metaclass

ModelMeta

Class used for type hinting. Users can subclass this one for convenience but it's not required. The only requirement is that ormar.Model has to have inner class with name Meta.

Source code in ormar\models\metaclass.py

class ModelMeta:
    """
    Class used for type hinting.
    Users can subclass this one for convenience but it's not required.
    The only requirement is that ormar.Model has to have inner class with name Meta.
    """

    tablename: str
    table: sqlalchemy.Table
    metadata: sqlalchemy.MetaData
    database: databases.Database
    columns: List[sqlalchemy.Column]
    constraints: List[ColumnCollectionConstraint]
    pkname: str
    model_fields: Dict[str, Union[BaseField, ForeignKeyField, ManyToManyField]]
    alias_manager: AliasManager
    property_fields: Set
    signals: SignalEmitter
    abstract: bool
    requires_ref_update: bool
    orders_by: List[str]
    exclude_parent_fields: List[str]
    extra: Extra
    queryset_class: Type[QuerySet]

ModelMetaclass

Bases: pydantic.main.ModelMetaclass

Source code in ormar\models\metaclass.py

class ModelMetaclass(pydantic.main.ModelMetaclass):
    def __new__(  # type: ignore # noqa: CCR001
        mcs: "ModelMetaclass", name: str, bases: Any, attrs: dict
    ) -> "ModelMetaclass":
        """
        Metaclass used by ormar Models that performs configuration
        and build of ormar Models.


        Sets pydantic configuration.
        Extract model_fields and convert them to pydantic FieldInfo,
        updates class namespace.

        Extracts settings and fields from parent classes.
        Fetches methods decorated with @property_field decorator
        to expose them later in dict().

        Construct parent pydantic Metaclass/ Model.

        If class has Meta class declared (so actual ormar Models) it also:

        * populate sqlalchemy columns, pkname and tables from model_fields
        * register reverse relationships on related models
        * registers all relations in alias manager that populates table_prefixes
        * exposes alias manager on each Model
        * creates QuerySet for each model and exposes it on a class

        :param name: name of current class
        :type name: str
        :param bases: base classes
        :type bases: Tuple
        :param attrs: class namespace
        :type attrs: Dict
        """
        merge_or_generate_pydantic_config(attrs=attrs, name=name)
        attrs["__name__"] = name
        attrs, model_fields = extract_annotations_and_default_vals(attrs)
        for base in reversed(bases):
            mod = base.__module__
            if mod.startswith("ormar.models.") or mod.startswith("pydantic."):
                continue
            attrs, model_fields = extract_from_parents_definition(
                base_class=base, curr_class=mcs, attrs=attrs, model_fields=model_fields
            )
        new_model = super().__new__(mcs, name, bases, attrs)  # type: ignore

        add_cached_properties(new_model)

        if hasattr(new_model, "Meta"):
            populate_default_options_values(new_model, model_fields)
            check_required_meta_parameters(new_model)
            add_property_fields(new_model, attrs)
            register_signals(new_model=new_model)
            populate_choices_validators(new_model)

            if not new_model.Meta.abstract:
                new_model = populate_meta_tablename_columns_and_pk(name, new_model)
                populate_meta_sqlalchemy_table_if_required(new_model.Meta)
                expand_reverse_relationships(new_model)
                # TODO: iterate only related fields
                for field_name, field in new_model.Meta.model_fields.items():
                    register_relation_in_alias_manager(field=field)
                    add_field_descriptor(
                        name=field_name, field=field, new_model=new_model
                    )

                if (
                    new_model.Meta.pkname
                    and new_model.Meta.pkname not in attrs["__annotations__"]
                    and new_model.Meta.pkname not in new_model.__fields__
                ):
                    field_name = new_model.Meta.pkname
                    attrs["__annotations__"][field_name] = Optional[int]  # type: ignore
                    attrs[field_name] = None
                    new_model.__fields__[field_name] = get_pydantic_field(
                        field_name=field_name, model=new_model
                    )
                new_model.Meta.alias_manager = alias_manager

