HclGetWorkflowRunResponseBody

class openapi_client.models.hcl_get_workflow_run_response_body.HclGetWorkflowRunResponseBody(**data)

Bases: BaseModel

omics_workflow_run_id: Optional[StrictStr]

hcls_workflow_id: Optional[StrictStr]

workflow_run_id: Optional[StrictStr]

workflow_run_status: Optional[StrictStr]

message: Optional[StrictStr]

workflow_run_name: Optional[StrictStr]

started_on: Optional[StrictStr]

storage_capacity: Optional[StrictInt]

workflow_run_params: Optional[Dict[str, Any]]

workflow_run_log_level: Optional[StrictStr]

completed_on: Optional[StrictStr]

started_by: 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 HclGetWorkflowRunResponseBody 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 HclGetWorkflowRunResponseBody from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'completed_on': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='CompletedOn', alias_priority=2), 'hcls_workflow_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='HclsWorkflowId', alias_priority=2), 'message': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Message', alias_priority=2), 'omics_workflow_run_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='OmicsWorkflowRunId', alias_priority=2), 'started_by': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='StartedBy', alias_priority=2), 'started_on': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='StartedOn', alias_priority=2), 'storage_capacity': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='StorageCapacity', alias_priority=2), 'workflow_run_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='WorkflowRunId', alias_priority=2), 'workflow_run_log_level': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='WorkflowRunLogLevel', alias_priority=2), 'workflow_run_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='WorkflowRunName', alias_priority=2), 'workflow_run_params': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, alias='WorkflowRunParams', alias_priority=2), 'workflow_run_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='WorkflowRunStatus', 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