MetadataGeneratorInput

pydantic model openapi_client.models.metadata_generator_input.MetadataGeneratorInput

Request body for POST /generate-payload/{resource_type}. Action selects get-schema (extract columns from uploaded file) or get-payload (build create-dataset body). Extra fields apply to get-payload.

Fields:
field file_name: StrictStr [Required] (alias 'FileName')

S3 key of the uploaded sample file under generate_payload/.

Constraints:
  • strict = True

field action: StrictStr [Required] (alias 'Action')

Operation to perform.

Constraints:
  • strict = True

field target_location: Optional[StrictStr] = None (alias 'TargetLocation')

Target storage backend for the generated payload (get-payload / get-schema).

field dataset_name: Optional[StrictStr] = None (alias 'DatasetName')

Proposed dataset name (get-payload).

field domain: Optional[StrictStr] = None (alias 'Domain')

Existing domain name (get-payload).

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

Search keywords (get-payload).

field table_update: Optional[StrictStr] = None (alias 'TableUpdate')

Load mode for the generated payload (get-payload).

field dataset_description: Optional[StrictStr] = None (alias 'DatasetDescription')

Optional description (get-payload).

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 MetadataGeneratorInput 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 MetadataGeneratorInput from a dict

Return type:

Optional[Self]