\"Decoder Src Layer\\\", layer+1)\\n fig, axs = plt.subplots(1,4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h ==0 else [], ax=axs[h])\\n plt.show()\\nclass SimpleLossCompute:\\n \\\"A simple loss compute and train function.\\\"\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n \\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), \\n y.contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\ndef rebatch(pad_idx, batch):\\n \\\"Fix order in torchtext to match ours\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter), model, \\n SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"Standard Training and Logging Function\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, \\n batch.src_mask, batch.trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens) #/ batch.ntokens\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print(\\\"Epoch Step: %d Loss: %f Tokens per Sec: %f\\\" %\\n (i, loss, tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\nSRC = Field(tokenize = \\\"spacy\\\",\\n tokenizer_language=\\\"de_core_news_sm\\\",\\n init_token = '<sos>',\\n eos_token = '<eos>',\\n lower = True)\\n\\nTRG = Field(tokenize = \\\"spacy\\\",\\n tokenizer_language=\\\"en_core_web_sm\\\",\\n init_token = '<sos>',\\n eos_token = '<eos>',\\n lower = True)\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\n\\n\\nMAX_LEN = 100\\ntrain_data, valid_data, test_data = Multi30k.splits(exts = ('.de', '.en'),fields = (SRC, TRG)\\n ,filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and len(vars(x)['trg']) <= MAX_LEN)\\nSRC.build_vocab(train_data.src, min_freq=2)\\nTRG.build_vocab(train_data.trg, min_freq=2)\\nINPUT_DIM = len(SRC.vocab)\\nOUTPUT_DIM = len(TRG.vocab)\\n\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\n\\nBATCH_SIZE = 64\\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=True)\\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\n\\nmodel_name = \\\"harvard_transformer2_state\\\"\\nargs = (INPUT_DIM, OUTPUT_DIM)\\nkwargs = {\\\"N\\\" : 6}\\nmodel = h.make_model(*args, **kwargs).to(device)\\n\\nstate = torch.load(model_name + \\\".pt\\\", map_location=device)\\nmodel.load_state_dict(state[\\\"state_dict\\\"])\\nlosses = state[\\\"loss\\\"]\\n\\npad_idx = TRG.vocab.stoi[\\\"<pad>\\\"]\\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\\n\\ntest_losses = evaluate(test_iter, model, criterion_test)\\nlosses[\\\"test\\\"].append(test_losses)\\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\\nprint(test_loss)\\nprint('Perplexity:', torch.exp(test_loss))\\n\\n# sentence = [SRC.preprocess(\\\"eine gruppe von menschen steht vor einem iglu .\\\")]\\n# real_translation = TRG.preprocess(\\\"a man in a blue shirt is standing on a ladder and cleaning a window\\\")\\n# sentence = [SRC.preprocess(\\\"eine gruppe von menschen steht vor einem iglu .\\\")]\\n# real_translation = TRG.preprocess(\\\"a group of people stands in front of an igloo.\\\")\\nsentence = [SRC.preprocess(\\\"ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .\\\")]\\nreal_translation = TRG.preprocess(\\\"a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .\\\")\\n\\nsrc = SRC.process(sentence).to(device).T\\nsrc_mask = (src != SRC.vocab.stoi[\\\"<pad>\\\"]).unsqueeze(-2)\\nmodel.eval()\\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\\\"<sos>\\\"])\\ntranslation = [\\\"<sos>\\\"]\\nfor i in range(1, out.size(1)):\\n sym = TRG.vocab.itos[out[0, i]]\\n translation.append(sym)\\n if sym == \\\"<eos>\\\":\\n break\\nprint(' '.join(translation))\\nprint(' '.join(real_translation))\\n\\n# plot_loss_curves(losses[\\\"train\\\"], losses[\\\"val\\\"])\\n\\nvisualise_attention(translation, [\\\"<sos>\\\"] + sentence[0] + [\\\"<eos>\\\"])\\n\\n# candidate = []\\n# reference = []\\n# for i, batch in enumerate(test_iter):\\n# src = batch.src.transpose(0, 1)[:1]\\n# src_mask = (src != SRC.vocab.stoi[\\\"<pad>\\\"]).unsqueeze(-2)\\n# model.eval()\\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\\\"<sos>\\\"])\\n\\n# translation = []\\n# for i in range(1, out.size(1)):\\n# sym = TRG.vocab.itos[out[0, i]]\\n# if sym == \\\"<eos>\\\": break\\n# translation.append(sym)\\n# print(\\\"Translation: \\\\t\\\", ' '.join(translation))\\n# target = []\\n# for i in range(1, batch.trg.size(0)):\\n# sym = TRG.vocab.itos[batch.trg.data[i, 0]]\\n# if sym == \\\"<eos>\\\": break\\n# target.append(sym)\\n# print(\\\"Target: \\\\t\\\", ' '.join(target))\\n# print()\\n\\n# candidate.append(translation)\\n# reference.append([target])\\n\\n# score = bleu(candidate, reference)\\n# print(score)\\n# # state[\\\"bleu\\\"] = bleu\\n# # save_model_state(\\\"harvard_transformer2_state.pt\\\", model, {\\\"args\\\" : args, \\\"kwargs\\\" : kwargs}, epoch+1, state[\\\"loss\\\"], state[\\\"bleu\\\"])\\n\\n\\n# dataset = load_dataset('wmt14', 'de-en', 'test')['test']['translation']\\n# trainloader = DataLoader(dataset, batch_size=1, shuffle=True)\\n\\n# model.eval()\\n\\n# candidate = []\\n# reference = []\\n# for val in trainloader:\\n# de=val['de']\\n# en=val['en']\\n\\n# de_tokens = [SRC.preprocess(sentence) for sentence in de]\\n# en_tokens = [TRG.preprocess(sentence) for sentence in en]\\n# src = SRC.process(de_tokens).to(device).T[:1]\\n# trg = TRG.process(en_tokens).to(device).T[:1]\\n# src_mask = (src != SRC.vocab.stoi[\\\"<pad>\\\"]).unsqueeze(-2)\\n# out = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.vocab.stoi[\\\"<sos>\\\"])\\n\\n# translation = []\\n# for i in range(1, out.size(1)):\\n# sym = TRG.vocab.itos[out[0, i]]\\n# if sym == \\\"<eos>\\\": break\\n# translation.append(sym)\\n# target = []\\n# for i in range(1, trg.size(1)):\\n# sym = TRG.vocab.itos[trg[0, i]]\\n# if sym == \\\"<eos>\\\": break\\n# target.append(sym)\\n# candidate.append(translation)\\n# reference.append([target])\\n\\n# print(bleu(candidate, reference))\\n\",\n \"import sys\\nsys.path.append('./')\\nfrom torchtext.datasets import Multi30k\\nfrom torchtext.data import Field\\nfrom torchtext import data\\nimport pickle\\nimport models.transformer as h\\nimport torch\\nfrom datasets import load_dataset\\nfrom torch.utils.data import DataLoader\\nfrom metrics.metrics import bleu\\nimport numpy as np\\nfrom torch.autograd import Variable\\nfrom utils import plot_training_curve, plot_loss_curves\\nfrom torch import nn\\nimport torch\\nimport time\\nimport matplotlib.pyplot as plt\\nimport seaborn\\nglobal max_src_in_batch, max_tgt_in_batch\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\ndef subsequent_mask(size):\\n \\\"\\\"\\\"Mask out subsequent positions.\\\"\\\"\\\"\\n attn_shape = 1, size, size\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\ndef rebatch(pad_idx, batch):\\n \\\"\\\"\\\"Fix order in torchtext to match ours\\\"\\\"\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\nSRC = Field(tokenize='spacy', tokenizer_language='de_core_news_sm',\\n init_token='<sos>', eos_token='<eos>', lower=True)\\nTRG = Field(tokenize='spacy', tokenizer_language='en_core_web_sm',\\n init_token='<sos>', eos_token='<eos>', lower=True)\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\nMAX_LEN = 100\\ntrain_data, valid_data, test_data = Multi30k.splits(exts=('.de', '.en'),\\n fields=(SRC, TRG), filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and\\n len(vars(x)['trg']) <= MAX_LEN)\\nSRC.build_vocab(train_data.src, min_freq=2)\\nTRG.build_vocab(train_data.trg, min_freq=2)\\nINPUT_DIM = len(SRC.vocab)\\nOUTPUT_DIM = len(TRG.vocab)\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\nBATCH_SIZE = 64\\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=True)\\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\nmodel_name = 'harvard_transformer2_state'\\nargs = INPUT_DIM, OUTPUT_DIM\\nkwargs = {'N': 6}\\nmodel = h.make_model(*args, **kwargs).to(device)\\nstate = torch.load(model_name + '.pt', map_location=device)\\nmodel.load_state_dict(state['state_dict'])\\nlosses = state['loss']\\npad_idx = TRG.vocab.stoi['<pad>']\\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\\ntest_losses = evaluate(test_iter, model, criterion_test)\\nlosses['test'].append(test_losses)\\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\\nprint(test_loss)\\nprint('Perplexity:', torch.exp(test_loss))\\nsentence = [SRC.preprocess(\\n 'ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .'\\n )]\\nreal_translation = TRG.preprocess(\\n 'a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .'\\n )\\nsrc = SRC.process(sentence).to(device).T\\nsrc_mask = (src != SRC.vocab.stoi['<pad>']).unsqueeze(-2)\\nmodel.eval()\\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.\\n vocab.stoi['<sos>'])\\ntranslation = ['<sos>']\\nfor i in range(1, out.size(1)):\\n sym = TRG.vocab.itos[out[0, i]]\\n translation.append(sym)\\n if sym == '<eos>':\\n break\\nprint(' '.join(translation))\\nprint(' '.join(real_translation))\\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\\n\",\n \"<import token>\\nsys.path.append('./')\\n<import token>\\nglobal max_src_in_batch, max_tgt_in_batch\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\ndef subsequent_mask(size):\\n \\\"\\\"\\\"Mask out subsequent positions.\\\"\\\"\\\"\\n attn_shape = 1, size, size\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\ndef rebatch(pad_idx, batch):\\n \\\"\\\"\\\"Fix order in torchtext to match ours\\\"\\\"\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\nSRC = Field(tokenize='spacy', tokenizer_language='de_core_news_sm',\\n init_token='<sos>', eos_token='<eos>', lower=True)\\nTRG = Field(tokenize='spacy', tokenizer_language='en_core_web_sm',\\n init_token='<sos>', eos_token='<eos>', lower=True)\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\nMAX_LEN = 100\\ntrain_data, valid_data, test_data = Multi30k.splits(exts=('.de', '.en'),\\n fields=(SRC, TRG), filter_pred=lambda x: len(vars(x)['src']) <= MAX_LEN and\\n len(vars(x)['trg']) <= MAX_LEN)\\nSRC.build_vocab(train_data.src, min_freq=2)\\nTRG.build_vocab(train_data.trg, min_freq=2)\\nINPUT_DIM = len(SRC.vocab)\\nOUTPUT_DIM = len(TRG.vocab)\\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\\nBATCH_SIZE = 64\\ntrain_iter = MyIterator(train_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=True)\\nvalid_iter = MyIterator(valid_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\ntest_iter = MyIterator(test_data, batch_size=BATCH_SIZE, device=device,\\n repeat=False, sort_key=lambda x: (len(x.src), len(x.trg)),\\n batch_size_fn=batch_size_fn, train=False)\\nmodel_name = 'harvard_transformer2_state'\\nargs = INPUT_DIM, OUTPUT_DIM\\nkwargs = {'N': 6}\\nmodel = h.make_model(*args, **kwargs).to(device)\\nstate = torch.load(model_name + '.pt', map_location=device)\\nmodel.load_state_dict(state['state_dict'])\\nlosses = state['loss']\\npad_idx = TRG.vocab.stoi['<pad>']\\ncriterion_test = nn.CrossEntropyLoss(ignore_index=pad_idx)\\ntest_losses = evaluate(test_iter, model, criterion_test)\\nlosses['test'].append(test_losses)\\ntest_loss = torch.tensor(sum(test_losses) / len(test_losses))\\nprint(test_loss)\\nprint('Perplexity:', torch.exp(test_loss))\\nsentence = [SRC.preprocess(\\n 'ein mann mit kariertem hut in einer schwarzen jacke und einer schwarz-weiß gestreiften hose spielt auf einer bühne mit einem sänger und einem weiteren gitarristen im hintergrund auf einer e-gitarre .'\\n )]\\nreal_translation = TRG.preprocess(\\n 'a man in a black jacket and checkered hat wearing black and white striped pants plays an electric guitar on a stage with a singer and another guitar player in the background .'\\n )\\nsrc = SRC.process(sentence).to(device).T\\nsrc_mask = (src != SRC.vocab.stoi['<pad>']).unsqueeze(-2)\\nmodel.eval()\\nout = greedy_decode(model, src, src_mask, max_len=60, start_symbol=TRG.\\n vocab.stoi['<sos>'])\\ntranslation = ['<sos>']\\nfor i in range(1, out.size(1)):\\n sym = TRG.vocab.itos[out[0, i]]\\n translation.append(sym)\\n if sym == '<eos>':\\n break\\nprint(' '.join(translation))\\nprint(' '.join(real_translation))\\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\\n\",\n \"<import token>\\nsys.path.append('./')\\n<import token>\\nglobal max_src_in_batch, max_tgt_in_batch\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\ndef subsequent_mask(size):\\n \\\"\\\"\\\"Mask out subsequent positions.\\\"\\\"\\\"\\n attn_shape = 1, size, size\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\ndef rebatch(pad_idx, batch):\\n \\\"\\\"\\\"Fix order in torchtext to match ours\\\"\\\"\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\nSRC.build_vocab(train_data.src, min_freq=2)\\nTRG.build_vocab(train_data.trg, min_freq=2)\\n<assignment token>\\nmodel.load_state_dict(state['state_dict'])\\n<assignment token>\\nlosses['test'].append(test_losses)\\n<assignment token>\\nprint(test_loss)\\nprint('Perplexity:', torch.exp(test_loss))\\n<assignment token>\\nmodel.eval()\\n<assignment token>\\nfor i in range(1, out.size(1)):\\n sym = TRG.vocab.itos[out[0, i]]\\n translation.append(sym)\\n if sym == '<eos>':\\n break\\nprint(' '.join(translation))\\nprint(' '.join(real_translation))\\nvisualise_attention(translation, ['<sos>'] + sentence[0] + ['<eos>'])\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\ndef subsequent_mask(size):\\n \\\"\\\"\\\"Mask out subsequent positions.\\\"\\\"\\\"\\n attn_shape = 1, size, size\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\ndef rebatch(pad_idx, batch):\\n \\\"\\\"\\\"Fix order in torchtext to match ours\\\"\\\"\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\ndef rebatch(pad_idx, batch):\\n \\\"\\\"\\\"Fix order in torchtext to match ours\\\"\\\"\\\"\\n src, trg = batch.src.transpose(0, 1), batch.trg.transpose(0, 1)\\n return Batch(src, trg, pad_idx)\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n\\n\\ndef greedy_decode(model, src, src_mask, max_len, start_symbol):\\n memory = model.encode(src, src_mask)\\n ys = torch.ones(1, 1).fill_(start_symbol).type_as(src.data)\\n for i in range(max_len - 1):\\n out = model.decode(memory, src_mask, Variable(ys), Variable(\\n subsequent_mask(ys.size(1)).type_as(src.data)))\\n prob = model.generator(out[:, -1])\\n _, next_word = torch.max(prob, dim=1)\\n next_word = next_word.data[0]\\n ys = torch.cat([ys, torch.ones(1, 1).type_as(src.data).fill_(\\n next_word)], dim=1)\\n return ys\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n\\n\\ndef evaluate(data_iter, model, criterion):\\n model.eval()\\n with torch.no_grad():\\n eval_loss = run_epoch((rebatch(pad_idx, b) for b in data_iter),\\n model, SimpleLossCompute(model.generator, criterion, opt=None))\\n return eval_loss\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n\\n\\ndef run_epoch(data_iter, model, loss_compute):\\n \\\"\\\"\\\"Standard Training and Logging Function\\\"\\\"\\\"\\n start = time.time()\\n total_tokens = 0\\n total_loss = []\\n tokens = 0\\n for i, batch in enumerate(data_iter):\\n out = model.forward(batch.src, batch.trg, batch.src_mask, batch.\\n trg_mask)\\n loss = loss_compute(out, batch.trg_y, batch.ntokens)\\n total_loss.append(loss.item())\\n total_tokens += batch.ntokens\\n tokens += batch.ntokens\\n if i % 50 == 1:\\n elapsed = time.time() - start\\n print('Epoch Step: %d Loss: %f Tokens per Sec: %f' % (i, loss, \\n tokens / elapsed))\\n start = time.time()\\n tokens = 0\\n return total_loss\\n\\n\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n\\n\\ndef batch_size_fn(new, count, sofar):\\n \\\"\\\"\\\"Keep augmenting batch and calculate total number of tokens + padding.\\\"\\\"\\\"\\n global max_src_in_batch, max_tgt_in_batch\\n if count == 1:\\n max_src_in_batch = 0\\n max_tgt_in_batch = 0\\n max_src_in_batch = max(max_src_in_batch, len(vars(new)['src']))\\n max_tgt_in_batch = max(max_tgt_in_batch, len(vars(new)['trg']) + 2)\\n src_elements = count * max_src_in_batch\\n tgt_elements = count * max_tgt_in_batch\\n return max(src_elements, tgt_elements)\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n\\n\\ndef visualise_attention(tgt_sent, sent):\\n\\n def draw(data, x, y, ax):\\n seaborn.heatmap(data, xticklabels=x, square=True, yticklabels=y,\\n vmin=0.0, vmax=1.0, cbar=False, ax=ax)\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Encoder Layer', layer + 1)\\n for h in range(4):\\n vals = model.encoder.layers[layer].self_attn.attn[0, h].data.cpu()\\n draw(vals, sent, sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n for layer in range(1, 6, 2):\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n print('Decoder Self Layer', layer + 1)\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(tgt_sent)].cpu()\\n draw(vals, tgt_sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n print('Decoder Src Layer', layer + 1)\\n fig, axs = plt.subplots(1, 4, figsize=(16, 5))\\n for h in range(4):\\n vals = model.decoder.layers[layer].self_attn.attn[0, h].data[:\\n len(tgt_sent), :len(sent)].cpu()\\n draw(vals, sent, tgt_sent if h == 0 else [], ax=axs[h])\\n plt.show()\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n\\n\\nclass Batch:\\n \\\"\\\"\\\"Object for holding a batch of data with mask during training.\\\"\\\"\\\"\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n\\n\\nclass Batch:\\n <docstring token>\\n\\n def __init__(self, src, trg=None, pad=0):\\n self.src = src\\n self.src_mask = (src != pad).unsqueeze(-2)\\n if trg is not None:\\n self.trg = trg[:, :-1]\\n self.trg_y = trg[:, 1:]\\n self.trg_mask = self.make_std_mask(self.trg, pad)\\n self.ntokens = (self.trg_y != pad).data.sum()\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n\\n\\nclass Batch:\\n <docstring token>\\n <function token>\\n\\n @staticmethod\\n def make_std_mask(tgt, pad):\\n \\\"\\\"\\\"Create a mask to hide padding and future words.\\\"\\\"\\\"\\n tgt_mask = (tgt != pad).unsqueeze(-2)\\n tgt_mask = tgt_mask & Variable(subsequent_mask(tgt.size(-1)).\\n type_as(tgt_mask.data))\\n return tgt_mask\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n\\n\\nclass Batch:\\n <docstring token>\\n <function token>\\n <function token>\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n\\n\\nclass MyIterator(data.Iterator):\\n\\n def create_batches(self):\\n if self.train:\\n\\n def pool(d, random_shuffler):\\n for p in data.batch(d, self.batch_size * 100):\\n p_batch = data.batch(sorted(p, key=self.sort_key), self\\n .batch_size, self.batch_size_fn)\\n for b in random_shuffler(list(p_batch)):\\n yield b\\n self.batches = pool(self.data(), self.random_shuffler)\\n else:\\n self.batches = []\\n for b in data.batch(self.data(), self.batch_size, self.