                for item in new_model.Meta.property_fields:
                    function = getattr(new_model, item)
                    setattr(
                        new_model,
                        item,
                        PropertyDescriptor(name=item, function=function),
                    )

                new_model.pk = PkDescriptor(name=new_model.Meta.pkname)
                remove_excluded_parent_fields(new_model)

        return new_model

    @property
    def objects(cls: Type["T"]) -> "QuerySet[T]":  # type: ignore
        if cls.Meta.requires_ref_update:
            raise ModelError(
                f"Model {cls.get_name()} has not updated "
                f"ForwardRefs. \nBefore using the model you "
                f"need to call update_forward_refs()."
            )
        return cls.Meta.queryset_class(model_cls=cls)

    def __getattr__(self, item: str) -> Any:
        """
        Returns FieldAccessors on access to model fields from a class,
        that way it can be used in python style filters and order_by.

        :param item: name of the field
        :type item: str
        :return: FieldAccessor for given field
        :rtype: FieldAccessor
        """
        if item == "pk":
            item = self.Meta.pkname
        if item in object.__getattribute__(self, "Meta").model_fields:
            field = self.Meta.model_fields.get(item)
            if field.is_relation:
                return FieldAccessor(
                    source_model=cast(Type["Model"], self),
                    model=field.to,
                    access_chain=item,
                )
            return FieldAccessor(
                source_model=cast(Type["Model"], self), field=field, access_chain=item
            )
        return object.__getattribute__(self, item)

__getattr__(item)

Returns FieldAccessors on access to model fields from a class, that way it can be used in python style filters and order_by.

Parameters:

Name	Type	Description	Default
item	str	name of the field	required

Returns:

Type	Description
FieldAccessor	FieldAccessor for given field

Source code in ormar\models\metaclass.py

def __getattr__(self, item: str) -> Any:
    """
    Returns FieldAccessors on access to model fields from a class,
    that way it can be used in python style filters and order_by.

    :param item: name of the field
    :type item: str
    :return: FieldAccessor for given field
    :rtype: FieldAccessor
    """
    if item == "pk":
        item = self.Meta.pkname
    if item in object.__getattribute__(self, "Meta").model_fields:
        field = self.Meta.model_fields.get(item)
        if field.is_relation:
            return FieldAccessor(
                source_model=cast(Type["Model"], self),
                model=field.to,
                access_chain=item,
            )
        return FieldAccessor(
            source_model=cast(Type["Model"], self), field=field, access_chain=item
        )
    return object.__getattribute__(self, item)

__new__(mcs, name, bases, attrs)

Metaclass used by ormar Models that performs configuration and build of ormar Models.

Sets pydantic configuration. Extract model_fields and convert them to pydantic FieldInfo, updates class namespace.

Extracts settings and fields from parent classes. Fetches methods decorated with @property_field decorator to expose them later in dict().

Construct parent pydantic Metaclass/ Model.

If class has Meta class declared (so actual ormar Models) it also:

• populate sqlalchemy columns, pkname and tables from model_fields
• register reverse relationships on related models
• registers all relations in alias manager that populates table_prefixes
• exposes alias manager on each Model
• creates QuerySet for each model and exposes it on a class

Parameters:

Name	Type	Description	Default
name	str	name of current class	required
bases	Any	base classes	required
attrs	dict	class namespace	required

Source code in ormar\models\metaclass.py

def __new__(  # type: ignore # noqa: CCR001
    mcs: "ModelMetaclass", name: str, bases: Any, attrs: dict
) -> "ModelMetaclass":
    """
    Metaclass used by ormar Models that performs configuration
    and build of ormar Models.


    Sets pydantic configuration.
    Extract model_fields and convert them to pydantic FieldInfo,
    updates class namespace.

    Extracts settings and fields from parent classes.
    Fetches methods decorated with @property_field decorator
    to expose them later in dict().

    Construct parent pydantic Metaclass/ Model.

