762 lines
28 KiB
Python
762 lines
28 KiB
Python
import sys
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import uuid
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from typing import (
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AbstractSet,
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Any,
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Callable,
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Dict,
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List,
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Mapping,
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MutableSequence,
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Optional,
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Sequence,
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Set,
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TYPE_CHECKING,
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Type,
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Union,
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cast,
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)
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try:
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import orjson as json
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except ImportError: # pragma: no cover
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import json # type: ignore
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import databases
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import pydantic
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import sqlalchemy
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from pydantic import BaseModel
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import ormar # noqa I100
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from ormar.exceptions import ModelError, ModelPersistenceError
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from ormar.fields import BaseField
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from ormar.fields.foreign_key import ForeignKeyField
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from ormar.models.helpers import register_relation_in_alias_manager
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from ormar.models.helpers.relations import expand_reverse_relationship
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from ormar.models.helpers.sqlalchemy import (
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populate_meta_sqlalchemy_table_if_required,
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update_column_definition,
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)
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from ormar.models.helpers.validation import validate_choices
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from ormar.models.metaclass import ModelMeta, ModelMetaclass
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from ormar.models.modelproxy import ModelTableProxy
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from ormar.queryset.utils import translate_list_to_dict
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from ormar.relations.alias_manager import AliasManager
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from ormar.relations.relation_manager import RelationsManager
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if TYPE_CHECKING: # pragma no cover
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from ormar.models import Model
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from ormar.signals import SignalEmitter
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IntStr = Union[int, str]
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DictStrAny = Dict[str, Any]
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AbstractSetIntStr = AbstractSet[IntStr]
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MappingIntStrAny = Mapping[IntStr, Any]
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class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass):
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"""
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Main base class of ormar Model.
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Inherits from pydantic BaseModel and has all mixins combined in ModelTableProxy.
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Constructed with ModelMetaclass which in turn also inherits pydantic metaclass.
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Abstracts away all internals and helper functions, so final Model class has only
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the logic concerned with database connection and data persistance.
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"""
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__slots__ = ("_orm_id", "_orm_saved", "_orm", "_pk_column")
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if TYPE_CHECKING: # pragma no cover
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pk: Any
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__model_fields__: Dict[str, BaseField]
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__table__: sqlalchemy.Table
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__fields__: Dict[str, pydantic.fields.ModelField]
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__pydantic_model__: Type[BaseModel]
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__pkname__: str
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__tablename__: str
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__metadata__: sqlalchemy.MetaData
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__database__: databases.Database
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_orm_relationship_manager: AliasManager
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_orm: RelationsManager
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_orm_id: int
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_orm_saved: bool
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_related_names: Optional[Set]
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_related_names_hash: str
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_choices_fields: Optional[Set]
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_pydantic_fields: Set
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_quick_access_fields: Set
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Meta: ModelMeta
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# noinspection PyMissingConstructor
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def __init__(self, *args: Any, **kwargs: Any) -> None: # type: ignore
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"""
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Initializer that creates a new ormar Model that is also pydantic Model at the
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same time.
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Passed keyword arguments can be only field names and their corresponding values
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as those will be passed to pydantic validation that will complain if extra
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params are passed.
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If relations are defined each relation is expanded and children models are also
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initialized and validated. Relation from both sides is registered so you can
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access related models from both sides.
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Json fields are automatically loaded/dumped if needed.
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Models marked as abstract=True in internal Meta class cannot be initialized.
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Accepts also special __pk_only__ flag that indicates that Model is constructed
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only with primary key value (so no other fields, it's a child model on other
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Model), that causes skipping the validation, that's the only case when the
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validation can be skipped.
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Accepts also special __excluded__ parameter that contains a set of fields that
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should be explicitly set to None, as otherwise pydantic will try to populate
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them with their default values if default is set.