\\n batch_size_fn):\\n self.batches.append(sorted(b, key=self.sort_key))\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n\\n\\nclass MyIterator(data.Iterator):\\n <function token>\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n \\\"\\\"\\\"A simple loss compute and train function.\\\"\\\"\\\"\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n <docstring token>\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n\\n def __call__(self, x, y, norm):\\n x = self.generator(x)\\n loss = self.criterion(x.contiguous().view(-1, x.size(-1)), y.\\n contiguous().view(-1)) / norm\\n if self.opt is not None:\\n loss.backward()\\n self.opt.step()\\n self.opt.optimizer.zero_grad()\\n return loss.data.item() * norm\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n <docstring token>\\n\\n def __init__(self, generator, criterion, opt=None):\\n self.generator = generator\\n self.criterion = criterion\\n self.opt = opt\\n <function token>\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n\\n\\nclass SimpleLossCompute:\\n <docstring token>\\n <function token>\\n <function token>\\n\\n\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<code token>\\n<function token>\\n<class token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n<class token>\\n<function token>\\n<function token>\\n<function token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8695,"cells":{"index":{"kind":"number","value":8695,"string":"8,695"},"blob_id":{"kind":"string","value":"f6401eca2dc0ea86a934e859c35fa2d6c85a61b3"},"code":{"kind":"string","value":"import turtle\r\nhexagon = turtle.Turtle()\r\nfor i in range (6):\r\n hexagon.forward(100)\r\n hexagon.left(60)\r\n "},"steps":{"kind":"list like","value":["import turtle\r\nhexagon = turtle.Turtle()\r\nfor i in range (6):\r\n hexagon.forward(100)\r\n hexagon.left(60)\r\n ","import turtle\nhexagon = turtle.Turtle()\nfor i in range(6):\n hexagon.forward(100)\n hexagon.left(60)\n","<import token>\nhexagon = turtle.Turtle()\nfor i in range(6):\n hexagon.forward(100)\n hexagon.left(60)\n","<import token>\n<assignment token>\nfor i in range(6):\n hexagon.forward(100)\n hexagon.left(60)\n","<import token>\n<assignment token>\n<code token>\n"],"string":"[\n \"import turtle\\r\\nhexagon = turtle.Turtle()\\r\\nfor i in range (6):\\r\\n hexagon.forward(100)\\r\\n hexagon.left(60)\\r\\n \",\n \"import turtle\\nhexagon = turtle.Turtle()\\nfor i in range(6):\\n hexagon.forward(100)\\n hexagon.left(60)\\n\",\n \"<import token>\\nhexagon = turtle.Turtle()\\nfor i in range(6):\\n hexagon.forward(100)\\n hexagon.left(60)\\n\",\n \"<import token>\\n<assignment token>\\nfor i in range(6):\\n hexagon.forward(100)\\n hexagon.left(60)\\n\",\n \"<import token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8696,"cells":{"index":{"kind":"number","value":8696,"string":"8,696"},"blob_id":{"kind":"string","value":"4932a357cfd60cb65630345e75794ebf58b82c82"},"code":{"kind":"string","value":"import matplotlib; matplotlib.use('agg')\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nfrom scipy.optimize import curve_fit\r\nfrom uncertainties import ufloat\r\n\r\n#Holt Werte aus Textdatei\r\nI, U = np.genfromtxt('werte2.txt', unpack=True)\r\n\r\n#Definiert Funktion mit der ihr fitten wollt (hier eine Gerade)\r\ndef f(x, A, B):\r\n return A*x + B\r\n\r\n#Erstellt linspace von Bereich, in dem Ausgleichsfunktion erstellt wird\r\nx_plot = np.linspace(50, 160, 1000)\r\n#Fittet\r\nparams, covariance_matrix = curve_fit(f, I, U)\r\nerrors = np.sqrt(np.diag(covariance_matrix))\r\n#Plottet Fit\r\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion', linewidth=0.5)\r\n#Gibt berechnete Parameter aus\r\nprint(params)\r\nprint(np.sqrt(np.diag(covariance_matrix)))\r\nplt.gcf().subplots_adjust(bottom=0.18)\r\n#Plot eurer eigentlichen Messwerte\r\nplt.plot(I , U, 'r.', label='Messwerte', Markersize=4)\r\nplt.xlim(50, 160)\r\nplt.ylim(1.7,2.3)\r\nplt.legend()\r\nplt.grid()\r\nplt.xlabel(r'$I\\,/\\,\\mathrm{mA}$')\r\nplt.ylabel(r'$U_K\\,/\\,\\mathrm{V}$')\r\nplt.savefig('plot2.pdf')\r\n"},"steps":{"kind":"list like","value":["import matplotlib; matplotlib.use('agg')\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nfrom scipy.optimize import curve_fit\r\nfrom uncertainties import ufloat\r\n\r\n#Holt Werte aus Textdatei\r\nI, U = np.genfromtxt('werte2.txt', unpack=True)\r\n\r\n#Definiert Funktion mit der ihr fitten wollt (hier eine Gerade)\r\ndef f(x, A, B):\r\n return A*x + B\r\n\r\n#Erstellt linspace von Bereich, in dem Ausgleichsfunktion erstellt wird\r\nx_plot = np.linspace(50, 160, 1000)\r\n#Fittet\r\nparams, covariance_matrix = curve_fit(f, I, U)\r\nerrors = np.sqrt(np.diag(covariance_matrix))\r\n#Plottet Fit\r\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion', linewidth=0.5)\r\n#Gibt berechnete Parameter aus\r\nprint(params)\r\nprint(np.sqrt(np.diag(covariance_matrix)))\r\nplt.gcf().subplots_adjust(bottom=0.18)\r\n#Plot eurer eigentlichen Messwerte\r\nplt.plot(I , U, 'r.', label='Messwerte', Markersize=4)\r\nplt.xlim(50, 160)\r\nplt.ylim(1.7,2.3)\r\nplt.legend()\r\nplt.grid()\r\nplt.xlabel(r'$I\\,/\\,\\mathrm{mA}$')\r\nplt.ylabel(r'$U_K\\,/\\,\\mathrm{V}$')\r\nplt.savefig('plot2.pdf')\r\n","import matplotlib\nmatplotlib.use('agg')\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.optimize import curve_fit\nfrom uncertainties import ufloat\nI, U = np.genfromtxt('werte2.txt', unpack=True)\n\n\ndef f(x, A, B):\n return A * x + B\n\n\nx_plot = np.linspace(50, 160, 1000)\nparams, covariance_matrix = curve_fit(f, I, U)\nerrors = np.sqrt(np.diag(covariance_matrix))\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\n linewidth=0.5)\nprint(params)\nprint(np.sqrt(np.diag(covariance_matrix)))\nplt.gcf().subplots_adjust(bottom=0.18)\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\nplt.xlim(50, 160)\nplt.ylim(1.7, 2.3)\nplt.legend()\nplt.grid()\nplt.xlabel('$I\\\\,/\\\\,\\\\mathrm{mA}$')\nplt.ylabel('$U_K\\\\,/\\\\,\\\\mathrm{V}$')\nplt.savefig('plot2.pdf')\n","<import token>\nmatplotlib.use('agg')\n<import token>\nI, U = np.genfromtxt('werte2.txt', unpack=True)\n\n\ndef f(x, A, B):\n return A * x + B\n\n\nx_plot = np.linspace(50, 160, 1000)\nparams, covariance_matrix = curve_fit(f, I, U)\nerrors = np.sqrt(np.diag(covariance_matrix))\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\n linewidth=0.5)\nprint(params)\nprint(np.sqrt(np.diag(covariance_matrix)))\nplt.gcf().subplots_adjust(bottom=0.18)\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\nplt.xlim(50, 160)\nplt.ylim(1.7, 2.3)\nplt.legend()\nplt.grid()\nplt.xlabel('$I\\\\,/\\\\,\\\\mathrm{mA}$')\nplt.ylabel('$U_K\\\\,/\\\\,\\\\mathrm{V}$')\nplt.savefig('plot2.pdf')\n","<import token>\nmatplotlib.use('agg')\n<import token>\n<assignment token>\n\n\ndef f(x, A, B):\n return A * x + B\n\n\n<assignment token>\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\n linewidth=0.5)\nprint(params)\nprint(np.sqrt(np.diag(covariance_matrix)))\nplt.gcf().subplots_adjust(bottom=0.18)\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\nplt.xlim(50, 160)\nplt.ylim(1.7, 2.3)\nplt.legend()\nplt.grid()\nplt.xlabel('$I\\\\,/\\\\,\\\\mathrm{mA}$')\nplt.ylabel('$U_K\\\\,/\\\\,\\\\mathrm{V}$')\nplt.savefig('plot2.pdf')\n","<import token>\n<code token>\n<import token>\n<assignment token>\n\n\ndef f(x, A, B):\n return A * x + B\n\n\n<assignment token>\n<code token>\n","<import token>\n<code token>\n<import token>\n<assignment token>\n<function token>\n<assignment token>\n<code token>\n"],"string":"[\n \"import matplotlib; matplotlib.use('agg')\\r\\nimport matplotlib.pyplot as plt\\r\\nimport numpy as np\\r\\nfrom scipy.optimize import curve_fit\\r\\nfrom uncertainties import ufloat\\r\\n\\r\\n#Holt Werte aus Textdatei\\r\\nI, U = np.genfromtxt('werte2.txt', unpack=True)\\r\\n\\r\\n#Definiert Funktion mit der ihr fitten wollt (hier eine Gerade)\\r\\ndef f(x, A, B):\\r\\n return A*x + B\\r\\n\\r\\n#Erstellt linspace von Bereich, in dem Ausgleichsfunktion erstellt wird\\r\\nx_plot = np.linspace(50, 160, 1000)\\r\\n#Fittet\\r\\nparams, covariance_matrix = curve_fit(f, I, U)\\r\\nerrors = np.sqrt(np.diag(covariance_matrix))\\r\\n#Plottet Fit\\r\\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion', linewidth=0.5)\\r\\n#Gibt berechnete Parameter aus\\r\\nprint(params)\\r\\nprint(np.sqrt(np.diag(covariance_matrix)))\\r\\nplt.gcf().subplots_adjust(bottom=0.18)\\r\\n#Plot eurer eigentlichen Messwerte\\r\\nplt.plot(I , U, 'r.', label='Messwerte', Markersize=4)\\r\\nplt.xlim(50, 160)\\r\\nplt.ylim(1.7,2.3)\\r\\nplt.legend()\\r\\nplt.grid()\\r\\nplt.xlabel(r'$I\\\\,/\\\\,\\\\mathrm{mA}$')\\r\\nplt.ylabel(r'$U_K\\\\,/\\\\,\\\\mathrm{V}$')\\r\\nplt.savefig('plot2.pdf')\\r\\n\",\n \"import matplotlib\\nmatplotlib.use('agg')\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\nfrom scipy.optimize import curve_fit\\nfrom uncertainties import ufloat\\nI, U = np.genfromtxt('werte2.txt', unpack=True)\\n\\n\\ndef f(x, A, B):\\n return A * x + B\\n\\n\\nx_plot = np.linspace(50, 160, 1000)\\nparams, covariance_matrix = curve_fit(f, I, U)\\nerrors = np.sqrt(np.diag(covariance_matrix))\\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\\n linewidth=0.5)\\nprint(params)\\nprint(np.sqrt(np.diag(covariance_matrix)))\\nplt.gcf().subplots_adjust(bottom=0.18)\\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\\nplt.xlim(50, 160)\\nplt.ylim(1.7, 2.3)\\nplt.legend()\\nplt.grid()\\nplt.xlabel('$I\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{mA}$')\\nplt.ylabel('$U_K\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{V}$')\\nplt.savefig('plot2.pdf')\\n\",\n \"<import token>\\nmatplotlib.use('agg')\\n<import token>\\nI, U = np.genfromtxt('werte2.txt', unpack=True)\\n\\n\\ndef f(x, A, B):\\n return A * x + B\\n\\n\\nx_plot = np.linspace(50, 160, 1000)\\nparams, covariance_matrix = curve_fit(f, I, U)\\nerrors = np.sqrt(np.diag(covariance_matrix))\\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\\n linewidth=0.5)\\nprint(params)\\nprint(np.sqrt(np.diag(covariance_matrix)))\\nplt.gcf().subplots_adjust(bottom=0.18)\\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\\nplt.xlim(50, 160)\\nplt.ylim(1.7, 2.3)\\nplt.legend()\\nplt.grid()\\nplt.xlabel('$I\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{mA}$')\\nplt.ylabel('$U_K\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{V}$')\\nplt.savefig('plot2.pdf')\\n\",\n \"<import token>\\nmatplotlib.use('agg')\\n<import token>\\n<assignment token>\\n\\n\\ndef f(x, A, B):\\n return A * x + B\\n\\n\\n<assignment token>\\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\\n linewidth=0.5)\\nprint(params)\\nprint(np.sqrt(np.diag(covariance_matrix)))\\nplt.gcf().subplots_adjust(bottom=0.18)\\nplt.plot(I, U, 'r.', label='Messwerte', Markersize=4)\\nplt.xlim(50, 160)\\nplt.ylim(1.7, 2.3)\\nplt.legend()\\nplt.grid()\\nplt.xlabel('$I\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{mA}$')\\nplt.ylabel('$U_K\\\\\\\\,/\\\\\\\\,\\\\\\\\mathrm{V}$')\\nplt.savefig('plot2.pdf')\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<assignment token>\\n\\n\\ndef f(x, A, B):\\n return A * x + B\\n\\n\\n<assignment token>\\n<code token>\\n\",\n \"<import token>\\n<code token>\\n<import token>\\n<assignment token>\\n<function token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8697,"cells":{"index":{"kind":"number","value":8697,"string":"8,697"},"blob_id":{"kind":"string","value":"641cbe2f35925d070249820a2e3a4f1cdd1cf642"},"code":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\napp definition\n\"\"\"\n\nfrom django.apps import AppConfig\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n name = 'coop_html_editor'\n verbose_name = \"Html Editor\"\n"},"steps":{"kind":"list like","value":["# -*- coding: utf-8 -*-\n\"\"\"\napp definition\n\"\"\"\n\nfrom django.apps import AppConfig\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n name = 'coop_html_editor'\n verbose_name = \"Html Editor\"\n","<docstring token>\nfrom django.apps import AppConfig\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n name = 'coop_html_editor'\n verbose_name = 'Html Editor'\n","<docstring token>\n<import token>\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n name = 'coop_html_editor'\n verbose_name = 'Html Editor'\n","<docstring token>\n<import token>\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n <assignment token>\n <assignment token>\n","<docstring token>\n<import token>\n<class token>\n"],"string":"[\n \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\napp definition\\n\\\"\\\"\\\"\\n\\nfrom django.apps import AppConfig\\n\\n\\nclass CoopHtmlEditorAppConfig(AppConfig):\\n name = 'coop_html_editor'\\n verbose_name = \\\"Html Editor\\\"\\n\",\n \"<docstring token>\\nfrom django.apps import AppConfig\\n\\n\\nclass CoopHtmlEditorAppConfig(AppConfig):\\n name = 'coop_html_editor'\\n verbose_name = 'Html Editor'\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass CoopHtmlEditorAppConfig(AppConfig):\\n name = 'coop_html_editor'\\n verbose_name = 'Html Editor'\\n\",\n \"<docstring token>\\n<import token>\\n\\n\\nclass CoopHtmlEditorAppConfig(AppConfig):\\n <assignment token>\\n <assignment token>\\n\",\n \"<docstring token>\\n<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8698,"cells":{"index":{"kind":"number","value":8698,"string":"8,698"},"blob_id":{"kind":"string","value":"3164eab8dc221149c9f865645edf9991d810d2ac"},"code":{"kind":"string","value":"import numpy as np\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport time\nimport sys\n\nclass ConsensusSimulation:\n \"\"\"Class to model a general consensus problem\n see DOI: 10.1109/JPROC.2006.887293\"\"\"\n def __init__(self,\n topology,\n dynamics,\n dynamics_args,\n time_step=0.01,\n x_init=None,\n convergence_warning=True,\n delay=0):\n # check arguments are of the\n # correct form\n if(isinstance(topology,nx.Graph)):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print(\"Argument Error: topology must be type\"\n , type(nx.Graph()))\n if(callable(dynamics)):\n self.f = dynamics\n if(len(dynamics_args)==1):\n self.f_arg = (dynamics_args,1)\n self.f_arg = dynamics_args\n else:\n print(\"Argument Error: dynamics must be a function\")\n self.dt = time_step\n self.tau = delay\n # set up initial vector to\n # 1,2,3,...,n\n if(not isinstance(x_init, type(np.ones(1))) and x_init==None):\n self.x = np.linspace(1,self.size,self.size)\n self.x = self.x.reshape(self.size,1)\n else:\n self.x = x_init.copy().reshape(self.size,1)\n # The Laplacian matrix, quite the building block\n # for the algorithms\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n # connected graph won't converge\n # maybe there's some algorithm that will\n # though...\n self.warn = convergence_warning\n\n self.d_max = max(np.array(self.graph.degree)[:,1])\n self.tau_max = (np.pi)/(4*self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5*(np.dot(np.dot(np.transpose(self.x),self.L),self.x)).item(0)\n\n def agreement(self,tol=1e-6):\n \"\"\"Test for convergence\"\"\"\n if(self.disagreement()<tol):\n return True\n else:\n return False\n\n def run_sim(self,record_all=False,update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t=0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if(t==0 and self.warn and not nx.is_connected(self.graph)):\n print(\"Graph not connected, consensus algorithm will probably not converge!\")\n print(\"Simulating to 5 seconds...\")\n flag = True\n if(flag and time.time()-start>5):\n break\n # core simulation done here\n # very simple discretisation...\n self.x = self.x+self.dt*self.f(self.x,*self.f_arg)\n # odd way to test for 1,2,3,etc\n # when arg is float\n if (record_all):\n self.X.append(self.x)\n self.T.append(time.time()-start)\n else:\n if (t-np.floor(t)<1e-2):\n self.X.append(self.x)\n self.T.append(time.time()-start)\n t = t+self.dt\n end = time.time()-start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write(\"\\r\" + \"Iteration: {}, disagreement: {}, time: {}\".format(progress,self.disagreement(),time.time()-start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n\n print(\"\")\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay = 1, runtime=100):\n t=0\n self.tau=delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0,delay+1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if (self.T[-1] > runtime):\n break\n if (t==0 and self.warn and not nx.is_connected(self.graph)):\n print(\"Graph not connected, consensus algorithm will probably not converge!\")\n print(\"Simulating to 5 seconds...\")\n flag = True\n if(flag and time.time()-start>5):\n break\n # core simulation done here\n # very simple discretisation...\n self.x = self.X[-1]\n if (len(self.X)-delay<0):\n pass\n else:\n index = len(self.X)-delay\n self.x = self.X[-1]+self.dt*self.f(self.X[index],*self.f_arg)\n # odd way to test for 1,2,3,etc\n # when arg is float\n self.X.append(self.x)\n self.T.append(time.time()-start)\n t = t+self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if(len(self.X)==0 or len(self.T)==0):\n print(\"Nothing to plot...