    If class has Meta class declared (so actual ormar Models) it also:

    * populate sqlalchemy columns, pkname and tables from model_fields
    * register reverse relationships on related models
    * registers all relations in alias manager that populates table_prefixes
    * exposes alias manager on each Model
    * creates QuerySet for each model and exposes it on a class

    :param name: name of current class
    :type name: str
    :param bases: base classes
    :type bases: Tuple
    :param attrs: class namespace
    :type attrs: Dict
    """
    merge_or_generate_pydantic_config(attrs=attrs, name=name)
    attrs["__name__"] = name
    attrs, model_fields = extract_annotations_and_default_vals(attrs)
    for base in reversed(bases):
        mod = base.__module__
        if mod.startswith("ormar.models.") or mod.startswith("pydantic."):
            continue
        attrs, model_fields = extract_from_parents_definition(
            base_class=base, curr_class=mcs, attrs=attrs, model_fields=model_fields
        )
    new_model = super().__new__(mcs, name, bases, attrs)  # type: ignore

    add_cached_properties(new_model)

    if hasattr(new_model, "Meta"):
        populate_default_options_values(new_model, model_fields)
        check_required_meta_parameters(new_model)
        add_property_fields(new_model, attrs)
        register_signals(new_model=new_model)
        populate_choices_validators(new_model)

        if not new_model.Meta.abstract:
            new_model = populate_meta_tablename_columns_and_pk(name, new_model)
            populate_meta_sqlalchemy_table_if_required(new_model.Meta)
            expand_reverse_relationships(new_model)
            # TODO: iterate only related fields
            for field_name, field in new_model.Meta.model_fields.items():
                register_relation_in_alias_manager(field=field)
                add_field_descriptor(
                    name=field_name, field=field, new_model=new_model
                )

            if (
                new_model.Meta.pkname
                and new_model.Meta.pkname not in attrs["__annotations__"]
                and new_model.Meta.pkname not in new_model.__fields__
            ):
                field_name = new_model.Meta.pkname
                attrs["__annotations__"][field_name] = Optional[int]  # type: ignore
                attrs[field_name] = None
                new_model.__fields__[field_name] = get_pydantic_field(
                    field_name=field_name, model=new_model
                )
            new_model.Meta.alias_manager = alias_manager

            for item in new_model.Meta.property_fields:
                function = getattr(new_model, item)
                setattr(
                    new_model,
                    item,
                    PropertyDescriptor(name=item, function=function),
                )

            new_model.pk = PkDescriptor(name=new_model.Meta.pkname)
            remove_excluded_parent_fields(new_model)

    return new_model

add_cached_properties(new_model)

Sets cached properties for both pydantic and ormar models.

Quick access fields are fields grabbed in getattribute to skip all checks.

Related fields and names are populated to None as they can change later. When children models are constructed they can modify parent to register itself.

All properties here are used as "cache" to not recalculate them constantly.

Parameters:

Name	Type	Description	Default
new_model	Type[Model]	newly constructed Model	required

Source code in ormar\models\metaclass.py

def add_cached_properties(new_model: Type["Model"]) -> None:
    """
    Sets cached properties for both pydantic and ormar models.

    Quick access fields are fields grabbed in getattribute to skip all checks.

    Related fields and names are populated to None as they can change later.
    When children models are constructed they can modify parent to register itself.

    All properties here are used as "cache" to not recalculate them constantly.

    :param new_model: newly constructed Model
    :type new_model: Model class
    """
    new_model._quick_access_fields = quick_access_set
    new_model._related_names = None
    new_model._through_names = None
    new_model._related_fields = None
    new_model._pydantic_fields = {name for name in new_model.__fields__}
    new_model._json_fields = set()
    new_model._bytes_fields = set()

add_field_descriptor(name, field, new_model)

Sets appropriate descriptor for each model field. There are 5 main types of descriptors, for bytes, json, pure pydantic fields, and 2 ormar ones - one for relation and one for pk shortcut

Parameters:

Name	Type	Description	Default
name	str	name of the field	required
field	BaseField	model field to add descriptor for	required
new_model	Type[Model]	model with fields	required

