DatalabCreateInputAdditionalMetadata

pydantic model openapi_client.models.datalab_create_input_additional_metadata.DatalabCreateInputAdditionalMetadata

Optional settings for keywords, cost tags, interactive sessions and startup scripts.

Fields:
field keywords: Optional[List[StrictStr]] = None (alias 'Keywords')

Search keywords for the datalab.

field cost_tags: Optional[List[ETLJobByIdResponseCostTagsInner]] = None (alias 'CostTags')

Tags used to attribute the datalab’s running cost.

field is_sessions_enabled: Optional[StrictBool] = False (alias 'IsSessionsEnabled')

Notebook datalabs only. Enables interactive sessions, which requires internet access to be Enabled.

field lifecycle_configuration: Optional[StrictStr] = None (alias 'LifecycleConfiguration')

Name of the lifecycle configuration whose startup script runs on this datalab.

field r_studio_access_status: Optional[StrictStr] = None (alias 'RStudioAccessStatus')

Studio datalabs only. Whether RStudio is available.

field studio_advanced_config: Optional[DatalabCreateInputAdditionalMetadataStudioAdvancedConfig] = None (alias 'StudioAdvancedConfig')
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 DatalabCreateInputAdditionalMetadata 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 DatalabCreateInputAdditionalMetadata from a dict

Return type:

Optional[Self]