\")\n x = np.array(self.X)\n for i in range(0,x.shape[1]):\n plt.plot(self.T,x[:,i,0])\n if(weight_average):\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:,1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i)/s\n x[i] = x[i]*w_i[i]\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+sum(x), label=\"Connected graph consensus: \"+str(sum(x)),color='red',marker='s')\n else:\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+np.mean(self.x_init), label=\"Connected graph consensus: \"+str(round(np.mean(self.x_init),3)),color='red',marker='s')\n plt.grid()\n plt.xlabel(\"Time (seconds)\")\n plt.ylabel(\"State\")\n plt.title(\"Convergence of consensus algorithm\")\n plt.legend()\n\n def print_delay(self):\n print(\"Delay in seconds\")\n return self.dt*self.tau\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return (np.pi)/(4*d[1])\n"},"steps":{"kind":"list like","value":["import numpy as np\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport time\nimport sys\n\nclass ConsensusSimulation:\n \"\"\"Class to model a general consensus problem\n see DOI: 10.1109/JPROC.2006.887293\"\"\"\n def __init__(self,\n topology,\n dynamics,\n dynamics_args,\n time_step=0.01,\n x_init=None,\n convergence_warning=True,\n delay=0):\n # check arguments are of the\n # correct form\n if(isinstance(topology,nx.Graph)):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print(\"Argument Error: topology must be type\"\n , type(nx.Graph()))\n if(callable(dynamics)):\n self.f = dynamics\n if(len(dynamics_args)==1):\n self.f_arg = (dynamics_args,1)\n self.f_arg = dynamics_args\n else:\n print(\"Argument Error: dynamics must be a function\")\n self.dt = time_step\n self.tau = delay\n # set up initial vector to\n # 1,2,3,...,n\n if(not isinstance(x_init, type(np.ones(1))) and x_init==None):\n self.x = np.linspace(1,self.size,self.size)\n self.x = self.x.reshape(self.size,1)\n else:\n self.x = x_init.copy().reshape(self.size,1)\n # The Laplacian matrix, quite the building block\n # for the algorithms\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n # connected graph won't converge\n # maybe there's some algorithm that will\n # though...\n self.warn = convergence_warning\n\n self.d_max = max(np.array(self.graph.degree)[:,1])\n self.tau_max = (np.pi)/(4*self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5*(np.dot(np.dot(np.transpose(self.x),self.L),self.x)).item(0)\n\n def agreement(self,tol=1e-6):\n \"\"\"Test for convergence\"\"\"\n if(self.disagreement()<tol):\n return True\n else:\n return False\n\n def run_sim(self,record_all=False,update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t=0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if(t==0 and self.warn and not nx.is_connected(self.graph)):\n print(\"Graph not connected, consensus algorithm will probably not converge!\")\n print(\"Simulating to 5 seconds...\")\n flag = True\n if(flag and time.time()-start>5):\n break\n # core simulation done here\n # very simple discretisation...\n self.x = self.x+self.dt*self.f(self.x,*self.f_arg)\n # odd way to test for 1,2,3,etc\n # when arg is float\n if (record_all):\n self.X.append(self.x)\n self.T.append(time.time()-start)\n else:\n if (t-np.floor(t)<1e-2):\n self.X.append(self.x)\n self.T.append(time.time()-start)\n t = t+self.dt\n end = time.time()-start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write(\"\\r\" + \"Iteration: {}, disagreement: {}, time: {}\".format(progress,self.disagreement(),time.time()-start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n\n print(\"\")\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay = 1, runtime=100):\n t=0\n self.tau=delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0,delay+1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if (self.T[-1] > runtime):\n break\n if (t==0 and self.warn and not nx.is_connected(self.graph)):\n print(\"Graph not connected, consensus algorithm will probably not converge!\")\n print(\"Simulating to 5 seconds...\")\n flag = True\n if(flag and time.time()-start>5):\n break\n # core simulation done here\n # very simple discretisation...\n self.x = self.X[-1]\n if (len(self.X)-delay<0):\n pass\n else:\n index = len(self.X)-delay\n self.x = self.X[-1]+self.dt*self.f(self.X[index],*self.f_arg)\n # odd way to test for 1,2,3,etc\n # when arg is float\n self.X.append(self.x)\n self.T.append(time.time()-start)\n t = t+self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if(len(self.X)==0 or len(self.T)==0):\n print(\"Nothing to plot...\")\n x = np.array(self.X)\n for i in range(0,x.shape[1]):\n plt.plot(self.T,x[:,i,0])\n if(weight_average):\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:,1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i)/s\n x[i] = x[i]*w_i[i]\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+sum(x), label=\"Connected graph consensus: \"+str(sum(x)),color='red',marker='s')\n else:\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+np.mean(self.x_init), label=\"Connected graph consensus: \"+str(round(np.mean(self.x_init),3)),color='red',marker='s')\n plt.grid()\n plt.xlabel(\"Time (seconds)\")\n plt.ylabel(\"State\")\n plt.title(\"Convergence of consensus algorithm\")\n plt.legend()\n\n def print_delay(self):\n print(\"Delay in seconds\")\n return self.dt*self.tau\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return (np.pi)/(4*d[1])\n","import numpy as np\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport time\nimport sys\n\n\nclass ConsensusSimulation:\n \"\"\"Class to model a general consensus problem\n see DOI: 10.1109/JPROC.2006.887293\"\"\"\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n\n def run_sim(self, record_all=False, update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t = 0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\n if record_all:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n elif t - np.floor(t) < 0.01:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time() - start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write('\\r' +\n 'Iteration: {}, disagreement: {}, time: {}'.format(\n progress, self.disagreement(), time.time() - start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n print('')\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if len(self.X) == 0 or len(self.T) == 0:\n print('Nothing to plot...')\n x = np.array(self.X)\n for i in range(0, x.shape[1]):\n plt.plot(self.T, x[:, i, 0])\n if weight_average:\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:, 1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i) / s\n x[i] = x[i] * w_i[i]\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\n label='Connected graph consensus: ' + str(sum(x)), color=\n 'red', marker='s')\n else:\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\n (self.x_init), label='Connected graph consensus: ' + str(\n round(np.mean(self.x_init), 3)), color='red', marker='s')\n plt.grid()\n plt.xlabel('Time (seconds)')\n plt.ylabel('State')\n plt.title('Convergence of consensus algorithm')\n plt.legend()\n\n def print_delay(self):\n print('Delay in seconds')\n return self.dt * self.tau\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n \"\"\"Class to model a general consensus problem\n see DOI: 10.1109/JPROC.2006.887293\"\"\"\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n\n def run_sim(self, record_all=False, update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t = 0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\n if record_all:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n elif t - np.floor(t) < 0.01:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time() - start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write('\\r' +\n 'Iteration: {}, disagreement: {}, time: {}'.format(\n progress, self.disagreement(), time.time() - start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n print('')\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if len(self.X) == 0 or len(self.T) == 0:\n print('Nothing to plot...')\n x = np.array(self.X)\n for i in range(0, x.shape[1]):\n plt.plot(self.T, x[:, i, 0])\n if weight_average:\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:, 1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i) / s\n x[i] = x[i] * w_i[i]\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\n label='Connected graph consensus: ' + str(sum(x)), color=\n 'red', marker='s')\n else:\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\n (self.x_init), label='Connected graph consensus: ' + str(\n round(np.mean(self.x_init), 3)), color='red', marker='s')\n plt.grid()\n plt.xlabel('Time (seconds)')\n plt.ylabel('State')\n plt.title('Convergence of consensus algorithm')\n plt.legend()\n\n def print_delay(self):\n print('Delay in seconds')\n return self.dt * self.tau\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n\n def run_sim(self, record_all=False, update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t = 0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\n if record_all:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n elif t - np.floor(t) < 0.01:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time() - start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write('\\r' +\n 'Iteration: {}, disagreement: {}, time: {}'.format(\n progress, self.disagreement(), time.time() - start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n print('')\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if len(self.X) == 0 or len(self.T) == 0:\n print('Nothing to plot...')\n x = np.array(self.X)\n for i in range(0, x.shape[1]):\n plt.plot(self.T, x[:, i, 0])\n if weight_average:\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:, 1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i) / s\n x[i] = x[i] * w_i[i]\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\n label='Connected graph consensus: ' + str(sum(x)), color=\n 'red', marker='s')\n else:\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\n (self.x_init), label='Connected graph consensus: ' + str(\n round(np.mean(self.x_init), 3)), color='red', marker='s')\n plt.grid()\n plt.xlabel('Time (seconds)')\n plt.ylabel('State')\n plt.title('Convergence of consensus algorithm')\n plt.legend()\n\n def print_delay(self):\n print('Delay in seconds')\n return self.dt * self.tau\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n\n def run_sim(self, record_all=False, update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t = 0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\n if record_all:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n elif t - np.floor(t) < 0.01:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time() - start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write('\\r' +\n 'Iteration: {}, disagreement: {}, time: {}'.format(\n progress, self.disagreement(), time.time() - start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n print('')\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n\n def plot(self, weight_average=False):\n \"\"\"Show the convergence analysis\"\"\"\n if len(self.X) == 0 or len(self.T) == 0:\n print('Nothing to plot...')\n x = np.array(self.X)\n for i in range(0, x.shape[1]):\n plt.plot(self.T, x[:, i, 0])\n if weight_average:\n w_i = np.zeros(self.size)\n s = sum(np.array(self.graph.degree)[:, 1])\n x = self.x_init\n for i in nx.nodes(self.graph):\n w_i[i] = self.graph.degree(i) / s\n x[i] = x[i] * w_i[i]\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\n label='Connected graph consensus: ' + str(sum(x)), color=\n 'red', marker='s')\n else:\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\n (self.x_init), label='Connected graph consensus: ' + str(\n round(np.mean(self.x_init), 3)), color='red', marker='s')\n plt.grid()\n plt.xlabel('Time (seconds)')\n plt.ylabel('State')\n plt.title('Convergence of consensus algorithm')\n plt.legend()\n <function token>\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n\n def run_sim(self, record_all=False, update_every=1.0):\n \"\"\"run the core simulation\"\"\"\n t = 0\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n time_since_last_update = 0.0\n progress = 1\n while self.agreement() == False:\n start_it = time.time()\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\n if record_all:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n elif t - np.floor(t) < 0.01:\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time() - start_it\n time_since_last_update += end\n if time_since_last_update >= update_every:\n sys.stdout.write('\\r' +\n 'Iteration: {}, disagreement: {}, time: {}'.format(\n progress, self.disagreement(), time.time() - start))\n sys.stdout.flush()\n time_since_last_update = 0.0\n progress += 1\n print('')\n end = time.time()\n return self.T[-1]\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n <function token>\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n\n def delay_stable_max(self):\n d = maximum_degree(self.graph)\n return np.pi / (4 * d[1])\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n\n def agreement(self, tol=1e-06):\n \"\"\"Test for convergence\"\"\"\n if self.disagreement() < tol:\n return True\n else:\n return False\n <function token>\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\n x_init=None, convergence_warning=True, delay=0):\n if isinstance(topology, nx.Graph):\n self.graph = topology\n self.size = len(self.graph)\n else:\n print('Argument Error: topology must be type', type(nx.Graph()))\n if callable(dynamics):\n self.f = dynamics\n if len(dynamics_args) == 1:\n self.f_arg = dynamics_args, 1\n self.f_arg = dynamics_args\n else:\n print('Argument Error: dynamics must be a function')\n self.dt = time_step\n self.tau = delay\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\n self.x = np.linspace(1, self.size, self.size)\n self.x = self.x.reshape(self.size, 1)\n else:\n self.x = x_init.copy().reshape(self.size, 1)\n self.L = nx.laplacian_matrix(self.graph).todense()\n self.X = list()\n self.T = list()\n self.warn = convergence_warning\n self.d_max = max(np.array(self.graph.degree)[:, 1])\n self.tau_max = np.pi / (4 * self.d_max)\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n <function token>\n <function token>\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n <function token>\n\n def disagreement(self):\n \"\"\"Returns the 'error'/inhomogeneity in the\n decision vector\"\"\"\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\n 0)\n <function token>\n <function token>\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n <function token>\n <function token>\n <function token>\n <function token>\n\n def sim_delay(self, delay=1, runtime=100):\n t = 0\n self.tau = delay\n self.x_init = self.x\n self.X = list()\n self.T = list()\n flag = False\n for i in range(0, delay + 1):\n self.X.append(self.x)\n self.T.append(0)\n start = time.time()\n while self.agreement() == False:\n if self.T[-1] > runtime:\n break\n if t == 0 and self.warn and not nx.is_connected(self.graph):\n print(\n 'Graph not connected, consensus algorithm will probably not converge!'\n )\n print('Simulating to 5 seconds...')\n flag = True\n if flag and time.time() - start > 5:\n break\n self.x = self.X[-1]\n if len(self.X) - delay < 0:\n pass\n else:\n index = len(self.X) - delay\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\n .f_arg)\n self.X.append(self.x)\n self.T.append(time.time() - start)\n t = t + self.dt\n end = time.time()\n return self.T[-1]\n <function token>\n <function token>\n <function token>\n","<import token>\n\n\nclass ConsensusSimulation:\n <docstring token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n <function token>\n","<import token>\n<class token>\n"],"string":"[\n \"import numpy as np\\nimport matplotlib.pyplot as plt\\nimport networkx as nx\\nimport time\\nimport sys\\n\\nclass ConsensusSimulation:\\n \\\"\\\"\\\"Class to model a general consensus problem\\n see DOI: 10.1109/JPROC.2006.887293\\\"\\\"\\\"\\n def __init__(self,\\n topology,\\n dynamics,\\n dynamics_args,\\n time_step=0.01,\\n x_init=None,\\n convergence_warning=True,\\n delay=0):\\n # check arguments are of the\\n # correct form\\n if(isinstance(topology,nx.Graph)):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print(\\\"Argument Error: topology must be type\\\"\\n , type(nx.Graph()))\\n if(callable(dynamics)):\\n self.f = dynamics\\n if(len(dynamics_args)==1):\\n self.f_arg = (dynamics_args,1)\\n self.f_arg = dynamics_args\\n else:\\n print(\\\"Argument Error: dynamics must be a function\\\")\\n self.dt = time_step\\n self.tau = delay\\n # set up initial vector to\\n # 1,2,3,...,n\\n if(not isinstance(x_init, type(np.ones(1))) and x_init==None):\\n self.x = np.linspace(1,self.size,self.size)\\n self.x = self.x.reshape(self.size,1)\\n else:\\n self.x = x_init.copy().reshape(self.size,1)\\n # The Laplacian matrix, quite the building block\\n # for the algorithms\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n # connected graph won't converge\\n # maybe there's some algorithm that will\\n # though...\\n self.warn = convergence_warning\\n\\n self.d_max = max(np.array(self.graph.degree)[:,1])\\n self.tau_max = (np.pi)/(4*self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5*(np.dot(np.dot(np.transpose(self.x),self.L),self.x)).item(0)\\n\\n def agreement(self,tol=1e-6):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if(self.disagreement()<tol):\\n return True\\n else:\\n return False\\n\\n def run_sim(self,record_all=False,update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t=0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if(t==0 and self.warn and not nx.is_connected(self.graph)):\\n print(\\\"Graph not connected, consensus algorithm will probably not converge!\\\")\\n print(\\\"Simulating to 5 seconds...\\\")\\n flag = True\\n if(flag and time.time()-start>5):\\n break\\n # core simulation done here\\n # very simple discretisation...\\n self.x = self.x+self.dt*self.f(self.x,*self.f_arg)\\n # odd way to test for 1,2,3,etc\\n # when arg is float\\n if (record_all):\\n self.X.append(self.x)\\n self.T.append(time.time()-start)\\n else:\\n if (t-np.floor(t)<1e-2):\\n self.X.append(self.x)\\n self.T.append(time.time()-start)\\n t = t+self.dt\\n end = time.time()-start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write(\\\"\\\\r\\\" + \\\"Iteration: {}, disagreement: {}, time: {}\\\".format(progress,self.disagreement(),time.time()-start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n\\n print(\\\"\\\")\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay = 1, runtime=100):\\n t=0\\n self.tau=delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0,delay+1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if (self.T[-1] > runtime):\\n break\\n if (t==0 and self.warn and not nx.is_connected(self.graph)):\\n print(\\\"Graph not connected, consensus algorithm will probably not converge!\\\")\\n print(\\\"Simulating to 5 seconds...\\\")\\n flag = True\\n if(flag and time.time()-start>5):\\n break\\n # core simulation done here\\n # very simple discretisation...