BatchUpdateDatasetMetadataInner

class openapi_client.models.batch_update_dataset_metadata_inner.BatchUpdateDatasetMetadataInner(**data)

Bases: BaseModel

dataset_description: Optional[StrictStr]

dataset_id: StrictStr

dataset_name: Optional[StrictStr]

domain: Optional[StrictStr]

file_type: Optional[StrictStr]

is_active: Optional[StrictStr]

access_type: Optional[StrictStr]

registration_status: Optional[StrictStr]

table_update: Optional[StrictStr]

target_location: Optional[StrictStr]

checked: Optional[StrictBool]

data_classification: Optional[List[StrictStr]]

datasource_type: Optional[StrictStr]

keywords: Optional[List[StrictStr]]

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True}

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

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of BatchUpdateDatasetMetadataInner from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of BatchUpdateDatasetMetadataInner from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'access_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='AccessType', alias_priority=2), 'checked': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False), 'data_classification': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='DataClassification', alias_priority=2), 'dataset_description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetDescription', alias_priority=2), 'dataset_id': FieldInfo(annotation=str, required=True, alias='DatasetId', alias_priority=2, metadata=[Strict(strict=True)]), 'dataset_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetName', alias_priority=2), 'datasource_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasourceType', alias_priority=2), 'domain': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Domain', alias_priority=2), 'file_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='FileType', alias_priority=2), 'is_active': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='IsActive', alias_priority=2), 'keywords': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='Keywords', alias_priority=2), 'registration_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='RegistrationStatus', alias_priority=2), 'table_update': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TableUpdate', alias_priority=2), 'target_location': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TargetLocation', alias_priority=2)}

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

This replaces Model.__fields__ from Pydantic V1.

model_post_init(__context)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• __context (Any) – The context.

Return type:

None