Source code in ormar\models\metaclass.py

def add_field_descriptor(
    name: str, field: "BaseField", new_model: Type["Model"]
) -> None:
    """
    Sets appropriate descriptor for each model field.
    There are 5 main types of descriptors, for bytes, json, pure pydantic fields,
    and 2 ormar ones - one for relation and one for pk shortcut

    :param name: name of the field
    :type name: str
    :param field: model field to add descriptor for
    :type field: BaseField
    :param new_model: model with fields
    :type new_model: Type["Model]
    """
    if field.is_relation:
        setattr(new_model, name, RelationDescriptor(name=name))
    elif field.__type__ == pydantic.Json:
        setattr(new_model, name, JsonDescriptor(name=name))
    elif field.__type__ == bytes:
        setattr(new_model, name, BytesDescriptor(name=name))
    else:
        setattr(new_model, name, PydanticDescriptor(name=name))

add_property_fields(new_model, attrs)

Checks class namespace for properties or functions with property_field. If attribute have property_field it was decorated with @property_field.

Functions like this are exposed in dict() (therefore also fastapi result). Names of property fields are cached for quicker access / extraction.

Parameters:

Name	Type	Description	Default
new_model	Type[Model]	newly constructed model	required
attrs	Dict		required

Source code in ormar\models\metaclass.py

def add_property_fields(new_model: Type["Model"], attrs: Dict) -> None:  # noqa: CCR001
    """
    Checks class namespace for properties or functions with __property_field__.
    If attribute have __property_field__ it was decorated with @property_field.

    Functions like this are exposed in dict() (therefore also fastapi result).
    Names of property fields are cached for quicker access / extraction.

    :param new_model: newly constructed model
    :type new_model: Model class
    :param attrs:
    :type attrs: Dict[str, str]
    """
    props = set()
    for var_name, value in attrs.items():
        if isinstance(value, property):
            value = value.fget
        field_config = getattr(value, "__property_field__", None)
        if field_config:
            props.add(var_name)

    if meta_field_not_set(model=new_model, field_name="property_fields"):
        new_model.Meta.property_fields = props
    else:
        new_model.Meta.property_fields = new_model.Meta.property_fields.union(props)

copy_and_replace_m2m_through_model(field, field_name, table_name, parent_fields, attrs, meta, base_class)

Clones class with Through model for m2m relations, appends child name to the name of the cloned class.

Clones non foreign keys fields from parent model, the same with database columns.

Modifies related_name with appending child table name after '_'

For table name, the table name of child is appended after '_'.

Removes the original sqlalchemy table from metadata if it was not removed.

Parameters:

Name	Type	Description	Default
base_class	Type[Model]	base class model	required
field	ManyToManyField	field with relations definition	required
field_name	str	name of the relation field	required
table_name	str	name of the table	required
parent_fields	Dict	dictionary of fields to copy to new models from parent	required
attrs	Dict	new namespace for class being constructed	required
meta	ModelMeta	metaclass of currently created model	required

Source code in ormar\models\metaclass.py

def copy_and_replace_m2m_through_model(  # noqa: CFQ002
    field: ManyToManyField,
    field_name: str,
    table_name: str,
    parent_fields: Dict,
    attrs: Dict,
    meta: ModelMeta,
    base_class: Type["Model"],
) -> None:
    """
    Clones class with Through model for m2m relations, appends child name to the name
    of the cloned class.

    Clones non foreign keys fields from parent model, the same with database columns.

    Modifies related_name with appending child table name after '_'

    For table name, the table name of child is appended after '_'.

    Removes the original sqlalchemy table from metadata if it was not removed.