\\n self.x = self.X[-1]\\n if (len(self.X)-delay<0):\\n pass\\n else:\\n index = len(self.X)-delay\\n self.x = self.X[-1]+self.dt*self.f(self.X[index],*self.f_arg)\\n # odd way to test for 1,2,3,etc\\n # when arg is float\\n self.X.append(self.x)\\n self.T.append(time.time()-start)\\n t = t+self.dt\\n end = time.time()\\n return self.T[-1]\\n\\n def plot(self, weight_average=False):\\n \\\"\\\"\\\"Show the convergence analysis\\\"\\\"\\\"\\n if(len(self.X)==0 or len(self.T)==0):\\n print(\\\"Nothing to plot...\\\")\\n x = np.array(self.X)\\n for i in range(0,x.shape[1]):\\n plt.plot(self.T,x[:,i,0])\\n if(weight_average):\\n w_i = np.zeros(self.size)\\n s = sum(np.array(self.graph.degree)[:,1])\\n x = self.x_init\\n for i in nx.nodes(self.graph):\\n w_i[i] = self.graph.degree(i)/s\\n x[i] = x[i]*w_i[i]\\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+sum(x), label=\\\"Connected graph consensus: \\\"+str(sum(x)),color='red',marker='s')\\n else:\\n plt.plot(np.linspace(0,self.T[-1],10),np.zeros(10)+np.mean(self.x_init), label=\\\"Connected graph consensus: \\\"+str(round(np.mean(self.x_init),3)),color='red',marker='s')\\n plt.grid()\\n plt.xlabel(\\\"Time (seconds)\\\")\\n plt.ylabel(\\\"State\\\")\\n plt.title(\\\"Convergence of consensus algorithm\\\")\\n plt.legend()\\n\\n def print_delay(self):\\n print(\\\"Delay in seconds\\\")\\n return self.dt*self.tau\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return (np.pi)/(4*d[1])\\n\",\n \"import numpy as np\\nimport matplotlib.pyplot as plt\\nimport networkx as nx\\nimport time\\nimport sys\\n\\n\\nclass ConsensusSimulation:\\n \\\"\\\"\\\"Class to model a general consensus problem\\n see DOI: 10.1109/JPROC.2006.887293\\\"\\\"\\\"\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n\\n def run_sim(self, record_all=False, update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t = 0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\\n if record_all:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n elif t - np.floor(t) < 0.01:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time() - start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write('\\\\r' +\\n 'Iteration: {}, disagreement: {}, time: {}'.format(\\n progress, self.disagreement(), time.time() - start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n print('')\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n\\n def plot(self, weight_average=False):\\n \\\"\\\"\\\"Show the convergence analysis\\\"\\\"\\\"\\n if len(self.X) == 0 or len(self.T) == 0:\\n print('Nothing to plot...')\\n x = np.array(self.X)\\n for i in range(0, x.shape[1]):\\n plt.plot(self.T, x[:, i, 0])\\n if weight_average:\\n w_i = np.zeros(self.size)\\n s = sum(np.array(self.graph.degree)[:, 1])\\n x = self.x_init\\n for i in nx.nodes(self.graph):\\n w_i[i] = self.graph.degree(i) / s\\n x[i] = x[i] * w_i[i]\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\\n label='Connected graph consensus: ' + str(sum(x)), color=\\n 'red', marker='s')\\n else:\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\\n (self.x_init), label='Connected graph consensus: ' + str(\\n round(np.mean(self.x_init), 3)), color='red', marker='s')\\n plt.grid()\\n plt.xlabel('Time (seconds)')\\n plt.ylabel('State')\\n plt.title('Convergence of consensus algorithm')\\n plt.legend()\\n\\n def print_delay(self):\\n print('Delay in seconds')\\n return self.dt * self.tau\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n \\\"\\\"\\\"Class to model a general consensus problem\\n see DOI: 10.1109/JPROC.2006.887293\\\"\\\"\\\"\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n\\n def run_sim(self, record_all=False, update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t = 0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\\n if record_all:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n elif t - np.floor(t) < 0.01:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time() - start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write('\\\\r' +\\n 'Iteration: {}, disagreement: {}, time: {}'.format(\\n progress, self.disagreement(), time.time() - start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n print('')\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n\\n def plot(self, weight_average=False):\\n \\\"\\\"\\\"Show the convergence analysis\\\"\\\"\\\"\\n if len(self.X) == 0 or len(self.T) == 0:\\n print('Nothing to plot...')\\n x = np.array(self.X)\\n for i in range(0, x.shape[1]):\\n plt.plot(self.T, x[:, i, 0])\\n if weight_average:\\n w_i = np.zeros(self.size)\\n s = sum(np.array(self.graph.degree)[:, 1])\\n x = self.x_init\\n for i in nx.nodes(self.graph):\\n w_i[i] = self.graph.degree(i) / s\\n x[i] = x[i] * w_i[i]\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\\n label='Connected graph consensus: ' + str(sum(x)), color=\\n 'red', marker='s')\\n else:\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\\n (self.x_init), label='Connected graph consensus: ' + str(\\n round(np.mean(self.x_init), 3)), color='red', marker='s')\\n plt.grid()\\n plt.xlabel('Time (seconds)')\\n plt.ylabel('State')\\n plt.title('Convergence of consensus algorithm')\\n plt.legend()\\n\\n def print_delay(self):\\n print('Delay in seconds')\\n return self.dt * self.tau\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n\\n def run_sim(self, record_all=False, update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t = 0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\\n if record_all:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n elif t - np.floor(t) < 0.01:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time() - start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write('\\\\r' +\\n 'Iteration: {}, disagreement: {}, time: {}'.format(\\n progress, self.disagreement(), time.time() - start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n print('')\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n\\n def plot(self, weight_average=False):\\n \\\"\\\"\\\"Show the convergence analysis\\\"\\\"\\\"\\n if len(self.X) == 0 or len(self.T) == 0:\\n print('Nothing to plot...')\\n x = np.array(self.X)\\n for i in range(0, x.shape[1]):\\n plt.plot(self.T, x[:, i, 0])\\n if weight_average:\\n w_i = np.zeros(self.size)\\n s = sum(np.array(self.graph.degree)[:, 1])\\n x = self.x_init\\n for i in nx.nodes(self.graph):\\n w_i[i] = self.graph.degree(i) / s\\n x[i] = x[i] * w_i[i]\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\\n label='Connected graph consensus: ' + str(sum(x)), color=\\n 'red', marker='s')\\n else:\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\\n (self.x_init), label='Connected graph consensus: ' + str(\\n round(np.mean(self.x_init), 3)), color='red', marker='s')\\n plt.grid()\\n plt.xlabel('Time (seconds)')\\n plt.ylabel('State')\\n plt.title('Convergence of consensus algorithm')\\n plt.legend()\\n\\n def print_delay(self):\\n print('Delay in seconds')\\n return self.dt * self.tau\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n\\n def run_sim(self, record_all=False, update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t = 0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\\n if record_all:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n elif t - np.floor(t) < 0.01:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time() - start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write('\\\\r' +\\n 'Iteration: {}, disagreement: {}, time: {}'.format(\\n progress, self.disagreement(), time.time() - start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n print('')\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n\\n def plot(self, weight_average=False):\\n \\\"\\\"\\\"Show the convergence analysis\\\"\\\"\\\"\\n if len(self.X) == 0 or len(self.T) == 0:\\n print('Nothing to plot...')\\n x = np.array(self.X)\\n for i in range(0, x.shape[1]):\\n plt.plot(self.T, x[:, i, 0])\\n if weight_average:\\n w_i = np.zeros(self.size)\\n s = sum(np.array(self.graph.degree)[:, 1])\\n x = self.x_init\\n for i in nx.nodes(self.graph):\\n w_i[i] = self.graph.degree(i) / s\\n x[i] = x[i] * w_i[i]\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + sum(x),\\n label='Connected graph consensus: ' + str(sum(x)), color=\\n 'red', marker='s')\\n else:\\n plt.plot(np.linspace(0, self.T[-1], 10), np.zeros(10) + np.mean\\n (self.x_init), label='Connected graph consensus: ' + str(\\n round(np.mean(self.x_init), 3)), color='red', marker='s')\\n plt.grid()\\n plt.xlabel('Time (seconds)')\\n plt.ylabel('State')\\n plt.title('Convergence of consensus algorithm')\\n plt.legend()\\n <function token>\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n\\n def run_sim(self, record_all=False, update_every=1.0):\\n \\\"\\\"\\\"run the core simulation\\\"\\\"\\\"\\n t = 0\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n time_since_last_update = 0.0\\n progress = 1\\n while self.agreement() == False:\\n start_it = time.time()\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.x + self.dt * self.f(self.x, *self.f_arg)\\n if record_all:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n elif t - np.floor(t) < 0.01:\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time() - start_it\\n time_since_last_update += end\\n if time_since_last_update >= update_every:\\n sys.stdout.write('\\\\r' +\\n 'Iteration: {}, disagreement: {}, time: {}'.format(\\n progress, self.disagreement(), time.time() - start))\\n sys.stdout.flush()\\n time_since_last_update = 0.0\\n progress += 1\\n print('')\\n end = time.time()\\n return self.T[-1]\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n <function token>\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n\\n def delay_stable_max(self):\\n d = maximum_degree(self.graph)\\n return np.pi / (4 * d[1])\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n\\n def agreement(self, tol=1e-06):\\n \\\"\\\"\\\"Test for convergence\\\"\\\"\\\"\\n if self.disagreement() < tol:\\n return True\\n else:\\n return False\\n <function token>\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n\\n def __init__(self, topology, dynamics, dynamics_args, time_step=0.01,\\n x_init=None, convergence_warning=True, delay=0):\\n if isinstance(topology, nx.Graph):\\n self.graph = topology\\n self.size = len(self.graph)\\n else:\\n print('Argument Error: topology must be type', type(nx.Graph()))\\n if callable(dynamics):\\n self.f = dynamics\\n if len(dynamics_args) == 1:\\n self.f_arg = dynamics_args, 1\\n self.f_arg = dynamics_args\\n else:\\n print('Argument Error: dynamics must be a function')\\n self.dt = time_step\\n self.tau = delay\\n if not isinstance(x_init, type(np.ones(1))) and x_init == None:\\n self.x = np.linspace(1, self.size, self.size)\\n self.x = self.x.reshape(self.size, 1)\\n else:\\n self.x = x_init.copy().reshape(self.size, 1)\\n self.L = nx.laplacian_matrix(self.graph).todense()\\n self.X = list()\\n self.T = list()\\n self.warn = convergence_warning\\n self.d_max = max(np.array(self.graph.degree)[:, 1])\\n self.tau_max = np.pi / (4 * self.d_max)\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n <function token>\\n <function token>\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n <function token>\\n\\n def disagreement(self):\\n \\\"\\\"\\\"Returns the 'error'/inhomogeneity in the\\n decision vector\\\"\\\"\\\"\\n return 0.5 * np.dot(np.dot(np.transpose(self.x), self.L), self.x).item(\\n 0)\\n <function token>\\n <function token>\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\\n def sim_delay(self, delay=1, runtime=100):\\n t = 0\\n self.tau = delay\\n self.x_init = self.x\\n self.X = list()\\n self.T = list()\\n flag = False\\n for i in range(0, delay + 1):\\n self.X.append(self.x)\\n self.T.append(0)\\n start = time.time()\\n while self.agreement() == False:\\n if self.T[-1] > runtime:\\n break\\n if t == 0 and self.warn and not nx.is_connected(self.graph):\\n print(\\n 'Graph not connected, consensus algorithm will probably not converge!'\\n )\\n print('Simulating to 5 seconds...')\\n flag = True\\n if flag and time.time() - start > 5:\\n break\\n self.x = self.X[-1]\\n if len(self.X) - delay < 0:\\n pass\\n else:\\n index = len(self.X) - delay\\n self.x = self.X[-1] + self.dt * self.f(self.X[index], *self\\n .f_arg)\\n self.X.append(self.x)\\n self.T.append(time.time() - start)\\n t = t + self.dt\\n end = time.time()\\n return self.T[-1]\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n\\n\\nclass ConsensusSimulation:\\n <docstring token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n <function token>\\n\",\n \"<import token>\\n<class token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}},{"rowIdx":8699,"cells":{"index":{"kind":"number","value":8699,"string":"8,699"},"blob_id":{"kind":"string","value":"5ccfad17ede9f685ea9ef9c514c0108a61c2dfd6"},"code":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jul 18 13:39:05 2017\n\n@author: jaredhaeme15\n\"\"\"\n\n\nimport cv2\nimport numpy as np\nfrom collections import deque\nimport imutils\nimport misc_image_tools \n\nframeFileName = r\"H:\\Summer Research 2017\\Whirligig Beetle pictures and videos\\large1.mp4\"\ncap = cv2.VideoCapture(r\"H:\\Summer Research 2017\\Whirligig Beetle pictures and videos\\large1.mp4\")\n \nwhile(1): \n \n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break \n lower_hsv_thresholdcr = np.array([0,250,250])\n upper_hsv_thresholdcr = np.array([10,255,255])\n gray = np.float32(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY))\n dst = cv2.cornerHarris(gray,2,3,0.04)\n #result is dilated for marking the corners, not important\n dst = cv2.dilate(dst,None)\n frameWithRedCorners = np.copy(frame)\n # Threshold for an optimal value, it may vary depending on the image.\n frameWithRedCorners[dst>0.005*dst.max()]=[0,0,255]\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\n #construct a mask for the color \"green\", then perform\n # a series of dilations and erosions to remove any small\n # blobs left in the mask\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL,\n cv2.CHAIN_APPROX_SIMPLE)[-2]\n cv2.imshow(\"Frame\", frameWithRedCorners)\n k = cv2.waitKey(10000) & 0xFF\n if k == 27: # esc key\n break\ncv2.destroyAllWindows()\ncap.release()"},"steps":{"kind":"list like","value":["# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jul 18 13:39:05 2017\n\n@author: jaredhaeme15\n\"\"\"\n\n\nimport cv2\nimport numpy as np\nfrom collections import deque\nimport imutils\nimport misc_image_tools \n\nframeFileName = r\"H:\\Summer Research 2017\\Whirligig Beetle pictures and videos\\large1.mp4\"\ncap = cv2.VideoCapture(r\"H:\\Summer Research 2017\\Whirligig Beetle pictures and videos\\large1.mp4\")\n \nwhile(1): \n \n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break \n lower_hsv_thresholdcr = np.array([0,250,250])\n upper_hsv_thresholdcr = np.array([10,255,255])\n gray = np.float32(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY))\n dst = cv2.cornerHarris(gray,2,3,0.04)\n #result is dilated for marking the corners, not important\n dst = cv2.dilate(dst,None)\n frameWithRedCorners = np.copy(frame)\n # Threshold for an optimal value, it may vary depending on the image.\n frameWithRedCorners[dst>0.005*dst.max()]=[0,0,255]\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\n #construct a mask for the color \"green\", then perform\n # a series of dilations and erosions to remove any small\n # blobs left in the mask\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL,\n cv2.CHAIN_APPROX_SIMPLE)[-2]\n cv2.imshow(\"Frame\", frameWithRedCorners)\n k = cv2.waitKey(10000) & 0xFF\n if k == 27: # esc key\n break\ncv2.destroyAllWindows()\ncap.release()","<docstring token>\nimport cv2\nimport numpy as np\nfrom collections import deque\nimport imutils\nimport misc_image_tools\nframeFileName = (\n 'H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4'\n )\ncap = cv2.VideoCapture(\n 'H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4'\n )\nwhile 1:\n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break\n lower_hsv_thresholdcr = np.array([0, 250, 250])\n upper_hsv_thresholdcr = np.array([10, 255, 255])\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\n dst = cv2.dilate(dst, None)\n frameWithRedCorners = np.copy(frame)\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\n CHAIN_APPROX_SIMPLE)[-2]\n cv2.imshow('Frame', frameWithRedCorners)\n k = cv2.waitKey(10000) & 255\n if k == 27:\n break\ncv2.destroyAllWindows()\ncap.release()\n","<docstring token>\n<import token>\nframeFileName = (\n 'H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4'\n )\ncap = cv2.VideoCapture(\n 'H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4'\n )\nwhile 1:\n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break\n lower_hsv_thresholdcr = np.array([0, 250, 250])\n upper_hsv_thresholdcr = np.array([10, 255, 255])\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\n dst = cv2.dilate(dst, None)\n frameWithRedCorners = np.copy(frame)\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\n CHAIN_APPROX_SIMPLE)[-2]\n cv2.imshow('Frame', frameWithRedCorners)\n k = cv2.waitKey(10000) & 255\n if k == 27:\n break\ncv2.destroyAllWindows()\ncap.release()\n","<docstring token>\n<import token>\n<assignment token>\nwhile 1:\n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break\n lower_hsv_thresholdcr = np.array([0, 250, 250])\n upper_hsv_thresholdcr = np.array([10, 255, 255])\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\n dst = cv2.dilate(dst, None)\n frameWithRedCorners = np.copy(frame)\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\n CHAIN_APPROX_SIMPLE)[-2]\n cv2.imshow('Frame', frameWithRedCorners)\n k = cv2.waitKey(10000) & 255\n if k == 27:\n break\ncv2.destroyAllWindows()\ncap.release()\n","<docstring token>\n<import token>\n<assignment token>\n<code token>\n"],"string":"[\n \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nCreated on Tue Jul 18 13:39:05 2017\\n\\n@author: jaredhaeme15\\n\\\"\\\"\\\"\\n\\n\\nimport cv2\\nimport numpy as np\\nfrom collections import deque\\nimport imutils\\nimport misc_image_tools \\n\\nframeFileName = r\\\"H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4\\\"\\ncap = cv2.VideoCapture(r\\\"H:\\\\Summer Research 2017\\\\Whirligig Beetle pictures and videos\\\\large1.mp4\\\")\\n \\nwhile(1): \\n \\n successFlag, frame = cap.read()\\n if not successFlag:\\n cv2.waitKey(0)\\n break \\n lower_hsv_thresholdcr = np.array([0,250,250])\\n upper_hsv_thresholdcr = np.array([10,255,255])\\n gray = np.float32(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY))\\n dst = cv2.cornerHarris(gray,2,3,0.04)\\n #result is dilated for marking the corners, not important\\n dst = cv2.dilate(dst,None)\\n frameWithRedCorners = np.copy(frame)\\n # Threshold for an optimal value, it may vary depending on the image.