hdmf_common_base

class ConfiguredBaseModel(*, hdf5_path: str | None = None, object_id: str | None = None)

Bases: BaseModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

hdf5_path: str | None

object_id: str | None

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[dict[str, FieldInfo]] = {'hdf5_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='The absolute path that this object is stored in an NWB file'), 'object_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Unique UUID for each object')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class LinkMLMeta(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

root: Dict[str, Any]

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[dict[str, FieldInfo]] = {'root': FieldInfo(annotation=Dict[str, Any], required=False, default={})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class Data(*, hdf5_path: str | None = None, object_id: str | None = None, name: str)

Bases: ConfiguredBaseModel

An abstract data type for a dataset.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'hdmf-common.base', 'tree_root': True})

name: str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hdf5_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='The absolute path that this object is stored in an NWB file'), 'name': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Unique UUID for each object')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class Container(*, hdf5_path: str | None = None, object_id: str | None = None, name: str)

Bases: ConfiguredBaseModel

An abstract data type for a group storing collections of data and metadata. Base type for all data and metadata containers.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'hdmf-common.base', 'tree_root': True})

name: str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hdf5_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='The absolute path that this object is stored in an NWB file'), 'name': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Unique UUID for each object')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class SimpleMultiContainer(*, hdf5_path: str | None = None, object_id: str | None = None, name: str, children: List[Container] | None = None)

Bases: Container

A simple Container for holding onto multiple containers.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'hdmf-common.base', 'tree_root': True})

children: List[Container] | None

name: str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'children': FieldInfo(annotation=Union[List[Container], NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'any_of': [{'range': 'Container'}]}}), 'hdf5_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='The absolute path that this object is stored in an NWB file'), 'name': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Unique UUID for each object')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.