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:raises ModelError: if abstract model is initialized, model has ForwardRefs
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that has not been updated or unknown field is passed
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:param args: ignored args
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:type args: Any
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:param kwargs: keyword arguments - all fields values and some special params
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:type kwargs: Any
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"""
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self._verify_model_can_be_initialized()
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object.__setattr__(self, "_orm_id", uuid.uuid4().hex)
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object.__setattr__(self, "_orm_saved", False)
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object.__setattr__(self, "_pk_column", None)
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object.__setattr__(
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self,
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"_orm",
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RelationsManager(
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related_fields=self.extract_related_fields(), owner=cast("Model", self),
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),
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)
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pk_only = kwargs.pop("__pk_only__", False)
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excluded: Set[str] = kwargs.pop("__excluded__", set())
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if "pk" in kwargs:
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kwargs[self.Meta.pkname] = kwargs.pop("pk")
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# build the models to set them and validate but don't register
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# also remove property fields values from validation
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try:
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new_kwargs: Dict[str, Any] = {
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k: self._convert_json(
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k,
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self.Meta.model_fields[k].expand_relationship(
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v, self, to_register=False,
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),
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"dumps",
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)
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for k, v in kwargs.items()
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if k not in object.__getattribute__(self, "Meta").property_fields
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}
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except KeyError as e:
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raise ModelError(
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f"Unknown field '{e.args[0]}' for model {self.get_name(lower=False)}"
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)
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# explicitly set None to excluded fields
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# as pydantic populates them with default if set
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for field_to_nullify in excluded:
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new_kwargs[field_to_nullify] = None
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values, fields_set, validation_error = pydantic.validate_model(
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self, new_kwargs # type: ignore
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)
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if validation_error and not pk_only:
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raise validation_error
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object.__setattr__(self, "__dict__", values)
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object.__setattr__(self, "__fields_set__", fields_set)
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# register the columns models after initialization
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for related in self.extract_related_names().union(self.extract_through_names()):
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self.Meta.model_fields[related].expand_relationship(
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new_kwargs.get(related), self, to_register=True,
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)
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def __setattr__(self, name: str, value: Any) -> None: # noqa CCR001
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"""
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Overwrites setattr in object to allow for special behaviour of certain params.
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Parameter "pk" is translated into actual primary key field name.
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Relations are expanded (child model constructed if needed) and registered on
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both ends of the relation. The related models are handled by RelationshipManager
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exposed at _orm param.
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Json fields converted if needed.
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Setting pk, foreign key value or any other field value sets Model save status
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to False. Setting a reverse relation or many to many relation does not as it
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does not modify the state of the model (but related model or through model).
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To short circuit all checks and expansions the set of attribute names present
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on each model is gathered into _quick_access_fields that is looked first and
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if field is in this set the object setattr is called directly.
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:param name: name of the attribute to set
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:type name: str
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:param value: value of the attribute to set
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:type value: Any
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:return: None
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:rtype: None
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"""
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if name in object.__getattribute__(self, "_quick_access_fields"):
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object.__setattr__(self, name, value)
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elif name == "pk":
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object.__setattr__(self, self.Meta.pkname, value)
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self.set_save_status(False)
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elif name in object.__getattribute__(self, "_orm"):
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model = (
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object.__getattribute__(self, "Meta")
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.model_fields[name]
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.expand_relationship(value=value, child=self)
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)
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if isinstance(object.__getattribute__(self, "__dict__").get(name), list):
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# virtual foreign key or many to many
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# TODO: Fix double items in dict, no effect on real action ugly repr
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# if model.pk not in [x.pk for x in related_list]:
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object.__getattribute__(self, "__dict__")[name].append(model)
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else:
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# foreign key relation
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object.__getattribute__(self, "__dict__")[name] = model
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self.set_save_status(False)
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else:
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if name in object.__getattribute__(self, "_choices_fields"):
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validate_choices(field=self.Meta.model_fields[name], value=value)
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super().__setattr__(name, value)
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self.set_save_status(False)
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def __getattribute__(self, item: str) -> Any: # noqa: CCR001
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"""
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Because we need to overwrite getting the attribute by ormar instead of pydantic
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as well as returning related models and not the value stored on the model the
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__getattribute__ needs to be used not __getattr__.
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It's used to access all attributes so it can be a big overhead that's why a
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number of short circuits is used.
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To short circuit all checks and expansions the set of attribute names present
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on each model is gathered into _quick_access_fields that is looked first and
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if field is in this set the object setattr is called directly.
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To avoid recursion object's getattribute is used to actually get the attribute
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value from the model after the checks.
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Even the function calls are constructed with objects functions.
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Parameter "pk" is translated into actual primary key field name.
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Relations are returned so the actual related model is returned and not current
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model's field. The related models are handled by RelationshipManager exposed
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at _orm param.
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Json fields are converted if needed.