\\n frameWithRedCorners[dst>0.005*dst.max()]=[0,0,255]\\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\\n #construct a mask for the color \\\"green\\\", then perform\\n # a series of dilations and erosions to remove any small\\n # blobs left in the mask\\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL,\\n cv2.CHAIN_APPROX_SIMPLE)[-2]\\n cv2.imshow(\\\"Frame\\\", frameWithRedCorners)\\n k = cv2.waitKey(10000) & 0xFF\\n if k == 27: # esc key\\n break\\ncv2.destroyAllWindows()\\ncap.release()\",\n \"<docstring token>\\nimport cv2\\nimport numpy as np\\nfrom collections import deque\\nimport imutils\\nimport misc_image_tools\\nframeFileName = (\\n 'H:\\\\\\\\Summer Research 2017\\\\\\\\Whirligig Beetle pictures and videos\\\\\\\\large1.mp4'\\n )\\ncap = cv2.VideoCapture(\\n 'H:\\\\\\\\Summer Research 2017\\\\\\\\Whirligig Beetle pictures and videos\\\\\\\\large1.mp4'\\n )\\nwhile 1:\\n successFlag, frame = cap.read()\\n if not successFlag:\\n cv2.waitKey(0)\\n break\\n lower_hsv_thresholdcr = np.array([0, 250, 250])\\n upper_hsv_thresholdcr = np.array([10, 255, 255])\\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\\n dst = cv2.dilate(dst, None)\\n frameWithRedCorners = np.copy(frame)\\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\\n CHAIN_APPROX_SIMPLE)[-2]\\n cv2.imshow('Frame', frameWithRedCorners)\\n k = cv2.waitKey(10000) & 255\\n if k == 27:\\n break\\ncv2.destroyAllWindows()\\ncap.release()\\n\",\n \"<docstring token>\\n<import token>\\nframeFileName = (\\n 'H:\\\\\\\\Summer Research 2017\\\\\\\\Whirligig Beetle pictures and videos\\\\\\\\large1.mp4'\\n )\\ncap = cv2.VideoCapture(\\n 'H:\\\\\\\\Summer Research 2017\\\\\\\\Whirligig Beetle pictures and videos\\\\\\\\large1.mp4'\\n )\\nwhile 1:\\n successFlag, frame = cap.read()\\n if not successFlag:\\n cv2.waitKey(0)\\n break\\n lower_hsv_thresholdcr = np.array([0, 250, 250])\\n upper_hsv_thresholdcr = np.array([10, 255, 255])\\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\\n dst = cv2.dilate(dst, None)\\n frameWithRedCorners = np.copy(frame)\\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\\n CHAIN_APPROX_SIMPLE)[-2]\\n cv2.imshow('Frame', frameWithRedCorners)\\n k = cv2.waitKey(10000) & 255\\n if k == 27:\\n break\\ncv2.destroyAllWindows()\\ncap.release()\\n\",\n \"<docstring token>\\n<import token>\\n<assignment token>\\nwhile 1:\\n successFlag, frame = cap.read()\\n if not successFlag:\\n cv2.waitKey(0)\\n break\\n lower_hsv_thresholdcr = np.array([0, 250, 250])\\n upper_hsv_thresholdcr = np.array([10, 255, 255])\\n gray = np.float32(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))\\n dst = cv2.cornerHarris(gray, 2, 3, 0.04)\\n dst = cv2.dilate(dst, None)\\n frameWithRedCorners = np.copy(frame)\\n frameWithRedCorners[dst > 0.005 * dst.max()] = [0, 0, 255]\\n hsv = cv2.cvtColor(frameWithRedCorners, cv2.COLOR_BGR2HSV)\\n crmask = cv2.inRange(hsv, lower_hsv_thresholdcr, upper_hsv_thresholdcr)\\n cntscr = cv2.findContours(crmask.copy(), cv2.RETR_EXTERNAL, cv2.\\n CHAIN_APPROX_SIMPLE)[-2]\\n cv2.imshow('Frame', frameWithRedCorners)\\n k = cv2.waitKey(10000) & 255\\n if k == 27:\\n break\\ncv2.destroyAllWindows()\\ncap.release()\\n\",\n \"<docstring token>\\n<import token>\\n<assignment token>\\n<code token>\\n\"\n]","isConversational":false},"error":{"kind":"bool","value":false,"string":"false"}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":86,"numItemsPerPage":100,"numTotalItems":100000,"offset":8600,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NjAyNDU4MCwic3ViIjoiL2RhdGFzZXRzL0NvaGVuUXUvdGhlLXN0YWNrLXYyLWRlZHVwLVB5dGhvbiIsImV4cCI6MTc3NjAyODE4MCwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.e5Hr13cUQLSxLqDJeMhkIWyd9Jkpr1qUQA-R7Eyo2lS38KlTWvuU5K4Hy0Eo8jjP7HVM78pgbkfC3F7AcubbBw","displayUrls":true,"splitSizeSummaries":[{"config":"0_100000","split":"train","numRows":100000,"numBytesParquet":1075633227},{"config":"100000_200000","split":"train","numRows":100000,"numBytesParquet":773849529},{"config":"1900000_2000000","split":"train","numRows":100000,"numBytesParquet":905561117},{"config":"2100000_2200000","split":"train","numRows":99999,"numBytesParquet":818411254},{"config":"2700000_2800000","split":"train","numRows":100000,"numBytesParquet":1131112800},{"config":"300000_400000","split":"train","numRows":100000,"numBytesParquet":1073321998},{"config":"500000_600000","split":"train","numRows":100000,"numBytesParquet":925113316}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
index int64 0 100k | blob_id stringlengths 40 40 | code stringlengths 7 7.27M | steps listlengths 1 1.25k | error bool 2
classes |
|---|---|---|---|---|
8,600 | e9659555938211d067919ee5e0083efb29d42d7b | # -*- coding: utf-8 -*-
# Generated by Django 1.10.5 on 2017-05-22 00:19
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('classroom', '0003_remove_anouncements_classroom'),
]
... | [
"# -*- coding: utf-8 -*-\n# Generated by Django 1.10.5 on 2017-05-22 00:19\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('classroom', '0003_remove_anouncements_class... | false |
8,601 | 2432e2b4da8af284055e7edf6e0bd94b7b293f0b | from __future__ import annotations
from .base import * # noqa
SECRET_KEY = "django-insecure-usp0sg081f=9+_j95j@-k^sfp+9c*!qrwh-m17%=_9^xot#9fn"
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql",
"NAME": "puka-test",
"USER": "jeff",
"PASSWORD": "",
"HOST... | [
"from __future__ import annotations\n\nfrom .base import * # noqa\n\nSECRET_KEY = \"django-insecure-usp0sg081f=9+_j95j@-k^sfp+9c*!qrwh-m17%=_9^xot#9fn\"\n\nDATABASES = {\n \"default\": {\n \"ENGINE\": \"django.db.backends.postgresql\",\n \"NAME\": \"puka-test\",\n \"USER\": \"jeff\",\n ... | false |
8,602 | 7727896d4e1b2b415c398b206f9fb7e228e6f26d | # DO NOT EDIT THIS FILE!
#
# Python module managedElementManager generated by omniidl
import omniORB
omniORB.updateModule("managedElementManager")
# ** 1. Stub files contributing to this module
import managedElementManager_idl
# ** 2. Sub-modules
# ** 3. End
| [
"# DO NOT EDIT THIS FILE!\n#\n# Python module managedElementManager generated by omniidl\n\nimport omniORB\nomniORB.updateModule(\"managedElementManager\")\n\n# ** 1. Stub files contributing to this module\nimport managedElementManager_idl\n\n# ** 2. Sub-modules\n\n# ** 3. End\n",
"import omniORB\nomniORB.updateM... | false |
8,603 | 9447d0d0481df3d0ee4273256d02977bc8044e4e | # -*- coding: utf-8 -*-
"""
python3
description :Fingerprint image enhancement by using gabor
"""
import os
import cv2
import math
import scipy
import numpy as np
from scipy import signal
def normalise(img):
normed = (img - np.mean(img)) / (np.std(img))
return normed
def ridge_segment(im, blksze, thresh):
... | [
"# -*- coding: utf-8 -*-\n\"\"\"\npython3\ndescription :Fingerprint image enhancement by using gabor\n\"\"\"\nimport os\nimport cv2\nimport math\nimport scipy\nimport numpy as np\nfrom scipy import signal\n\n\ndef normalise(img):\n normed = (img - np.mean(img)) / (np.std(img))\n return normed\n\n\ndef ridge_s... | false |
8,604 | 3b7c30718838a164eaf3aa12cd7b6a68930346f8 | '''Mock classes that imitate idlelib modules or classes.
Attributes and methods will be added as needed for tests.
'''
from idlelib.idle_test.mock_tk import Text
class Editor:
'''Minimally imitate EditorWindow.EditorWindow class.
'''
def __init__(self, flist=None, filename=None, key=None, root=None):
... | [
"'''Mock classes that imitate idlelib modules or classes.\n\nAttributes and methods will be added as needed for tests.\n'''\n\nfrom idlelib.idle_test.mock_tk import Text\n\nclass Editor:\n '''Minimally imitate EditorWindow.EditorWindow class.\n '''\n def __init__(self, flist=None, filename=None, key=None, ... | false |
8,605 | fc2748d766ebce8c9577f1eebc8435e2aa58ae25 |
import numpy as np
import random
import argparse
import networkx as nx
from gensim.models import Word2Vec
from utils import read_node_label, plot_embeddings
class node2vec_walk():
def __init__(self, nx_G, is_directed, p, q):
self.G = nx_G
self.is_directed = is_directed
self.p = p
... | [
"\n\nimport numpy as np\nimport random\n\nimport argparse\nimport networkx as nx\nfrom gensim.models import Word2Vec\n\nfrom utils import read_node_label, plot_embeddings\n\nclass node2vec_walk():\n\n def __init__(self, nx_G, is_directed, p, q):\n self.G = nx_G\n self.is_directed = is_directed\n ... | false |
8,606 | 3c8352ff2fc92ada1b58603df2a1a402e57842be | # coding: utf-8
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
driver = webdriver.Chrome()
driver.get("https://www.baidu.com")
elem = driver.find_element_by_xpath('//*[@id="kw"]')
elem.send_keys("python selenium", Keys.ENTER)
print(driver.page_source)
| [
"# coding: utf-8\r\n\r\n\r\nfrom selenium import webdriver\r\nfrom selenium.webdriver.common.keys import Keys\r\n\r\ndriver = webdriver.Chrome()\r\ndriver.get(\"https://www.baidu.com\")\r\n\r\nelem = driver.find_element_by_xpath('//*[@id=\"kw\"]')\r\nelem.send_keys(\"python selenium\", Keys.ENTER)\r\n\r\nprint(driv... | false |
8,607 | 7f62af951b49c3d1796c2811527ceb30ca931632 | import pandas as pd
from datetime import datetime
from iFinDPy import *
thsLogin = THS_iFinDLogin("iFind账号","iFind账号密码")
index_list = ['000001.SH','399001.SZ','399006.SZ']
result = pd.DataFrame()
today =datetime.today().strftime('%Y-%m-%d')
for index in index_list:
data_js = THS_DateSerial(index,'ths_pre_clo... | [
"import pandas as pd\nfrom datetime import datetime\nfrom iFinDPy import *\n\n\n\nthsLogin = THS_iFinDLogin(\"iFind账号\",\"iFind账号密码\")\n\n\nindex_list = ['000001.SH','399001.SZ','399006.SZ']\nresult = pd.DataFrame()\ntoday =datetime.today().strftime('%Y-%m-%d')\n\nfor index in index_list: \n data_js = THS_DateSe... | false |
8,608 | 465d5baae8d5be77fbf3d550d10667da420a8fbe | import sys
sys.path.append("../")
import numpy as np
import tensorflow as tf
from utils import eval_accuracy_main_cdan
from models import mnist2mnistm_shared_discrepancy, mnist2mnistm_predictor_discrepancy
import keras
import argparse
import pickle as pkl
parser = argparse.ArgumentParser(description='Traini... | [
"import sys\r\nsys.path.append(\"../\")\r\nimport numpy as np\r\nimport tensorflow as tf\r\nfrom utils import eval_accuracy_main_cdan\r\nfrom models import mnist2mnistm_shared_discrepancy, mnist2mnistm_predictor_discrepancy\r\nimport keras\r\nimport argparse\r\nimport pickle as pkl \r\n\r\nparser = argparse.Argumen... | false |
8,609 | 09905d4b5ad2e59578d874db171aafb6c42db105 | # Given an unsorted integer array nums, find the smallest missing positive integer.
class Solution:
def firstMissingPositive(self, nums: List[int]) -> int:
# if nums is emtpy, first pos int is 1
if not nums:
return 1
maxnum = max(nums) # for speed we assign max of nums to var max... | [
"# Given an unsorted integer array nums, find the smallest missing positive integer.\nclass Solution:\n def firstMissingPositive(self, nums: List[int]) -> int:\n # if nums is emtpy, first pos int is 1\n if not nums:\n return 1\n maxnum = max(nums) # for speed we assign max of nums... | false |
8,610 | 45d57f8392b89776f9349c32b4bb2fa71a4aaa83 | # -*- coding: utf-8 -*-
"""
A customised logger for this project for logging to the file and console
Created on 29/07/2022
@author: PNimbhore
"""
# imports
import os
import logging
class Logger:
"""
A custom logger which will take care
of logging to console and file.
"""
def __init__(self, filepat... | [
"# -*- coding: utf-8 -*-\n\"\"\"\nA customised logger for this project for logging to the file and console\nCreated on 29/07/2022\n@author: PNimbhore\n\"\"\"\n# imports\nimport os\nimport logging\n\n\nclass Logger:\n \"\"\"\n A custom logger which will take care\n of logging to console and file.\n \"\"\... | false |
8,611 | 530ec3df27cc4c8f0798566f0c66cfbffe510786 | import os
import subprocess
import sys
import time
# print sys.argv
start = time.time()
subprocess.call(sys.argv[1:], shell=True)
stop = time.time()
print "\nTook %.1f seconds" % (stop - start)
| [
"import os\r\nimport subprocess\r\nimport sys\r\nimport time\r\n\r\n# print sys.argv\r\nstart = time.time()\r\nsubprocess.call(sys.argv[1:], shell=True)\r\nstop = time.time()\r\nprint \"\\nTook %.1f seconds\" % (stop - start)\r\n"
] | true |
8,612 | 02c32cf04529ff8b5edddf4e4117f8c4fdf27da9 | class Formater():
def clean_number (posible_number):
sanitize_number = posible_number.replace(' ', '')
number_of_dots = sanitize_number.count('.')
if number_of_dots > 1:
return None
if number_of_dots == 1:
dot_position = sanitize_number.index('.')
... | [
"class Formater():\n def clean_number (posible_number):\n sanitize_number = posible_number.replace(' ', '')\n number_of_dots = sanitize_number.count('.')\n\n if number_of_dots > 1:\n return None\n if number_of_dots == 1:\n dot_position = sanitize_number.index('.'... | false |
8,613 | 2ccc3bb63445572610f6dbdfe5b1cbeef506c9a9 | from pygraphblas.matrix import Matrix
from pygraphblas.types import BOOL
from pyformlang.regular_expression import Regex
class Graph:
def __init__(self):
self.n_vertices = 0
self.label_matrices = dict()
self.start_vertices = set()
self.final_vertices = set()
def from_trans(self... | [
"from pygraphblas.matrix import Matrix\nfrom pygraphblas.types import BOOL\nfrom pyformlang.regular_expression import Regex\n\nclass Graph:\n def __init__(self):\n self.n_vertices = 0\n self.label_matrices = dict()\n self.start_vertices = set()\n self.final_vertices = set()\n\n def... | false |
8,614 | 55acae8129ddaba9a860d5d356e91f40607ac95a | def func(n):
return n*2
def my_map(f, seq):
return [f(item) for item in seq]
def main():
numbers = [1, 2, 3, 4]
result = list(map(func, numbers))
print(result)
result = [func(item) for item in numbers]
print(result)
if __name__ == '__main__':
main()
| [
"def func(n):\n return n*2\n\ndef my_map(f, seq):\n return [f(item) for item in seq]\n\ndef main():\n numbers = [1, 2, 3, 4]\n result = list(map(func, numbers))\n print(result)\n\n result = [func(item) for item in numbers]\n print(result)\n\n\nif __name__ == '__main__':\n main()\n",
"def f... | false |
8,615 | acd2d84529e197d6f9d134e8d7e25a51a442f3ae | # MÁSTER EN BIG DATA Y BUSINESS ANALYTICS
# MOD 1 - FINAL EVALUATION - EX. 2: dado un archivo que contiene en cada línea
# una palabra o conjunto de palabras seguido de un valor numérico denominado
# “sentimiento” y un conjunto de tweets, se pide calcular el sentimiento de
# aquellas palabras o conjunto de palabras que... | [
"# MÁSTER EN BIG DATA Y BUSINESS ANALYTICS\n# MOD 1 - FINAL EVALUATION - EX. 2: dado un archivo que contiene en cada línea\n# una palabra o conjunto de palabras seguido de un valor numérico denominado\n# “sentimiento” y un conjunto de tweets, se pide calcular el sentimiento de\n# aquellas palabras o conjunto de pal... | false |
8,616 | c485466a736fa0a4f183092e561a27005c01316d | import pylab,numpy as np
from numpy import sin
from matplotlib.patches import FancyArrowPatch
fig=pylab.figure()
w=1
h=1
th=3.14159/25.
x=np.r_[0,0,w,w,0]
y=np.r_[0,h,h-w*sin(th),0-w*sin(th),0]
pylab.plot(x,y)
x=np.r_[0,0,w/2.0,w/2.0,0]
y=np.r_[0,h/6.0,h/6.0-w/2.0*sin(th),0-w/2.0*sin(th),0]
pylab.plot(x... | [
"import pylab,numpy as np\r\nfrom numpy import sin\r\nfrom matplotlib.patches import FancyArrowPatch\r\n\r\nfig=pylab.figure()\r\nw=1\r\nh=1\r\nth=3.14159/25.\r\nx=np.r_[0,0,w,w,0]\r\ny=np.r_[0,h,h-w*sin(th),0-w*sin(th),0]\r\npylab.plot(x,y)\r\n\r\nx=np.r_[0,0,w/2.0,w/2.0,0]\r\ny=np.r_[0,h/6.0,h/6.0-w/2.0*sin(th),0... | false |
8,617 | 4e6e4917aee2385fe118d6e58c359a4c9fc50943 | # -*- coding: utf-8 -*-
'''
File Name: bubustatus/utils.py
Author: JackeyGao
mail: junqi.gao@shuyun.com
Created Time: 一 9/14 12:51:37 2015
'''
from rest_framework.views import exception_handler
def custom_exception_handler(exc, context):
# Call REST framework's default exception handler first,
# to get the st... | [
"# -*- coding: utf-8 -*-\n'''\nFile Name: bubustatus/utils.py\nAuthor: JackeyGao\nmail: junqi.gao@shuyun.com\nCreated Time: 一 9/14 12:51:37 2015\n'''\nfrom rest_framework.views import exception_handler\n\ndef custom_exception_handler(exc, context):\n # Call REST framework's default exception handler first,\n ... | false |
8,618 | c65969bba72142f4a328f978d78e0235cd56e393 | from huobi import RequestClient
from huobi.constant.test import *
request_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)
obj_list = request_client.get_cross_margin_loan_orders()
if len(obj_list):
for obj in obj_list:
obj.print_object()
print()
... | [
"from huobi import RequestClient\r\nfrom huobi.constant.test import *\r\n\r\n\r\nrequest_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)\r\nobj_list = request_client.get_cross_margin_loan_orders()\r\nif len(obj_list):\r\n for obj in obj_list:\r\n obj.print_object()\r\n print()\r\... | false |
8,619 | 4e538251dedfe0b9ffb68de2de7dc50681320f1f | #
# @lc app=leetcode id=267 lang=python3
#
# [267] Palindrome Permutation II
#
# https://leetcode.com/problems/palindrome-permutation-ii/description/
#
# algorithms
# Medium (33.28%)
# Total Accepted: 24.8K
# Total Submissions: 74.4K
# Testcase Example: '"aabb"'
#
# Given a string s, return all the palindromic perm... | [
"#\n# @lc app=leetcode id=267 lang=python3\n#\n# [267] Palindrome Permutation II\n#\n# https://leetcode.com/problems/palindrome-permutation-ii/description/\n#\n# algorithms\n# Medium (33.28%)\n# Total Accepted: 24.8K\n# Total Submissions: 74.4K\n# Testcase Example: '\"aabb\"'\n#\n# Given a string s, return all ... | true |
8,620 | 1b71789ba7c2191b433a405723fe6c985c926610 | # Generated by Django 2.2.6 on 2020-04-06 16:47
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='User',
fie... | [
"# Generated by Django 2.2.6 on 2020-04-06 16:47\r\n\r\nfrom django.db import migrations, models\r\nimport django.db.models.deletion\r\n\r\n\r\nclass Migration(migrations.Migration):\r\n\r\n initial = True\r\n\r\n dependencies = [\r\n ]\r\n\r\n operations = [\r\n migrations.CreateModel(\r\n ... | false |
8,621 | dfe7f0e25f340601886334c61a50806491a4ae2b | """Tests for our `neo login` subcommand."""