    :param base_class: base class model
    :type base_class: Type["Model"]
    :param field: field with relations definition
    :type field: ManyToManyField
    :param field_name: name of the relation field
    :type field_name: str
    :param table_name: name of the table
    :type table_name: str
    :param parent_fields: dictionary of fields to copy to new models from parent
    :type parent_fields: Dict
    :param attrs: new namespace for class being constructed
    :type attrs: Dict
    :param meta: metaclass of currently created model
    :type meta: ModelMeta
    """
    Field: Type[BaseField] = type(  # type: ignore
        field.__class__.__name__, (ManyToManyField, BaseField), {}
    )
    copy_field = Field(**dict(field.__dict__))
    related_name = field.related_name + "_" + table_name
    copy_field.related_name = related_name  # type: ignore

    through_class = field.through
    if not through_class:
        field.owner = base_class
        field.create_default_through_model()
        through_class = field.through
    new_meta: ormar.ModelMeta = type(  # type: ignore
        "Meta", (), dict(through_class.Meta.__dict__)
    )
    copy_name = through_class.__name__ + attrs.get("__name__", "")
    copy_through = type(copy_name, (ormar.Model,), {"Meta": new_meta})
    new_meta.tablename += "_" + meta.tablename
    # create new table with copied columns but remove foreign keys
    # they will be populated later in expanding reverse relation
    if hasattr(new_meta, "table"):
        del new_meta.table
    new_meta.model_fields = {
        name: field
        for name, field in new_meta.model_fields.items()
        if not field.is_relation
    }
    _, columns = sqlalchemy_columns_from_model_fields(
        new_meta.model_fields, copy_through
    )  # type: ignore
    new_meta.columns = columns
    populate_meta_sqlalchemy_table_if_required(new_meta)
    copy_field.through = copy_through

    parent_fields[field_name] = copy_field

    if through_class.Meta.table in through_class.Meta.metadata:
        through_class.Meta.metadata.remove(through_class.Meta.table)

copy_data_from_parent_model(base_class, curr_class, attrs, model_fields)

Copy the key parameters [database, metadata, property_fields and constraints] and fields from parent models. Overwrites them if needed.

Only abstract classes can be subclassed.

Since relation fields requires different related_name for different children

Parameters:

Name	Type	Description	Default
base_class	Type[Model]	one of the parent classes	required
curr_class	type	current constructed class	required
attrs	Dict	new namespace for class being constructed	required
model_fields	Dict[str, Union[BaseField, ForeignKeyField, ManyToManyField]]	ormar fields in defined in current class	required

Returns:

Type	Description
Tuple[Dict, Dict]	updated attrs and model_fields

Raises:

Type	Description
ModelDefinitionError	if non abstract model is subclassed

Source code in ormar\models\metaclass.py

def copy_data_from_parent_model(  # noqa: CCR001
    base_class: Type["Model"],
    curr_class: type,
    attrs: Dict,
    model_fields: Dict[str, Union[BaseField, ForeignKeyField, ManyToManyField]],
) -> Tuple[Dict, Dict]:
    """
    Copy the key parameters [database, metadata, property_fields and constraints]
    and fields from parent models. Overwrites them if needed.

    Only abstract classes can be subclassed.

    Since relation fields requires different related_name for different children


    :raises ModelDefinitionError: if non abstract model is subclassed
    :param base_class: one of the parent classes
    :type base_class: Model or model parent class
    :param curr_class: current constructed class
    :type curr_class: Model or model parent class
    :param attrs: new namespace for class being constructed
    :type attrs: Dict
    :param model_fields: ormar fields in defined in current class
    :type model_fields: Dict[str, BaseField]
    :return: updated attrs and model_fields
    :rtype: Tuple[Dict, Dict]
    """
    if attrs.get("Meta"):
        if model_fields and not base_class.Meta.abstract:  # type: ignore
            raise ModelDefinitionError(
                f"{curr_class.__name__} cannot inherit "
                f"from non abstract class {base_class.__name__}"
            )
        update_attrs_from_base_meta(
            base_class=base_class,  # type: ignore
            attrs=attrs,
            model_fields=model_fields,
        )
        parent_fields: Dict = dict()
        meta = attrs.get("Meta")
        if not meta:  # pragma: no cover
            raise ModelDefinitionError(
                f"Model {curr_class.__name__} declared without Meta"
            )
        table_name = (
            meta.tablename
            if hasattr(meta, "tablename") and meta.tablename
            else attrs.get("__name__", "").lower() + "s"
        )
        for field_name, field in base_class.Meta.model_fields.items():
            if (
                hasattr(meta, "exclude_parent_fields")
                and field_name in meta.exclude_parent_fields
            ):
                continue
            if field.is_multi:
                field = cast(ManyToManyField, field)
                copy_and_replace_m2m_through_model(
                    field=field,
                    field_name=field_name,
                    table_name=table_name,
                    parent_fields=parent_fields,
                    attrs=attrs,
                    meta=meta,
                    base_class=base_class,  # type: ignore
                )

