DatalabsListResponseDatalabsInner

class openapi_client.models.datalabs_list_response_datalabs_inner.DatalabsListResponseDatalabsInner(**data)

Bases: BaseModel

datalab_id: Optional[StrictStr]

datalab_name: Optional[StrictStr]

datalab_type: Optional[StrictStr]

message: Optional[StrictStr]

description: Optional[StrictStr]

access_type: Optional[StrictStr]

datalab_status: Optional[StrictStr]

created_by: Optional[StrictStr]

creation_time: Optional[StrictStr]

last_modified_by: Optional[StrictStr]

last_modified_time: Optional[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 DatalabsListResponseDatalabsInner 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 DatalabsListResponseDatalabsInner 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), 'created_by': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='CreatedBy', alias_priority=2), 'creation_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='CreationTime', alias_priority=2), 'datalab_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatalabId', alias_priority=2), 'datalab_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatalabName', alias_priority=2), 'datalab_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatalabStatus', alias_priority=2), 'datalab_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatalabType', alias_priority=2), 'description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Description', alias_priority=2), 'last_modified_by': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LastModifiedBy', alias_priority=2), 'last_modified_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LastModifiedTime', alias_priority=2), 'message': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Message', 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