import pytest
import os
from neo.libs import login
from neo.libs import utils
class TestAuth:
@pytest.mark.run(order=0)
def test_do_login(self, monkeypatch):
login.load_env_file()
username = os.environ.get('OS_USERNAME')
passwd = os.environ.g... | [
"\"\"\"Tests for our `neo login` subcommand.\"\"\"\n\nimport pytest\nimport os\nfrom neo.libs import login\nfrom neo.libs import utils\n\nclass TestAuth:\n @pytest.mark.run(order=0)\n def test_do_login(self, monkeypatch):\n login.load_env_file()\n username = os.environ.get('OS_USERNAME')\n ... | false |
8,622 | a4eca0f5b7d5a03ca3600554ae3fe3b94c59fc68 | from os import environ
from process import process
from s3Service import put_object
environ['ACCESS_KEY'] = '1234567890'
environ['SECRET_KEY'] = '1234567890'
environ['ENDPOINT_URL'] = 'http://localhost:4566'
environ['REGION'] = 'us-east-1'
environ['BUCKET_GLOBAL'] = 'fl2-statement-global'
environ['BUCKET_GLOBAL_BACKUP... | [
"from os import environ\nfrom process import process\nfrom s3Service import put_object\n\nenviron['ACCESS_KEY'] = '1234567890'\nenviron['SECRET_KEY'] = '1234567890'\nenviron['ENDPOINT_URL'] = 'http://localhost:4566'\nenviron['REGION'] = 'us-east-1'\nenviron['BUCKET_GLOBAL'] = 'fl2-statement-global'\nenviron['BUCKET... | false |
8,623 | 09b2c1e69203f440754e82506b42e7856c94639a | from robotcar import RobotCar
import pdb
class RobotCar_Stub(RobotCar):
def forward(self):
print("Forward")
def backward(self):
print("Backward")
def left(self):
print("Left")
def right(self):
print("Right")
def stop(self):
print("Stop")
if __name__ == '__main__':
... | [
"from robotcar import RobotCar\nimport pdb\n\nclass RobotCar_Stub(RobotCar):\n\n def forward(self):\n print(\"Forward\")\n \n def backward(self):\n print(\"Backward\")\n \n def left(self):\n print(\"Left\")\n \n def right(self):\n print(\"Right\")\n \n def stop(self):\n print(\"Stop\... | false |
8,624 | 27e66b2a03bc626d5babd804e736a4652ba030d5 | #!/usr/bin/python2
import unittest
import luna_utils as luna
import time
API_URL = "com.webos.service.videooutput/"
VERBOSE_LOG = True
SUPPORT_REGISTER = False
SINK_MAIN = "MAIN"
SINK_SUB = "SUB0"
#TODO(ekwang): If you connect SUB, HAL error occurs. Just test MAIN in the current state
#SINK_LIST = [SINK_MAIN, SINK_... | [
"#!/usr/bin/python2\nimport unittest\nimport luna_utils as luna\nimport time\n\nAPI_URL = \"com.webos.service.videooutput/\"\n\nVERBOSE_LOG = True\nSUPPORT_REGISTER = False\n\nSINK_MAIN = \"MAIN\"\nSINK_SUB = \"SUB0\"\n\n#TODO(ekwang): If you connect SUB, HAL error occurs. Just test MAIN in the current state\n#SINK... | false |
8,625 | 49b007b723b9c43fb79d5dffa2546c856faf4937 | # _*_ coding:utf-8 _*_
from __future__ import unicode_literals
from django.db import models
from django.core.urlresolvers import reverse
# Create your models here.
# 本文件中，用__unicode__代替了__str__，以免在admin界面中显示中文而引发错误。
# 参考：http://blog.csdn.net/jiangnanandi/article/details/3574007
# 或者另一个解决方案：http://blog.sina.com.cn/s... | [
"# _*_ coding:utf-8 _*_\nfrom __future__ import unicode_literals\n\nfrom django.db import models\nfrom django.core.urlresolvers import reverse \n# Create your models here.\n\n\n# 本文件中，用__unicode__代替了__str__，以免在admin界面中显示中文而引发错误。\n# 参考：http://blog.csdn.net/jiangnanandi/article/details/3574007\n# 或者另一个解决方案：http://blo... | false |
8,626 | 45b2b611a80b93c9a7d8ec8a09e5838147e1ea76 | # Generated by Django 3.0.2 on 2020-08-27 16:03
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('info', '0010_auto_20200808_2117'),
]
operations = [
migrations.AddField(
model_name='profile',
name='annual_income',... | [
"# Generated by Django 3.0.2 on 2020-08-27 16:03\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('info', '0010_auto_20200808_2117'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='profile',\n na... | false |
8,627 | 5fe4f2738285d2f4b8bbfee2c4c6d15665737ea4 | from django.urls import path
from .views import *
urlpatterns = [
path('', ListUser.as_view() , name = 'list'),
path('register/', UserRegister.as_view() , name = 'register'),
path('login/', UserLogin.as_view() , name = 'login'),
path('delete/' , UserDelete.as_view() , name ='delete'),
path('update/... | [
"from django.urls import path\nfrom .views import *\n\nurlpatterns = [\n path('', ListUser.as_view() , name = 'list'),\n path('register/', UserRegister.as_view() , name = 'register'),\n path('login/', UserLogin.as_view() , name = 'login'),\n path('delete/' , UserDelete.as_view() , name ='delete'),\n ... | false |
8,628 | d3b6a105b14d9c3485a71058391a03c2f4aa5c10 | import pickle as pickle
import os
import pandas as pd
import torch
import numpy as np
import random
from sklearn.metrics import accuracy_score
from transformers import XLMRobertaTokenizer, XLMRobertaForSequenceClassification, Trainer, TrainingArguments, XLMRobertaConfig, ElectraForSequenceClassification, Electra... | [
"import pickle as pickle\r\nimport os\r\nimport pandas as pd\r\nimport torch\r\nimport numpy as np\r\nimport random\r\nfrom sklearn.metrics import accuracy_score\r\nfrom transformers import XLMRobertaTokenizer, XLMRobertaForSequenceClassification, Trainer, TrainingArguments, XLMRobertaConfig, ElectraForSequenceClas... | false |
8,629 | 5f56838ad0717c4f7a2da6b53f586a88b0166113 | from django.urls import path
from . import apiviews
from rest_framework.authtoken.views import obtain_auth_token
urlpatterns = [
path('contacts', apiviews.ContactsView.as_view(), name='contacts'),
path('contact/<int:pk>', apiviews.ContactView.as_view(), name='contact'),
path('signup', apiviews.create_user... | [
"from django.urls import path\nfrom . import apiviews\nfrom rest_framework.authtoken.views import obtain_auth_token\n\n\nurlpatterns = [\n path('contacts', apiviews.ContactsView.as_view(), name='contacts'),\n path('contact/<int:pk>', apiviews.ContactView.as_view(), name='contact'),\n path('signup', apiview... | false |
8,630 | fa5cbbd03641d2937e4502ce459d64d20b5ee227 |
import matplotlib.pyplot as plt
import numpy as np
from tti_explorer.contacts import he_infection_profile
plt.style.use('default')
loc = 0
# taken from He et al
gamma_params = {
'a': 2.11,
'loc': loc,
'scale': 1/0.69
}
t = 10
days = np.arange(t)
mass = he_infection_profile(t, gamma_params)
fig, ax = pl... | [
"\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfrom tti_explorer.contacts import he_infection_profile\n\nplt.style.use('default')\nloc = 0\n# taken from He et al\ngamma_params = {\n 'a': 2.11,\n 'loc': loc,\n 'scale': 1/0.69\n}\nt = 10\ndays = np.arange(t)\n\nmass = he_infection_profile(t, gamma... | false |
8,631 | 9a62a57f6d9af7ef09c8ed6e78a100df7978da6e | ID = '113'
TITLE = 'Path Sum II'
DIFFICULTY = 'Medium'
URL = 'https://oj.leetcode.com/problems/path-sum-ii/'
BOOK = False
PROBLEM = r"""Given a binary tree and a sum, find all root-to-leaf paths where each path's
sum equals the given sum.
For example:
Given the below binary tree and `sum = 22`,
... | [
"ID = '113'\nTITLE = 'Path Sum II'\nDIFFICULTY = 'Medium'\nURL = 'https://oj.leetcode.com/problems/path-sum-ii/'\nBOOK = False\nPROBLEM = r\"\"\"Given a binary tree and a sum, find all root-to-leaf paths where each path's\nsum equals the given sum.\n\nFor example: \nGiven the below binary tree and `sum = 22`,\n\n ... | false |
8,632 | 492c416becc44deaafef519eae8c9a82ac00cc0e | #!/usr/bin/python
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
ledPin = 4
pinOn = False
GPIO.setup(ledPin, GPIO.OUT)
GPIO.output(ledPin, GPIO.LOW)
def print_pin_status(pin_number):
GPIO.setup(pin_number, GPIO.IN)
value = GPIO.input(pin_number)
print(f'Current Value of {pin_number} is {value}')
G... | [
"#!/usr/bin/python\n\nimport RPi.GPIO as GPIO\n\nGPIO.setmode(GPIO.BCM)\n\nledPin = 4\npinOn = False\n\nGPIO.setup(ledPin, GPIO.OUT)\nGPIO.output(ledPin, GPIO.LOW)\n\n\ndef print_pin_status(pin_number):\n GPIO.setup(pin_number, GPIO.IN)\n value = GPIO.input(pin_number)\n print(f'Current Value of {pin_numbe... | false |
8,633 | 61232ec951cf378798220c00280ef2d351088d06 | import random
#liste de choix possibles
liste = ["rock", "paper", "scissors"]
#si le joueur veut jouer il répond y
answer = "y"
while answer == "y":
#choix du joueur
user_choice = input("rock,paper,scissors ?")
#verifie si le joueur a mis la réponse correcte
if user_choice in liste :
#choix d... | [
"import random\n\n#liste de choix possibles\nliste = [\"rock\", \"paper\", \"scissors\"]\n\n#si le joueur veut jouer il répond y\nanswer = \"y\"\nwhile answer == \"y\":\n #choix du joueur\n user_choice = input(\"rock,paper,scissors ?\")\n\n #verifie si le joueur a mis la réponse correcte\n if user_choic... | false |
8,634 | bf7676dc2c47d9cd2f1ce2d436202ae2c5061265 | from .base import GnuRecipe
class CAresRecipe(GnuRecipe):
def __init__(self, *args, **kwargs):
super(CAresRecipe, self).__init__(*args, **kwargs)
self.sha256 = '45d3c1fd29263ceec2afc8ff9cd06d5f' \
'8f889636eb4e80ce3cc7f0eaf7aadc6e'
self.name = 'c-ares'
self.ve... | [
"from .base import GnuRecipe\n\n\nclass CAresRecipe(GnuRecipe):\n def __init__(self, *args, **kwargs):\n super(CAresRecipe, self).__init__(*args, **kwargs)\n self.sha256 = '45d3c1fd29263ceec2afc8ff9cd06d5f' \\\n '8f889636eb4e80ce3cc7f0eaf7aadc6e'\n self.name = 'c-ares'\n... | false |
8,635 | f28222625e28939b34b1b5c21d28dbf9c49c6374 | import knn
datingDataMat,datingLabels = knn.file2matrix('datingTestSet2.txt')
normMat,ranges,minVals = knn.autoNorm(datingDataMat)
print normMat
print ranges
print minVals | [
"import knn\n\ndatingDataMat,datingLabels = knn.file2matrix('datingTestSet2.txt')\nnormMat,ranges,minVals = knn.autoNorm(datingDataMat)\n\nprint normMat\nprint ranges\nprint minVals"
] | true |
8,636 | e01b1f57a572571619d6c0981370030dc6105fd2 | import urllib.request
import urllib.parse
import json
content = input("请输入需要翻译的内容：")
url = 'http://fanyi.youdao.com/translate?smartresult=dict&smartresult=rule'
data = {}
data['action'] = 'FY_BY_CLICKBUTTION'
data['bv'] = '1ca13a5465c2ab126e616ee8d6720cc3'
data['client'] = 'fanyideskweb'
data['doctype'] = 'json'
dat... | [
"import urllib.request\nimport urllib.parse\nimport json\n\ncontent = input(\"请输入需要翻译的内容：\")\n\nurl = 'http://fanyi.youdao.com/translate?smartresult=dict&smartresult=rule'\n\ndata = {}\ndata['action'] = 'FY_BY_CLICKBUTTION'\ndata['bv'] = '1ca13a5465c2ab126e616ee8d6720cc3'\ndata['client'] = 'fanyideskweb'\ndata['doc... | false |
8,637 | c34ff2bbb0ba743268ace77c110ce0b283a25eba | f=open('p102_triangles.txt')
def cross(a,b,c):
t1=b[0]-a[0]
t2=b[1]-a[1]
t3=c[0]-a[0]
t4=c[1]-a[1]
return t1*t4-t2*t3
x=[0,0]
y=[0,0]
z=[0,0]
origin=(0,0)
ans=0
for i in f.xreadlines():
x[0],x[1],y[0],y[1],z[0],z[1]=map(int,i.split(','))
area1=abs(cross(x,y,z))
area2=abs(cross(x,y,orig... | [
"f=open('p102_triangles.txt')\n\ndef cross(a,b,c):\n t1=b[0]-a[0]\n t2=b[1]-a[1]\n t3=c[0]-a[0]\n t4=c[1]-a[1]\n return t1*t4-t2*t3\n\nx=[0,0]\ny=[0,0]\nz=[0,0]\norigin=(0,0)\nans=0\nfor i in f.xreadlines():\n x[0],x[1],y[0],y[1],z[0],z[1]=map(int,i.split(','))\n area1=abs(cross(x,y,z))\n ar... | true |
8,638 | 47587cce572807922344523d8c5fefb09552fe34 | import urllib, json
from PyQt4.QtCore import QRectF, Qt
from PyQt4.Qt import QPrinter, QPainter, QFont, QBrush, QColor, QPen, QImage
from PyQt4.QtGui import QApplication
# bkgimg = QImage()
# bkgimg.load("KosyMost.jpg", format = "jpg")
#
# print bkgimg
# exit()
def background(painter, bkgimg):
maxx = painter.d... | [
"import urllib, json\nfrom PyQt4.QtCore import QRectF, Qt\nfrom PyQt4.Qt import QPrinter, QPainter, QFont, QBrush, QColor, QPen, QImage\nfrom PyQt4.QtGui import QApplication\n\n\n# bkgimg = QImage()\n# bkgimg.load(\"KosyMost.jpg\", format = \"jpg\")\n# \n# print bkgimg\n# exit()\n\ndef background(painter, bkgimg):... | true |
8,639 | 75833617996549167fa157ff78cc1a11f870784f | import os
import sys
import glob
import shutil
import json
import codecs
from collections import OrderedDict
def getRegionClass(image_path, data_id, imgName):
region_class = ['nosmoke_background', 'nosmoke_face', 'nosmoke_suspect', 'nosmoke_cover', 'smoke_hand', 'smoke_nohand', 'smoke_hard']
label_class = ['nosmok... | [
"import os\nimport sys\nimport glob\nimport shutil\nimport json\nimport codecs\nfrom collections import OrderedDict\n\ndef getRegionClass(image_path, data_id, imgName):\n region_class = ['nosmoke_background', 'nosmoke_face', 'nosmoke_suspect', 'nosmoke_cover', 'smoke_hand', 'smoke_nohand', 'smoke_hard']\n label_c... | false |
8,640 | 894d8d00fd05bf8648f1b95ecf30b70e7b4e841b | #Copyright [2017] [Mauro Riva <lemariva@mail.com> <lemariva.com>]
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law ... | [
"#Copyright [2017] [Mauro Riva <lemariva@mail.com> <lemariva.com>]\n\n#Licensed under the Apache License, Version 2.0 (the \"License\");\n#you may not use this file except in compliance with the License.\n#You may obtain a copy of the License at\n\n#http://www.apache.org/licenses/LICENSE-2.0\n\n#Unless required by ... | false |
8,641 | 8f17c1ed0cb273a88b986cd7fe7a45439211d536 | ### Global parameters ###
seconds_per_unit_time = 0.01
#########################
pars_spont = {
"tau_p": 2.5,
"tau_d": 5.0,
"amp_p": 0.08,
"amp_d": -0.0533,
"rho": 0.0015,
"N": 50,
"w_max": 0.05,
"mu": 0.07,
"seed": None,
"tend": 50_000_000,
"r_in": 0.04,
"w_in": 0.05,... | [
"### Global parameters ###\n\nseconds_per_unit_time = 0.01\n\n#########################\n\npars_spont = {\n \"tau_p\": 2.5,\n \"tau_d\": 5.0,\n \"amp_p\": 0.08,\n \"amp_d\": -0.0533,\n \"rho\": 0.0015,\n \"N\": 50,\n \"w_max\": 0.05,\n \"mu\": 0.07,\n \"seed\": None,\n \"tend\": 50_000... | false |
8,642 | 7b5a16fdc536eb4ae3fdc08f827663613560187a | import subprocess
from whoosh.index import create_in
from whoosh.fields import *
import os
import codecs
from whoosh.qparser import QueryParser
import whoosh.index as index
import json
from autosub.autosub import autosub
from azure.storage.blob import AppendBlobService
vedio_formats = ['mp4','avi','wmv','mov'] # 1
aud... | [
"import subprocess\nfrom whoosh.index import create_in\nfrom whoosh.fields import *\nimport os\nimport codecs\nfrom whoosh.qparser import QueryParser\nimport whoosh.index as index\nimport json\nfrom autosub.autosub import autosub\nfrom azure.storage.blob import AppendBlobService\n\nvedio_formats = ['mp4','avi','wmv... | true |
8,643 | b1b9840fabc96c901e5ed45e22ee63af2f3550cb |
from os import listdir
from os.path import isfile, join
import sys
cat_list = dict();
def onImport():
mypath = "../../data/roget_processed";
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))];
for f_name in onlyfiles:
f_temp = open(mypath + "/" + f_name);
f_lines = f_temp.readlines();
for l... | [
"\nfrom os import listdir\nfrom os.path import isfile, join\nimport sys\n\ncat_list = dict();\n\ndef onImport():\n\tmypath = \"../../data/roget_processed\";\n\tonlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))];\n\tfor f_name in onlyfiles:\n\t\tf_temp = open(mypath + \"/\" + f_name);\n\t\tf_lines =... | false |
8,644 | 85bc304c69dac8bb570f920f9f12f558f4844c49 | listtuple = [(1,2), (2,3), (3,4), (4,5)]
dictn = dict(listtuple)
print(dictn) | [
"listtuple = [(1,2), (2,3), (3,4), (4,5)]\ndictn = dict(listtuple)\nprint(dictn)",
"listtuple = [(1, 2), (2, 3), (3, 4), (4, 5)]\ndictn = dict(listtuple)\nprint(dictn)\n",
"<assignment token>\nprint(dictn)\n",
"<assignment token>\n<code token>\n"
] | false |
8,645 | dce6ef64cf1a758ed25e11f626ce31206d18f960 | import os
from matplotlib import pyplot as plt
from matplotlib import colors
import numpy as np
class figure:
def __init__(self, dire, dpi, span, data, CIM,
learn_loss=None, eval_loss=None, different_dir_app=True, reference_steps=0, reveal_trend=1):
self.dire = self.new_num_directory(di... | [
"import os\nfrom matplotlib import pyplot as plt\nfrom matplotlib import colors\nimport numpy as np\n\n\nclass figure:\n\n def __init__(self, dire, dpi, span, data, CIM,\n learn_loss=None, eval_loss=None, different_dir_app=True, reference_steps=0, reveal_trend=1):\n\n self.dire = self.new_... | false |
8,646 | 4e31619efcaf6eeab3b32116b21e71de8202aee2 | from framework import *
from pebble_game import *
from constructive_pebble_game import *
from nose.tools import ok_
import numpy as np
# initialise the seed for reproducibility np.random.seed(102)
fw_2d = create_framework([0,1,2,3], [(0,1), (0,3), (1,2), (1,3), (2,3)], [(2,3), (4,4), (5,2), (1,1)])
# a 3d fw constric... | [
"from framework import *\nfrom pebble_game import *\nfrom constructive_pebble_game import *\nfrom nose.tools import ok_\nimport numpy as np\n\n# initialise the seed for reproducibility np.random.seed(102)\n\nfw_2d = create_framework([0,1,2,3], [(0,1), (0,3), (1,2), (1,3), (2,3)], [(2,3), (4,4), (5,2), (1,1)])\n# a ... | false |
8,647 | 24274dddbeb1be743cfcac331ee688d48c9a46dd | import requests
from bs4 import BeautifulSoup
'''
OCWから学院一覧を取得するスクリプト(6個くらいだから必要ない気もする)
gakuinListの各要素は次のような辞書に鳴っている
{
'name' : 学院名,
'url' : その学院の授業の一覧のurl,
}
'''
def getGakuinList():
url = "http://www.ocw.titech.ac.jp/"
response = requests.get(url)
soup = BeautifulSoup(response.content,"lxml")
topMainNav = sou... | [
"import requests\nfrom bs4 import BeautifulSoup\n\n'''\nOCWから学院一覧を取得するスクリプト(6個くらいだから必要ない気もする)\ngakuinListの各要素は次のような辞書に鳴っている\n{\n\t'name' : 学院名,\n\t'url' : その学院の授業の一覧のurl,\n}\n'''\ndef getGakuinList():\n\turl = \"http://www.ocw.titech.ac.jp/\"\n\tresponse = requests.get(url)\n\tsoup = BeautifulSoup(response.content,... | false |
8,648 | 4293ad0b2a4a352d6bdc4b860448c4a3b14ca629 | import torch
from torchvision import transforms
from torch.autograd import Variable
class NormalizeImageDict(object):
"""
Normalize image in dictionary
normalize range is True, the image is divided by 255
"""
def __init__(self,image_keys, normalizeRange=True):
self.image_keys = image_keys
... | [
"import torch\nfrom torchvision import transforms\nfrom torch.autograd import Variable\n\nclass NormalizeImageDict(object):\n \"\"\"\n Normalize image in dictionary\n normalize range is True, the image is divided by 255\n \"\"\"\n def __init__(self,image_keys, normalizeRange=True):\n self.imag... | false |
8,649 | b1dce573e6da81c688b338277af214838bbab9dd | def simple_formatter(zipcode: str, address: str) -> str:
return f'{zipcode}は「{address}」です'
| [
"def simple_formatter(zipcode: str, address: str) -> str:\n\n return f'{zipcode}は「{address}」です'\n\n\n",
"def simple_formatter(zipcode: str, address: str) ->str:\n return f'{zipcode}は「{address}」です'\n",
"<function token>\n"
] | false |
8,650 | 16dd73f2c85eff8d62cf0e605489d0db1616e36e | # Copyright The Linux Foundation and each contributor to CommunityBridge.