            elif field.is_relation and field.related_name:
                Field = type(  # type: ignore
                    field.__class__.__name__, (ForeignKeyField, BaseField), {}
                )
                copy_field = Field(**dict(field.__dict__))
                related_name = field.related_name + "_" + table_name
                copy_field.related_name = related_name  # type: ignore
                parent_fields[field_name] = copy_field
            else:
                parent_fields[field_name] = field

        parent_fields.update(model_fields)  # type: ignore
        model_fields = parent_fields
    return attrs, model_fields

extract_from_parents_definition(base_class, curr_class, attrs, model_fields)

Extracts fields from base classes if they have valid ormar fields.

If model was already parsed -> fields definitions need to be removed from class cause pydantic complains about field re-definition so after first child we need to extract from parsed_fields not the class itself.

If the class is parsed first time annotations and field definition is parsed from the class.dict.

If the class is a ormar.Model it is skipped.

Parameters:

Name	Type	Description	Default
base_class	type	one of the parent classes	required
curr_class	type	current constructed class	required
attrs	Dict	new namespace for class being constructed	required
model_fields	Dict[str, Union[BaseField, ForeignKeyField, ManyToManyField]]	ormar fields in defined in current class	required

Returns:

Type	Description
Tuple[Dict, Dict]	updated attrs and model_fields

Source code in ormar\models\metaclass.py

def extract_from_parents_definition(  # noqa: CCR001
    base_class: type,
    curr_class: type,
    attrs: Dict,
    model_fields: Dict[str, Union[BaseField, ForeignKeyField, ManyToManyField]],
) -> Tuple[Dict, Dict]:
    """
    Extracts fields from base classes if they have valid ormar fields.

    If model was already parsed -> fields definitions need to be removed from class
    cause pydantic complains about field re-definition so after first child
    we need to extract from __parsed_fields__ not the class itself.

    If the class is parsed first time annotations and field definition is parsed
    from the class.__dict__.

    If the class is a ormar.Model it is skipped.

    :param base_class: one of the parent classes
    :type base_class: Model or model parent class
    :param curr_class: current constructed class
    :type curr_class: Model or model parent class
    :param attrs: new namespace for class being constructed
    :type attrs: Dict
    :param model_fields: ormar fields in defined in current class
    :type model_fields: Dict[str, BaseField]
    :return: updated attrs and model_fields
    :rtype: Tuple[Dict, Dict]
    """
    if hasattr(base_class, "Meta"):
        base_class = cast(Type["Model"], base_class)
        return copy_data_from_parent_model(
            base_class=base_class,
            curr_class=curr_class,
            attrs=attrs,
            model_fields=model_fields,
        )

    key = "__annotations__"
    if hasattr(base_class, PARSED_FIELDS_KEY):
        # model was already parsed -> fields definitions need to be removed from class
        # cause pydantic complains about field re-definition so after first child
        # we need to extract from __parsed_fields__ not the class itself
        new_attrs, new_model_fields = getattr(base_class, PARSED_FIELDS_KEY)

        new_fields = set(new_model_fields.keys())
        model_fields = update_attrs_and_fields(
            attrs=attrs,
            new_attrs=new_attrs,
            model_fields=model_fields,
            new_model_fields=new_model_fields,
            new_fields=new_fields,
        )
        return attrs, model_fields

    potential_fields = get_potential_fields(base_class.__dict__)
    if potential_fields:
        # parent model has ormar fields defined and was not parsed before
        new_attrs = {key: {k: v for k, v in base_class.__dict__.get(key, {}).items()}}
        new_attrs.update(potential_fields)

        new_fields = set(potential_fields.keys())
        for name in new_fields:
            delattr(base_class, name)

        new_attrs, new_model_fields = extract_annotations_and_default_vals(new_attrs)
        setattr(base_class, PARSED_FIELDS_KEY, (new_attrs, new_model_fields))
        model_fields = update_attrs_and_fields(
            attrs=attrs,
            new_attrs=new_attrs,
            model_fields=model_fields,
            new_model_fields=new_model_fields,
            new_fields=new_fields,
        )
    return attrs, model_fields

get_constraint_copy(constraint)