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:param item: name of the attribute to retrieve
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:type item: str
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:return: value of the attribute
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:rtype: Any
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"""
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if item in object.__getattribute__(self, "_quick_access_fields"):
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return object.__getattribute__(self, item)
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if item == "pk":
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return object.__getattribute__(self, "__dict__").get(self.Meta.pkname, None)
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if item in object.__getattribute__(self, "extract_related_names")():
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return self._extract_related_model_instead_of_field(item)
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if item in object.__getattribute__(self, "extract_through_names")():
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return self._extract_related_model_instead_of_field(item)
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if item in object.__getattribute__(self, "Meta").property_fields:
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value = object.__getattribute__(self, item)
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return value() if callable(value) else value
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if item in object.__getattribute__(self, "_pydantic_fields"):
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value = object.__getattribute__(self, "__dict__").get(item, None)
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value = object.__getattribute__(self, "_convert_json")(item, value, "loads")
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return value
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return object.__getattribute__(self, item) # pragma: no cover
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def _verify_model_can_be_initialized(self) -> None:
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"""
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Raises exception if model is abstract or has ForwardRefs in relation fields.
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:return: None
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:rtype: None
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"""
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if self.Meta.abstract:
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raise ModelError(f"You cannot initialize abstract model {self.get_name()}")
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if self.Meta.requires_ref_update:
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raise ModelError(
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f"Model {self.get_name()} has not updated "
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f"ForwardRefs. \nBefore using the model you "
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f"need to call update_forward_refs()."
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)
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def _extract_related_model_instead_of_field(
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self, item: str
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) -> Optional[Union["Model", Sequence["Model"]]]:
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"""
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Retrieves the related model/models from RelationshipManager.
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:param item: name of the relation
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:type item: str
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:return: related model, list of related models or None
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:rtype: Optional[Union[Model, List[Model]]]
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"""
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if item in self._orm:
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return self._orm.get(item) # type: ignore
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return None # pragma no cover
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def __eq__(self, other: object) -> bool:
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"""
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Compares other model to this model. when == is called.
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:param other: other model to compare
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:type other: object
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:return: result of comparison
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:rtype: bool
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"""
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if isinstance(other, NewBaseModel):
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return self.__same__(other)
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return super().__eq__(other) # pragma no cover
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def __same__(self, other: "NewBaseModel") -> bool:
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"""
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Used by __eq__, compares other model to this model.
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Compares:
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* _orm_ids,
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* primary key values if it's set
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* dictionary of own fields (excluding relations)
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:param other: model to compare to
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:type other: NewBaseModel
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:return: result of comparison
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:rtype: bool
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"""
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return (
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self._orm_id == other._orm_id
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or (self.pk == other.pk and self.pk is not None)
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or self.dict(exclude=self.extract_related_names())
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== other.dict(exclude=other.extract_related_names())
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)
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@classmethod
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def get_name(cls, lower: bool = True) -> str:
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"""
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Returns name of the Model class, by default lowercase.
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:param lower: flag if name should be set to lowercase
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:type lower: bool
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:return: name of the model
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:rtype: str
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"""
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name = cls.__name__
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if lower:
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name = name.lower()
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return name
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@property
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def pk_column(self) -> sqlalchemy.Column:
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"""
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Retrieves primary key sqlalchemy column from models Meta.table.
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Each model has to have primary key.
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Only one primary key column is allowed.
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:return: primary key sqlalchemy column
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:rtype: sqlalchemy.Column
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"""
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if object.__getattribute__(self, "_pk_column") is not None:
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return object.__getattribute__(self, "_pk_column")
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pk_columns = self.Meta.table.primary_key.columns.values()
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pk_col = pk_columns[0]
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object.__setattr__(self, "_pk_column", pk_col)
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return pk_col
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@property
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def saved(self) -> bool:
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"""Saved status of the model. Changed by setattr and loading from db"""
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return self._orm_saved
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@property
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def signals(self) -> "SignalEmitter":
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"""Exposes signals from model Meta"""
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return self.Meta.signals
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@classmethod
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def pk_type(cls) -> Any:
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"""Shortcut to models primary key field type"""
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return cls.Meta.model_fields[cls.Meta.pkname].__type__
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@classmethod
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def db_backend_name(cls) -> str:
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"""Shortcut to database dialect,
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cause some dialect require different treatment"""
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return cls.Meta.database._backend._dialect.name
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def remove(self, parent: "Model", name: str) -> None:
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"""Removes child from relation with given name in RelationshipManager"""
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self._orm.remove_parent(self, parent, name)
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def set_save_status(self, status: bool) -> None:
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"""Sets value of the save status"""
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object.__setattr__(self, "_orm_saved", status)
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@classmethod
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def get_properties(
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cls, include: Union[Set, Dict, None], exclude: Union[Set, Dict, None]
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) -> Set[str]:
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"""
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Returns a set of names of functions/fields decorated with
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@property_field decorator.