# SPDX-License-Identifier: MIT
"""
Holds the AWS SNS email service that can be used to send emails.
"""
import boto3
import os
import cla
import uuid
import json
import datetime
from cla.models import email_service_interface
region = os.enviro... | [
"# Copyright The Linux Foundation and each contributor to CommunityBridge.\n# SPDX-License-Identifier: MIT\n\n\"\"\"\nHolds the AWS SNS email service that can be used to send emails.\n\"\"\"\n\nimport boto3\nimport os\nimport cla\nimport uuid\nimport json\nimport datetime\nfrom cla.models import email_service_inter... | false |
8,651 | d508cb0a8d4291f1c8e76d9d720be352c05ef146 | """
Given a list of partitioned and sentiment-analyzed tweets, run several trials
to guess who won the election
"""
import json
import math
import sys
import pprint
import feature_vector
def positive_volume(f):
return f['relative_volume'] * f['positive_percent']
def inv_negative_volume(f):
return 1.0 - f['r... | [
"\"\"\"\nGiven a list of partitioned and sentiment-analyzed tweets, run several trials\nto guess who won the election\n\"\"\"\n\nimport json\nimport math\nimport sys\nimport pprint\n\nimport feature_vector\n\ndef positive_volume(f):\n return f['relative_volume'] * f['positive_percent']\n\ndef inv_negative_volume... | false |
8,652 | 2b3a42fed98b43cdd78edd751b306ba25328061a | import PyPDF2
from pathlib import Path
def get_filenames():
"""
Get PDF files not yet reordered in the current directory
:return: list of PDF file names
"""
filenames = []
for filename in Path('.').glob('*.pdf'):
if 'reordered' not in filename.stem:
filenames.append(filenam... | [
"import PyPDF2\nfrom pathlib import Path\n\n\ndef get_filenames():\n \"\"\"\n Get PDF files not yet reordered in the current directory\n :return: list of PDF file names\n \"\"\"\n filenames = []\n for filename in Path('.').glob('*.pdf'):\n if 'reordered' not in filename.stem:\n f... | false |
8,653 | f0c082968e26d414b0dbb679d4e5077056e99979 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import xmlrunner
import os
import sys
import glob
import yaml
ASSETS_DIR = ""
class GenerateMachineConfig(unittest.TestCase):
def setUp(self):
self.machine_configs = []
for machine_config_path in glob.glob(
f'{ASSETS_D... | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport unittest\nimport xmlrunner\n\nimport os\nimport sys\nimport glob\nimport yaml\n\nASSETS_DIR = \"\"\n\nclass GenerateMachineConfig(unittest.TestCase):\n def setUp(self):\n self.machine_configs = []\n for machine_config_path in glob.glob(\n ... | false |
8,654 | c5bdbcc8ba38b02e5e5cf8b53362e87ba761443d | from django.db import models
# Create your models here.
class Advertisement(models.Model):
title = models.CharField(max_length=1500, db_index=True, verbose_name='Заголовок')
description = models.TextField(blank=True)
created_at = models.DateTimeField(auto_now_add=True)
update_at = models.DateTimeFiel... | [
"from django.db import models\n\n# Create your models here.\n\n\nclass Advertisement(models.Model):\n title = models.CharField(max_length=1500, db_index=True, verbose_name='Заголовок')\n description = models.TextField(blank=True)\n created_at = models.DateTimeField(auto_now_add=True)\n update_at = model... | false |
8,655 | b84b3206e87176feee2c39fc0866ada994c9ac7a | from django.shortcuts import render
from PIL import Image
from django.views.decorators import csrf
import numpy as np
import re
import sys
import os
from .utils import *
from django.http import JsonResponse
from django.views.decorators.csrf import csrf_exempt
import base64
sys.path.append(os.path.abspath("./models"))
O... | [
"from django.shortcuts import render\nfrom PIL import Image\nfrom django.views.decorators import csrf\nimport numpy as np\nimport re\nimport sys\nimport os\nfrom .utils import *\nfrom django.http import JsonResponse\nfrom django.views.decorators.csrf import csrf_exempt\nimport base64\nsys.path.append(os.path.abspat... | false |
8,656 | 19962e94afdd3edf298b28b9954f479fefa3bba8 | #1. Create a greeting for your program.
print("Welcome to the Band Name Generator")
#2. Ask the user for the city that they grew up in.
city = input("Which city did you grew up in?\n")
#3. Ask the user for the name of a pet.
pet = input("What is the name of the pet?\n")
#4. Combine the name of their city and pet an... | [
"#1. Create a greeting for your program.\nprint(\"Welcome to the Band Name Generator\")\n\n#2. Ask the user for the city that they grew up in.\ncity = input(\"Which city did you grew up in?\\n\")\n\n#3. Ask the user for the name of a pet.\npet = input(\"What is the name of the pet?\\n\")\n\n#4. Combine the name of... | false |
8,657 | 129df937d7d295bae2009cfb65b2f85228206698 | # !/usr/bin/env python3
# -*- coding: UTF-8 -*-
# Copyright (c) 2021 Baidu, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | [
"# !/usr/bin/env python3\n# -*- coding: UTF-8 -*-\n# Copyright (c) 2021 Baidu, Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.... | false |
8,658 | bb6d6061365fad809448d09a1c031b984423b5e0 | __author__ = 'liwenchang'
#-*- coding:utf-8 -*-
import os
import time
import win32api, win32pdhutil, win32con, win32com.client
import win32pdh, string
def check_exsit(process_name):
WMI = win32com.client.GetObject('winmgmts:')
processCodeCov = WMI.ExecQuery('select * from Win32_Process where Name="%s"' % pro... | [
"__author__ = 'liwenchang'\n #-*- coding:utf-8 -*-\nimport os\nimport time\nimport win32api, win32pdhutil, win32con, win32com.client\nimport win32pdh, string\n\n\ndef check_exsit(process_name):\n WMI = win32com.client.GetObject('winmgmts:')\n processCodeCov = WMI.ExecQuery('select * from Win32_Process where N... | false |
8,659 | 2286aa1581ca7d6282b35847505a904980da275e | import cv2
import numpy as np
kernel = np.ones((3, 3), np.uint8)
def mask(image):
# define region of interest
green_frame = image[50:350, 50:350]
cv2.rectangle(image, (50, 50), (350, 350), (0, 255, 0), 0)
hsv = cv2.cvtColor(green_frame, cv2.COLOR_BGR2HSV)
# define range of skin color in HSV
lowe... | [
"import cv2\nimport numpy as np\nkernel = np.ones((3, 3), np.uint8)\ndef mask(image):\n # define region of interest\n green_frame = image[50:350, 50:350]\n cv2.rectangle(image, (50, 50), (350, 350), (0, 255, 0), 0)\n hsv = cv2.cvtColor(green_frame, cv2.COLOR_BGR2HSV)\n # define range of skin color in... | false |
8,660 | 687ab41e9ce94c8d14154a941504845a8fa9f2d9 | def test_number():
pass
| [
"def test_number():\n pass\n",
"<function token>\n"
] | false |
8,661 | e6d506dd45e72ee7f0162a884981ee1156153d3d | import json
import os
from lib.create import create_server, create_user
os.chdir(r'/home/niko/data/Marvin')
def edit_user_stats(server_id: str, user_id: str, stat: str, datas):
create_user(server_id, user_id)
if os.path.isfile("Server/{}/user.json".format(server_id)):
with open("Server/{}... | [
"import json\r\nimport os\r\n\r\nfrom lib.create import create_server, create_user\r\n\r\nos.chdir(r'/home/niko/data/Marvin')\r\n\r\n\r\ndef edit_user_stats(server_id: str, user_id: str, stat: str, datas):\r\n create_user(server_id, user_id)\r\n if os.path.isfile(\"Server/{}/user.json\".format(server_id)):\r\... | false |
8,662 | e44c4b2c3b60d34d4540ec2d3a782c777c52fbc0 | name = input("Введите ваше имя ")
print("Добрый день,", name)
| [
"name = input(\"Введите ваше имя \")\nprint(\"Добрый день,\", name)\n",
"name = input('Введите ваше имя ')\nprint('Добрый день,', name)\n",
"<assignment token>\nprint('Добрый день,', name)\n",
"<assignment token>\n<code token>\n"
] | false |
8,663 | ddb81e3ce0df44ee503c558b68b41c35935358a0 | #!/usr/bin/env python
"""Server that accepts and executes control-type commands on the bot."""
import sys
import os
from inspect import getmembers, ismethod
from simplejson.decoder import JSONDecodeError
import zmq
import signal
# This is required to make imports work
sys.path = [os.getcwd()] + sys.path
import bot.l... | [
"#!/usr/bin/env python\n\"\"\"Server that accepts and executes control-type commands on the bot.\"\"\"\n\nimport sys\nimport os\nfrom inspect import getmembers, ismethod\nfrom simplejson.decoder import JSONDecodeError\nimport zmq\nimport signal\n\n# This is required to make imports work\nsys.path = [os.getcwd()] + ... | false |
8,664 | 3fed96e9bedb157a14cf9c441de5aae8b4f6edc8 | import sys
import os
# Module "sys"
#
# See docs for the sys module: https://docs.python.org/3.7/library/sys.html
# Print out the command line arguments in sys.argv, one per line:
# Print out the plaform from sys:
# for arg in sys.argv:
# print(arg)
# Print out the Python version from sys:print(sys.platform)
... | [
"import sys\nimport os\n\n# Module \"sys\"\n#\n# See docs for the sys module: https://docs.python.org/3.7/library/sys.html\n\n# Print out the command line arguments in sys.argv, one per line:\n\n\n# Print out the plaform from sys:\n# for arg in sys.argv:\n# print(arg)\n\n\n# Print out the Python version from sy... | false |
8,665 | 0279057b3962e4b9839a86fc2e2683ac1da11b1a | from amqpstorm import management
if __name__ == '__main__':