Copy the constraint and unpacking it's values

Parameters:

Name	Type	Description	Default
value	Instance of ColumnCollectionConstraint child	an instance of the ColumnCollectionConstraint class	required

Returns:

Type	Description
Union[UniqueColumns, IndexColumns, CheckColumns]	copy ColumnCollectionConstraint ormar constraints

Raises:

Type	Description
ValueError	if non subclass of ColumnCollectionConstraint

Source code in ormar\models\metaclass.py

def get_constraint_copy(
    constraint: ColumnCollectionConstraint,
) -> Union[UniqueColumns, IndexColumns, CheckColumns]:
    """
    Copy the constraint and unpacking it's values

    :raises ValueError: if non subclass of ColumnCollectionConstraint
    :param value: an instance of the ColumnCollectionConstraint class
    :type value: Instance of ColumnCollectionConstraint child
    :return: copy ColumnCollectionConstraint ormar constraints
    :rtype: Union[UniqueColumns, IndexColumns, CheckColumns]
    """

    constraints = {
        sqlalchemy.UniqueConstraint: lambda x: UniqueColumns(*x._pending_colargs),
        sqlalchemy.Index: lambda x: IndexColumns(*x._pending_colargs),
        sqlalchemy.CheckConstraint: lambda x: CheckColumns(x.sqltext),
    }
    checks = (key if isinstance(constraint, key) else None for key in constraints)
    target_class = next((target for target in checks if target is not None), None)
    constructor: Optional[Callable] = constraints.get(target_class)
    if not constructor:
        raise ValueError(f"{constraint} must be a ColumnCollectionMixin!")

    return constructor(constraint)

register_signals(new_model)

Registers on model's SignalEmmiter and sets pre defined signals. Predefined signals are (pre/post) + (save/update/delete).

Signals are emitted in both model own methods and in selected queryset ones.

Parameters:

Name	Type	Description	Default
new_model	Type[Model]	newly constructed model	required

Source code in ormar\models\metaclass.py

def register_signals(new_model: Type["Model"]) -> None:  # noqa: CCR001
    """
    Registers on model's SignalEmmiter and sets pre defined signals.
    Predefined signals are (pre/post) + (save/update/delete).

    Signals are emitted in both model own methods and in selected queryset ones.

    :param new_model: newly constructed model
    :type new_model: Model class
    """
    if meta_field_not_set(model=new_model, field_name="signals"):
        signals = SignalEmitter()
        signals.pre_save = Signal()
        signals.pre_update = Signal()
        signals.pre_delete = Signal()
        signals.post_save = Signal()
        signals.post_update = Signal()
        signals.post_delete = Signal()
        signals.pre_relation_add = Signal()
        signals.post_relation_add = Signal()
        signals.pre_relation_remove = Signal()
        signals.post_relation_remove = Signal()
        signals.post_bulk_update = Signal()
        new_model.Meta.signals = signals

update_attrs_and_fields(attrs, new_attrs, model_fields, new_model_fields, new_fields)

Updates annotations, values of model fields (so pydantic FieldInfos) as well as model.Meta.model_fields definitions from parents.

Parameters:

Name	Type	Description	Default
attrs	Dict	new namespace for class being constructed	required
new_attrs	Dict	related of the namespace extracted from parent class	required
model_fields	Dict	ormar fields in defined in current class	required
new_model_fields	Dict	ormar fields defined in parent classes	required
new_fields	Set	set of new fields names	required

Source code in ormar\models\metaclass.py

def update_attrs_and_fields(
    attrs: Dict,
    new_attrs: Dict,
    model_fields: Dict,
    new_model_fields: Dict,
    new_fields: Set,
) -> Dict:
    """
    Updates __annotations__, values of model fields (so pydantic FieldInfos)
    as well as model.Meta.model_fields definitions from parents.