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They are added to dictionary when called directly and therefore also are
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present in fastapi responses.
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:param include: fields to include
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:type include: Union[Set, Dict, None]
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:param exclude: fields to exclude
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:type exclude: Union[Set, Dict, None]
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:return: set of property fields names
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:rtype: Set[str]
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"""
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props = cls.Meta.property_fields
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if include:
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props = {prop for prop in props if prop in include}
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if exclude:
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props = {prop for prop in props if prop not in exclude}
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return props
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@classmethod
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def update_forward_refs(cls, **localns: Any) -> None:
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"""
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Processes fields that are ForwardRef and need to be evaluated into actual
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models.
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Expands relationships, register relation in alias manager and substitutes
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sqlalchemy columns with new ones with proper column type (null before).
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Populates Meta table of the Model which is left empty before.
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Sets self_reference flag on models that links to themselves.
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Calls the pydantic method to evaluate pydantic fields.
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:param localns: local namespace
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:type localns: Any
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:return: None
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:rtype: None
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"""
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globalns = sys.modules[cls.__module__].__dict__.copy()
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globalns.setdefault(cls.__name__, cls)
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fields_to_check = cls.Meta.model_fields.copy()
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for field in fields_to_check.values():
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if field.has_unresolved_forward_refs():
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field = cast(ForeignKeyField, field)
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field.evaluate_forward_ref(globalns=globalns, localns=localns)
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field.set_self_reference_flag()
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expand_reverse_relationship(model_field=field)
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register_relation_in_alias_manager(field=field)
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update_column_definition(model=cls, field=field)
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populate_meta_sqlalchemy_table_if_required(meta=cls.Meta)
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super().update_forward_refs(**localns)
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cls.Meta.requires_ref_update = False
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def _get_related_not_excluded_fields(
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self, include: Optional[Dict], exclude: Optional[Dict],
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) -> List:
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"""
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Returns related field names applying on them include and exclude set.
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:param include: fields to include
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:type include: Union[Set, Dict, None]
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:param exclude: fields to exclude
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:type exclude: Union[Set, Dict, None]
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:return:
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:rtype: List of fields with relations that is not excluded
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"""
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fields = [field for field in self.extract_related_names()]
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if include:
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fields = [field for field in fields if field in include]
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if exclude:
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fields = [
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field
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for field in fields
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if field not in exclude or exclude.get(field) is not Ellipsis
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]
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return fields
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@staticmethod
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def _extract_nested_models_from_list(
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models: MutableSequence,
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include: Union[Set, Dict, None],
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exclude: Union[Set, Dict, None],
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) -> List:
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"""
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Converts list of models into list of dictionaries.
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:param models: List of models
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:type models: List
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:param include: fields to include
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:type include: Union[Set, Dict, None]
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:param exclude: fields to exclude
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:type exclude: Union[Set, Dict, None]
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:return: list of models converted to dictionaries
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:rtype: List[Dict]
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"""
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result = []
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for model in models:
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try:
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result.append(
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model.dict(nested=True, include=include, exclude=exclude,)
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)
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except ReferenceError: # pragma no cover
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continue
|
|
return result
|
|
|
|
def _skip_ellipsis(
|
|
self, items: Union[Set, Dict, None], key: str
|
|
) -> Union[Set, Dict, None]:
|
|
"""
|
|
Helper to traverse the include/exclude dictionaries.
|
|
In dict() Ellipsis should be skipped as it indicates all fields required
|
|
and not the actual set/dict with fields names.
|
|
|
|
:param items: current include/exclude value
|
|
:type items: Union[Set, Dict, None]
|
|
:param key: key for nested relations to check
|
|
:type key: str
|
|
:return: nested value of the items
|
|
:rtype: Union[Set, Dict, None]
|
|
"""
|
|
result = self.get_child(items, key)
|
|
return result if result is not Ellipsis else None
|
|
|
|
def _extract_nested_models( # noqa: CCR001
|
|
self,
|
|
nested: bool,
|
|
dict_instance: Dict,
|
|
include: Optional[Dict],
|
|
exclude: Optional[Dict],
|
|
) -> Dict:
|
|
"""
|
|
Traverse nested models and converts them into dictionaries.