# If using a self-signed certificate, change verify=True to point at your CA bundle.
# You can disable certificate verification for testing by passing in verify=False.
API = management.ManagementApi('https://rmq.amqpstorm.io:15671', 'guest',
... | [
"from amqpstorm import management\n\nif __name__ == '__main__':\n # If using a self-signed certificate, change verify=True to point at your CA bundle.\n # You can disable certificate verification for testing by passing in verify=False.\n API = management.ManagementApi('https://rmq.amqpstorm.io:15671', 'gue... | false |
8,666 | 03a13037a9a102397c8be4d9f0f4c5e150965808 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'mapGraph.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MapGraphTab(object):
def setupUi(self, MapGraphTab):
MapGra... | [
"# -*- coding: utf-8 -*-\n\n# Form implementation generated from reading ui file 'mapGraph.ui'\n#\n# Created by: PyQt5 UI code generator 5.9.2\n#\n# WARNING! All changes made in this file will be lost!\n\nfrom PyQt5 import QtCore, QtGui, QtWidgets\n\nclass Ui_MapGraphTab(object):\n def setupUi(self, MapGraphTab)... | false |
8,667 | 2611d7dd364f6a027da29c005754ac2465faa8be | from numpy import pi,sqrt,cross,dot,zeros,linalg
from defs import *
##from numba import njit, prange
##
##@njit(parallel=True)
def engparallelb2(MU,NU,b1,b2,x1,x2,y1,y2,eta,a):
#For use in enginteract below
#HL p.154 Eq.(6-45)
b1x=b1[0]
b1y=b1[1]
b1z=b1[2]
b2x=b2[0]
b2y=b2[1]
b2z=b2[2]
... | [
"from numpy import pi,sqrt,cross,dot,zeros,linalg\n\nfrom defs import *\n##from numba import njit, prange\n##\n##@njit(parallel=True)\n\n\ndef engparallelb2(MU,NU,b1,b2,x1,x2,y1,y2,eta,a):\n\n#For use in enginteract below\n#HL p.154 Eq.(6-45)\n\n b1x=b1[0]\n b1y=b1[1]\n b1z=b1[2]\n\n b2x=b2[0]\n b2y=... | false |
8,668 | 2350c2ab05499f1b40ba61f2101c51d9581d57f6 |
def addnumber(i,j):
sum= i+j
print(sum)
num1 = int(input("Enter 1st number"))
num2 = int(input("Enter 2nd number"))
z = addnumber(num1,num2)
| [
"\n\n\ndef addnumber(i,j):\n sum= i+j\n print(sum)\n\nnum1 = int(input(\"Enter 1st number\"))\nnum2 = int(input(\"Enter 2nd number\"))\nz = addnumber(num1,num2)\n\n\n",
"def addnumber(i, j):\n sum = i + j\n print(sum)\n\n\nnum1 = int(input('Enter 1st number'))\nnum2 = int(input('Enter 2nd number'))\nz... | false |
8,669 | 5f8303ce91c5de779bbddbaafb3fb828596babe5 | # orm/relationships.py
# Copyright (C) 2005-2023 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
"""Heuristics related to join conditions as used in
:func:`_orm.relationship`.... | [
"# orm/relationships.py\n# Copyright (C) 2005-2023 the SQLAlchemy authors and contributors\n# <see AUTHORS file>\n#\n# This module is part of SQLAlchemy and is released under\n# the MIT License: https://www.opensource.org/licenses/mit-license.php\n\n\"\"\"Heuristics related to join conditions as used in\n:func:`_or... | false |
8,670 | e486e0ab91a8f5671435f5bbcf5340a62a970d3a | class SmartChineseAnalyzer:
def __init__(self):
pass
def create_components(self, filename):
#tokenizer = SentenceTokenize(filename)
#result = WordTokenFilter(tokenizer)
#result = PorterStemFilter(result)
if self.stopwords:
result = StopFilter(result,... | [
"class SmartChineseAnalyzer:\n def __init__(self):\n pass\n\n def create_components(self, filename):\n #tokenizer = SentenceTokenize(filename)\n #result = WordTokenFilter(tokenizer)\n #result = PorterStemFilter(result)\n \n if self.stopwords:\n result = Sto... | false |
8,671 | ef5c51a5c706387b62ef3f40c7cadf7dbef6d082 | from flask_minify.utils import get_optimized_hashing
class MemoryCache:
def __init__(self, store_key_getter=None, limit=0):
self.store_key_getter = store_key_getter
self.limit = limit
self._cache = {}
self.hashing = get_optimized_hashing()
@property
def store(self):
... | [
"from flask_minify.utils import get_optimized_hashing\n\n\nclass MemoryCache:\n def __init__(self, store_key_getter=None, limit=0):\n self.store_key_getter = store_key_getter\n self.limit = limit\n self._cache = {}\n self.hashing = get_optimized_hashing()\n\n @property\n def sto... | false |
8,672 | 42187f460a64572d2581ed5baec41eaff47466f8 | version https://git-lfs.github.com/spec/v1
oid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49
size 964
| [
"version https://git-lfs.github.com/spec/v1\noid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49\nsize 964\n"
] | true |
8,673 | 83be35b79dcaa34f9273281976ebb71e81c58cdd | import logging
import os
import time
from datetime import datetime
from pathlib import Path
from configargparse import ArgumentParser
from cryptography import x509
from cryptography.hazmat.backends import default_backend
from cryptography.x509.oid import ExtensionOID
from cryptography.x509.extensions import ExtensionN... | [
"import logging\nimport os\nimport time\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom configargparse import ArgumentParser\nfrom cryptography import x509\nfrom cryptography.hazmat.backends import default_backend\nfrom cryptography.x509.oid import ExtensionOID\nfrom cryptography.x509.extensions im... | false |
8,674 | dac8dbb0eba78d4f8dfbe3284325735324a87dc2 | """
时间最优
思路：
将和为目标值的那 两个 整数定义为 num1 和 num2
创建一个新字典，内容存在数组中的数字及索引
将数组nums转换为字典，
遍历字典， num1为字典中的元素（其实与数组总的元素一样），
num2 为 target减去num1， 判定num2是否在字典中，如果存在，返回字典中num2的值（也就是在数组nums中的下标）和 i（也就是num1在数组中的下标）
如果不存在，设置字典num1的值为i
"""
def two_sum(nums, target):
dct = {}
for i, num1 in enumerate(nums):
... | [
"\"\"\"\r\n时间最优\r\n\r\n思路：\r\n将和为目标值的那 两个 整数定义为 num1 和 num2\r\n创建一个新字典，内容存在数组中的数字及索引\r\n将数组nums转换为字典，\r\n遍历字典， num1为字典中的元素（其实与数组总的元素一样），\r\nnum2 为 target减去num1， 判定num2是否在字典中，如果存在，返回字典中num2的值（也就是在数组nums中的下标）和 i（也就是num1在数组中的下标）\r\n如果不存在，设置字典num1的值为i\r\n\"\"\"\r\n\r\ndef two_sum(nums, target):\r\n dct = {}\r\n f... | false |
8,675 | 60d8276a5715899823b12ffdf132925c6f2693bd | from __future__ import annotations
from typing import TYPE_CHECKING
from datetime import datetime
from sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer
from sqlalchemy.orm import relationship
from app.db.base_class import Base
if TYPE_CHECKING:
from .account import Account # noqa: F401
... | [
"from __future__ import annotations\n\n\nfrom typing import TYPE_CHECKING\nfrom datetime import datetime\n\nfrom sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer\nfrom sqlalchemy.orm import relationship\n\nfrom app.db.base_class import Base\n\nif TYPE_CHECKING:\n from .account import Accoun... | false |
8,676 | c87ede0e3c6d4cc305450f68b4cf61fb63986760 | import uvicore
from uvicore.support import module
from uvicore.typing import Dict, List
from uvicore.support.dumper import dump, dd
from uvicore.contracts import Email
@uvicore.service()
class Mail:
def __init__(self, *,
mailer: str = None,
mailer_options: Dict = None,
to: List = [],
... | [
"import uvicore\nfrom uvicore.support import module\nfrom uvicore.typing import Dict, List\nfrom uvicore.support.dumper import dump, dd\nfrom uvicore.contracts import Email\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *,\n mailer: str = None,\n mailer_options: Dict = None,\n t... | false |
8,677 | 4a8a733a965e25ad7ef53600fad6dd47343655b0 | # -*- coding: utf-8 -*-
"""
Created on Wed Apr 12 16:38:22 2017
@author: secoder
"""
import io
import random
import nltk
from nltk.tokenize import RegexpTokenizer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from collections import Ordered... | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 12 16:38:22 2017\n\n@author: secoder\n\"\"\"\nimport io\nimport random\nimport nltk\nfrom nltk.tokenize import RegexpTokenizer\n\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\n\n\nfrom... | false |
8,678 | 74028a7b317c02c90603ad24c1ddb35a1d5d0e9d | student = []
while True:
name = str(input('Name: ')).capitalize().strip()
grade1 = float(input('Grade 1: '))
grade2 = float(input('Grade 2: '))
avgrade = (grade1 + grade2) / 2
student.append([name, [grade1, grade2], avgrade])
resp = ' '
while resp not in 'NnYy':
resp = str(input('Ano... | [
"student = []\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n student.append([name, [grade1, grade2], avgrade])\n resp = ' '\n while resp not in 'NnYy':\n resp = ... | false |
8,679 | 606abf8501d85c29051df4bf0276ed5b098ee6c5 | from django.contrib import admin
from search.models import PrimaryCategory,PlaceCategory
class PrimaryCategoryAdmin(admin.ModelAdmin):
list_display = ('primary_name','is_active','description','image',)
actions = None
def has_delete_permission(self,request,obj=None):
return False
... | [
"from django.contrib import admin\nfrom search.models import PrimaryCategory,PlaceCategory\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n \n list_display = ('primary_name','is_active','description','image',)\n actions = None\n \n def has_delete_permission(self,request,obj=None):\n return F... | false |
8,680 | 932502c93dd7dfc095adfe2ab88b4404396d9845 | # Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# d... | [
"# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, so... | false |
8,681 | 7c6ada250770e04b395dda774a78042da69e2854 | from collections import Counter
def main():
N = int(input())
A = tuple(map(int, input().split()))
c = Counter(A).most_common()
if c[0][0] == 0 and c[0][1] == N:
print("Yes")
elif len(c) == 2 and c[0][1] == 2*N//3 and c[1][0] == 0 and c[1][1] == N//3:
print("Yes")
elif ... | [
"from collections import Counter\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n \n c = Counter(A).most_common()\n \n if c[0][0] == 0 and c[0][1] == N:\n print(\"Yes\")\n elif len(c) == 2 and c[0][1] == 2*N//3 and c[1][0] == 0 and c[1][1] == N//3:\n prin... | false |
8,682 | 130581ddb0394dcceabc316468385d4e21959b63 | import unittest
from domain.Activity import Activity
from domain.NABException import NABException
from domain.Person import Person
from domain.ActivityValidator import ActivityValidator
from repository.PersonRepository import PersonRepository
from repository.PersonFileRepository import PersonFileRepository
from reposit... | [
"import unittest\nfrom domain.Activity import Activity\nfrom domain.NABException import NABException\nfrom domain.Person import Person\nfrom domain.ActivityValidator import ActivityValidator\nfrom repository.PersonRepository import PersonRepository\nfrom repository.PersonFileRepository import PersonFileRepository\n... | false |
8,683 | e7d63c3b56459297eb67c56e93a3c640d93e5f6d | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import tensorflow
from pyspark.sql.functions import split
from pyspark.ml.fpm import FPGrowth
from pyspark.sql import SparkSession
from pyspark import SparkConf
from pyspark.sql.functions import udf, array
import re
from pyspark.sql.types import *
import pyspark.sql.functi... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport tensorflow\nfrom pyspark.sql.functions import split\nfrom pyspark.ml.fpm import FPGrowth\nfrom pyspark.sql import SparkSession\nfrom pyspark import SparkConf\nfrom pyspark.sql.functions import udf, array\nimport re\nfrom pyspark.sql.types import *\nimport pys... | false |
8,684 | e403be68894ba283d71a0b71bb0bfd0adfab8c41 | import logging
def log_func(handler):
if handler.get_status() < 400:
log_method = logging.info
elif handler.get_status() < 500:
log_method = logging.warning
else:
log_method = logging.error
request_time = 1000.0 * handler.request.request_time()
log_method("%d %s %s (%s) %s ... | [
"import logging\n\n\ndef log_func(handler):\n if handler.get_status() < 400:\n log_method = logging.info\n elif handler.get_status() < 500:\n log_method = logging.warning\n else:\n log_method = logging.error\n request_time = 1000.0 * handler.request.request_time()\n log_method(\"... | false |
8,685 | 5c179752f4c4e1d693346c6edddd79211a895735 | valor1=input("Ingrese Primera Cantidad ")
valor2=input("Ingrese Segunda Cantidad ")
Total = valor1 + valor2
print "El total es: " + str(Total)
| [
"valor1=input(\"Ingrese Primera Cantidad \")\nvalor2=input(\"Ingrese Segunda Cantidad \")\nTotal = valor1 + valor2\nprint \"El total es: \" + str(Total)\n"
] | true |
8,686 | ec2d3bbfce06c498790afd491931df3f391dafbe | ../PyFoam/bin/pyFoamPlotWatcher.py | [
"../PyFoam/bin/pyFoamPlotWatcher.py"
] | true |
8,687 | 022f588455d8624d0b0107180417f65816254cb1 | class car:
def info(self):
print(self.speed,self. color,self.model)
def increment(self):
print('increment')
def decrement(self):
print ('decrement')
BMW = car()
BMW.speed = 320
BMW.color = 'red'
BMW.model = 1982
BMW.info()
Camry = car()
Camry.speed = 220
Camry.col... | [
"class car:\r\n\r\n def info(self):\r\n print(self.speed,self. color,self.model)\r\n def increment(self):\r\n print('increment')\r\n def decrement(self):\r\n print ('decrement')\r\n\r\nBMW = car()\r\nBMW.speed = 320\r\nBMW.color = 'red'\r\nBMW.model = 1982\r\nBMW.info()\r\n\r\nCamry = ... | false |
8,688 | a494b3469682a909b76e67e1b78ad25affe99f24 | # Your code here
d = dict()
count = 0
fave_fast_food = input("Fave fast food restaurant: ")
for i in range(1, 11):
if fave_fast_food in d:
d[fave_fast_food] += 1
else:
d[fave_fast_food] = 1
count+= 1
fave_fast_food = input("Fave fast food restaurant: ")
for k,v in d.items():
print('Fast Food R... | [
"# Your code here\nd = dict()\ncount = 0\nfave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor i in range(1, 11):\n if fave_fast_food in d:\n d[fave_fast_food] += 1\n else:\n d[fave_fast_food] = 1\n count+= 1\n fave_fast_food = input(\"Fave fast food restaurant: \")\n\nfor k,v in d.items():\... | false |
8,689 | a87ab07bb1502a75a7e705cd5c92db829ebdd966 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import json
from flask import jsonify
from flask import make_response
from MultipleInterfaceManager.settings import STATUS_CODE
def _render(resp):
response = make_response(jsonify(resp))
# response.headers["Access-Control-Allow-Origin"] = "*"
return ... | [
"#!/usr/bin/python\r\n# -*- coding: utf-8 -*-\r\n\r\nimport json\r\n\r\nfrom flask import jsonify\r\nfrom flask import make_response\r\nfrom MultipleInterfaceManager.settings import STATUS_CODE\r\n\r\n\r\ndef _render(resp):\r\n response = make_response(jsonify(resp))\r\n# response.headers[\"Access-Control-All... | false |
8,690 | 24891cdefcd061f04e7b7768b1bde4e32b78adcc | import heapq
from util import edit_distance
def autocomplete(suggest_tree, bktree, prefix, count=5):
"""Suggest top completions for a prefix given a SuggestTree and BKTree.
Completions for a given prefix are weighted primarily by their weight in the
suggest tree, and secondarily by their Levenshtein... | [
"import heapq\nfrom util import edit_distance\n\n\ndef autocomplete(suggest_tree, bktree, prefix, count=5):\n \"\"\"Suggest top completions for a prefix given a SuggestTree and BKTree.\n \n Completions for a given prefix are weighted primarily by their weight in the \n suggest tree, and secondarily by t... | false |
8,691 | b934770e9e57a0ead124e245f394433ce853dec9 | import time
import machine
from machine import Timer
import network
import onewire, ds18x20
import ujson
import ubinascii
from umqtt.simple import MQTTClient
import ntptime
import errno
#Thrown if an error that is fatal occurs,
#stop measurement cycle.
class Error(Exception):
pass
#Thrown if an error that is not ... | [
"import time\nimport machine\nfrom machine import Timer\nimport network\nimport onewire, ds18x20\nimport ujson\nimport ubinascii\nfrom umqtt.simple import MQTTClient\nimport ntptime\nimport errno\n\n#Thrown if an error that is fatal occurs,\n#stop measurement cycle.\nclass Error(Exception):\n pass\n\n#Thrown if ... | false |
8,692 | 5d3b9005b8924da36a5885201339aa41082034cd | from selenium.webdriver.common.by import By
class BasePageLocators:
LOGIN_LINK = (By.CSS_SELECTOR, "#login_link")
BASKET_LINK = (By.CSS_SELECTOR, '[class="btn btn-default"]:nth-child(1)')
USER_ICON = (By.CSS_SELECTOR, ".icon-user")
class LoginPageLocators:
LOG_IN_FORM = (By.CSS_SELECTOR, "#login_for... | [
"from selenium.webdriver.common.by import By\n\n\nclass BasePageLocators:\n LOGIN_LINK = (By.CSS_SELECTOR, \"#login_link\")\n BASKET_LINK = (By.CSS_SELECTOR, '[class=\"btn btn-default\"]:nth-child(1)')\n USER_ICON = (By.CSS_SELECTOR, \".icon-user\")\n\n\nclass LoginPageLocators:\n LOG_IN_FORM = (By.CSS_... | false |
8,693 | 252a6b97f108b7fdc165ccb2a7f61ce31f129d3d | import sys
from collections import namedtuple
from PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \
QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem
from PyQt5.QtCore import Qt, QSize
from runWidget import RunWidget
from recordWidget import RecordWidget
def QListWidget_qss():
return ... | [
"import sys\nfrom collections import namedtuple\nfrom PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \\\n QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem\nfrom PyQt5.QtCore import Qt, QSize\n\nfrom runWidget import RunWidget\nfrom recordWidget import RecordWidget\n\n\ndef QListWidget_qs... | false |
8,694 | 57bc34c6a23c98fd031ea6634441d4d135c06590 | import sys
sys.path.append("./")
from torchtext.datasets import Multi30k
from torchtext.data import Field
from torchtext import data
import pickle
import models.transformer as h
import torch
from datasets import load_dataset
from torch.utils.data import DataLoader
from metrics.metrics import bleu
import numpy as np
fro... | [
"import sys\nsys.path.append(\"./\")\nfrom torchtext.datasets import Multi30k\nfrom torchtext.data import Field\nfrom torchtext import data\nimport pickle\nimport models.transformer as h\nimport torch\nfrom datasets import load_dataset\nfrom torch.utils.data import DataLoader\nfrom metrics.metrics import bleu\nimpo... | false |
8,695 | f6401eca2dc0ea86a934e859c35fa2d6c85a61b3 | import turtle
hexagon = turtle.Turtle()
for i in range (6):
hexagon.forward(100)
hexagon.left(60)
| [
"import turtle\r\nhexagon = turtle.Turtle()\r\nfor i in range (6):\r\n hexagon.forward(100)\r\n hexagon.left(60)\r\n ",
"import turtle\nhexagon = turtle.Turtle()\nfor i in range(6):\n hexagon.forward(100)\n hexagon.left(60)\n",
"<import token>\nhexagon = turtle.Turtle()\nfor i in range(6):\n ... | false |
8,696 | 4932a357cfd60cb65630345e75794ebf58b82c82 | import matplotlib; matplotlib.use('agg')
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from uncertainties import ufloat
#Holt Werte aus Textdatei
I, U = np.genfromtxt('werte2.txt', unpack=True)
#Definiert Funktion mit der ihr fitten wollt (hier eine Gerade)
def f(x,... | [
"import matplotlib; matplotlib.use('agg')\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nfrom scipy.optimize import curve_fit\r\nfrom uncertainties import ufloat\r\n\r\n#Holt Werte aus Textdatei\r\nI, U = np.genfromtxt('werte2.txt', unpack=True)\r\n\r\n#Definiert Funktion mit der ihr fitten wollt (hier... | false |
8,697 | 641cbe2f35925d070249820a2e3a4f1cdd1cf642 | # -*- coding: utf-8 -*-
"""
app definition
"""
from django.apps import AppConfig
class CoopHtmlEditorAppConfig(AppConfig):
name = 'coop_html_editor'
verbose_name = "Html Editor"
| [
"# -*- coding: utf-8 -*-\n\"\"\"\napp definition\n\"\"\"\n\nfrom django.apps import AppConfig\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n name = 'coop_html_editor'\n verbose_name = \"Html Editor\"\n",
"<docstring token>\nfrom django.apps import AppConfig\n\n\nclass CoopHtmlEditorAppConfig(AppConfig):\n... | false |
8,698 | 3164eab8dc221149c9f865645edf9991d810d2ac | import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
import time
import sys
class ConsensusSimulation:
"""Class to model a general consensus problem
see DOI: 10.1109/JPROC.2006.887293"""
def __init__(self,
topology,
dynamics,
dynami... | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport time\nimport sys\n\nclass ConsensusSimulation:\n \"\"\"Class to model a general consensus problem\n see DOI: 10.1109/JPROC.2006.887293\"\"\"\n def __init__(self,\n topology,\n dynamics,\n... | false |
8,699 | 5ccfad17ede9f685ea9ef9c514c0108a61c2dfd6 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 18 13:39:05 2017
@author: jaredhaeme15
"""
import cv2
import numpy as np
from collections import deque
import imutils
import misc_image_tools
frameFileName = r"H:\Summer Research 2017\Whirligig Beetle pictures and videos\large1.mp4"
cap = cv2.VideoCapture(r"H:\Summer ... | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jul 18 13:39:05 2017\n\n@author: jaredhaeme15\n\"\"\"\n\n\nimport cv2\nimport numpy as np\nfrom collections import deque\nimport imutils\nimport misc_image_tools \n\nframeFileName = r\"H:\\Summer Research 2017\\Whirligig Beetle pictures and videos\\large1.mp4\"\ncap ... | false |
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