    :param attrs: new namespace for class being constructed
    :type attrs: Dict
    :param new_attrs: related of the namespace extracted from parent class
    :type new_attrs: Dict
    :param model_fields: ormar fields in defined in current class
    :type model_fields: Dict[str, BaseField]
    :param new_model_fields: ormar fields defined in parent classes
    :type new_model_fields: Dict[str, BaseField]
    :param new_fields: set of new fields names
    :type new_fields: Set[str]
    """
    key = "__annotations__"
    attrs[key].update(new_attrs[key])
    attrs.update({name: new_attrs[name] for name in new_fields})
    updated_model_fields = {k: v for k, v in new_model_fields.items()}
    updated_model_fields.update(model_fields)
    return updated_model_fields

update_attrs_from_base_meta(base_class, attrs, model_fields)

Updates Meta parameters in child from parent if needed.

Parameters:

Name	Type	Description	Default
base_class	Model	one of the parent classes	required
attrs	Dict	new namespace for class being constructed	required
model_fields	Dict	ormar fields in defined in current class	required

Source code in ormar\models\metaclass.py

def update_attrs_from_base_meta(  # noqa: CCR001
    base_class: "Model", attrs: Dict, model_fields: Dict
) -> None:
    """
    Updates Meta parameters in child from parent if needed.

    :param base_class: one of the parent classes
    :type base_class: Model or model parent class
    :param attrs: new namespace for class being constructed
    :type attrs: Dict
    :param model_fields: ormar fields in defined in current class
    :type model_fields: Dict[str, BaseField]
    """

    params_to_update = ["metadata", "database", "constraints", "property_fields"]
    for param in params_to_update:
        current_value = attrs.get("Meta", {}).__dict__.get(param, ormar.Undefined)
        parent_value = (
            base_class.Meta.__dict__.get(param) if hasattr(base_class, "Meta") else None
        )
        if parent_value:
            if param == "constraints":
                verify_constraint_names(
                    base_class=base_class,
                    model_fields=model_fields,
                    parent_value=parent_value,
                )
                parent_value = [get_constraint_copy(value) for value in parent_value]
            if isinstance(current_value, list):
                current_value.extend(parent_value)
            else:
                setattr(attrs["Meta"], param, parent_value)

verify_constraint_names(base_class, model_fields, parent_value)

Verifies if redefined fields that are overwritten in subclasses did not remove any name of the column that is used in constraint as it will fail in sqlalchemy Table creation.

Parameters:

Name	Type	Description	Default
base_class	Model	one of the parent classes	required
model_fields	Dict	ormar fields in defined in current class	required
parent_value	List	list of base class constraints	required

Source code in ormar\models\metaclass.py

def verify_constraint_names(
    base_class: "Model", model_fields: Dict, parent_value: List
) -> None:
    """
    Verifies if redefined fields that are overwritten in subclasses did not remove
    any name of the column that is used in constraint as it will fail in sqlalchemy
    Table creation.

    :param base_class: one of the parent classes
    :type base_class: Model or model parent class
    :param model_fields: ormar fields in defined in current class
    :type model_fields: Dict[str, BaseField]
    :param parent_value: list of base class constraints
    :type parent_value: List
    """
    new_aliases = {x.name: x.get_alias() for x in model_fields.values()}
    old_aliases = {x.name: x.get_alias() for x in base_class.Meta.model_fields.values()}
    old_aliases.update(new_aliases)
    constraints_columns = [x._pending_colargs for x in parent_value]
    for column_set in constraints_columns:
        if any(x not in old_aliases.values() for x in column_set):
            raise ModelDefinitionError(
                f"Column constraints "
                f"{column_set} "
                f"has column names "
                f"that are not in the model fields."
                f"\n Check columns redefined in subclasses "
                f"to verify that they have proper 'name' set."
            )