|
|
Calls itself recursively if needed.
|
|
|
|
:param nested: flag if current instance is nested
|
|
:type nested: bool
|
|
:param dict_instance: current instance dict
|
|
:type dict_instance: Dict
|
|
:param include: fields to include
|
|
:type include: Optional[Dict]
|
|
:param exclude: fields to exclude
|
|
:type exclude: Optional[Dict]
|
|
:return: current model dict with child models converted to dictionaries
|
|
:rtype: Dict
|
|
"""
|
|
|
|
fields = self._get_related_not_excluded_fields(include=include, exclude=exclude)
|
|
|
|
for field in fields:
|
|
if self.Meta.model_fields[field].virtual and nested:
|
|
continue
|
|
nested_model = getattr(self, field)
|
|
if isinstance(nested_model, MutableSequence):
|
|
dict_instance[field] = self._extract_nested_models_from_list(
|
|
models=nested_model,
|
|
include=self._skip_ellipsis(include, field),
|
|
exclude=self._skip_ellipsis(exclude, field),
|
|
)
|
|
elif nested_model is not None:
|
|
dict_instance[field] = nested_model.dict(
|
|
nested=True,
|
|
include=self._skip_ellipsis(include, field),
|
|
exclude=self._skip_ellipsis(exclude, field),
|
|
)
|
|
else:
|
|
dict_instance[field] = None
|
|
return dict_instance
|
|
|
|
def dict( # type: ignore # noqa A003
|
|
self,
|
|
*,
|
|
include: Union[Set, Dict] = None,
|
|
exclude: Union[Set, Dict] = None,
|
|
by_alias: bool = False,
|
|
skip_defaults: bool = None,
|
|
exclude_unset: bool = False,
|
|
exclude_defaults: bool = False,
|
|
exclude_none: bool = False,
|
|
nested: bool = False,
|
|
) -> "DictStrAny": # noqa: A003'
|
|
"""
|
|
|
|
Generate a dictionary representation of the model,
|
|
optionally specifying which fields to include or exclude.
|
|
|
|
Nested models are also parsed to dictionaries.
|
|
|
|
Additionally fields decorated with @property_field are also added.
|
|
|
|
:param include: fields to include
|
|
:type include: Union[Set, Dict, None]
|
|
:param exclude: fields to exclude
|
|
:type exclude: Union[Set, Dict, None]
|
|
:param by_alias: flag to get values by alias - passed to pydantic
|
|
:type by_alias: bool
|
|
:param skip_defaults: flag to not set values - passed to pydantic
|
|
:type skip_defaults: bool
|
|
:param exclude_unset: flag to exclude not set values - passed to pydantic
|
|
:type exclude_unset: bool
|
|
:param exclude_defaults: flag to exclude default values - passed to pydantic
|
|
:type exclude_defaults: bool
|
|
:param exclude_none: flag to exclude None values - passed to pydantic
|
|
:type exclude_none: bool
|
|
:param nested: flag if the current model is nested
|
|
:type nested: bool
|
|
:return:
|
|
:rtype:
|
|
"""
|
|
dict_instance = super().dict(
|
|
include=include,
|
|
exclude=self._update_excluded_with_related_not_required(exclude, nested),
|
|
by_alias=by_alias,
|
|
skip_defaults=skip_defaults,
|
|
exclude_unset=exclude_unset,
|
|
exclude_defaults=exclude_defaults,
|
|
exclude_none=exclude_none,
|
|
)
|
|
|
|
if include and isinstance(include, Set):
|
|
include = translate_list_to_dict(include)
|
|
if exclude and isinstance(exclude, Set):
|
|
exclude = translate_list_to_dict(exclude)
|
|
|
|
dict_instance = self._extract_nested_models(
|
|
nested=nested,
|
|
dict_instance=dict_instance,
|
|
include=include, # type: ignore
|
|
exclude=exclude, # type: ignore
|
|
)
|
|
|
|
# include model properties as fields in dict
|
|
if object.__getattribute__(self, "Meta").property_fields:
|
|
props = self.get_properties(include=include, exclude=exclude)
|
|
if props:
|
|
dict_instance.update({prop: getattr(self, prop) for prop in props})
|
|
|
|
return dict_instance
|
|
|
|
def update_from_dict(self, value_dict: Dict) -> "NewBaseModel":
|
|
"""
|
|
Updates self with values of fields passed in the dictionary.
|
|
|
|
:param value_dict: dictionary of fields names and values
|
|
:type value_dict: Dict
|
|
:return: self
|
|
:rtype: NewBaseModel
|
|
"""
|
|
for key, value in value_dict.items():
|
|
setattr(self, key, value)
|
|
return self
|
|
|
|
def _convert_json(self, column_name: str, value: Any, op: str) -> Union[str, Dict]:
|
|
"""
|
|
Converts value to/from json if needed (for Json columns).
|
|
|
|
:param column_name: name of the field
|
|
:type column_name: str
|
|
:param value: value fo the field
|
|
:type value: Any
|
|
:param op: operator on json
|
|
:type op: str
|
|
:return: converted value if needed, else original value
|
|
:rtype: Any
|
|
"""
|
|
if not self._is_conversion_to_json_needed(column_name):
|
|
return value
|
|
|
|
condition = (
|
|
isinstance(value, str) if op == "loads" else not isinstance(value, str)
|
|
)
|
|
operand: Callable[[Any], Any] = (
|
|
json.loads if op == "loads" else json.dumps # type: ignore
|
|
)
|
|
|
|
if condition:
|
|
try:
|
|
value = operand(value)
|
|
except TypeError: # pragma no cover
|
|
pass
|
|
return value.decode("utf-8") if isinstance(value, bytes) else value
|
|
|
|
def _is_conversion_to_json_needed(self, column_name: str) -> bool:
|
|
"""
|
|
Checks if given column name is related to JSON field.
|
|
|
|
:param column_name: name of the field
|
|
:type column_name: str
|
|
:return: result of the check
|
|
:rtype: bool
|
|
"""
|
|
return (
|
|
column_name in self.Meta.model_fields
|
|
and self.Meta.model_fields[column_name].__type__ == pydantic.Json
|
|
)
|
|
|
|
def _extract_own_model_fields(self) -> Dict:
|
|
"""
|
|
Returns a dictionary with field names and values for fields that are not
|
|
relations fields (ForeignKey, ManyToMany etc.)
|
|
|
|
:return: dictionary of fields names and values.
|
|
:rtype: Dict
|
|
"""
|
|
related_names = self.extract_related_names()
|
|
self_fields = self.dict(exclude=related_names)
|
|
return self_fields
|
|
|
|
def _extract_model_db_fields(self) -> Dict:
|
|
"""
|
|
Returns a dictionary with field names and values for fields that are stored in
|
|
current model's table.
|
|
|
|
That includes own non-relational fields ang foreign key fields.
|
|
|
|
:return: dictionary of fields names and values.
|
|
:rtype: Dict
|
|
"""
|
|
self_fields = self._extract_own_model_fields()
|
|
self_fields = {
|
|
k: v
|
|
for k, v in self_fields.items()
|
|
if self.get_column_alias(k) in self.Meta.table.columns
|
|
}
|
|
for field in self._extract_db_related_names():
|
|
relation_field = self.Meta.model_fields[field]
|
|
target_pk_name = relation_field.to.Meta.pkname
|
|
target_field = getattr(self, field)
|
|
self_fields[field] = getattr(target_field, target_pk_name, None)
|
|
if not relation_field.nullable and not self_fields[field]:
|
|
raise ModelPersistenceError(
|
|
f"You cannot save {relation_field.to.get_name()} "
|
|
f"model without pk set!"
|
|
)
|
|
return self_fields
|
|
|
|
def get_relation_model_id(self, target_field: "BaseField") -> Optional[int]:
|
|
"""
|
|
Returns an id of the relation side model to use in prefetch query.
|
|
|
|
:param target_field: field with relation definition
|
|
:type target_field: "BaseField"
|
|
:return: value of pk if set
|
|
:rtype: Optional[int]
|
|
"""
|
|
if target_field.virtual or target_field.is_multi:
|
|
return self.pk
|
|
related_name = target_field.name
|
|
related_model = getattr(self, related_name)
|
|
return None if not related_model else related_model.pk
|