DatasourceFlowsUpdateDataflowConfigDataTransformationConfiguration¶
- pydantic model openapi_client.models.datasource_flows_update_dataflow_config_data_transformation_configuration.DatasourceFlowsUpdateDataflowConfigDataTransformationConfiguration¶
Data transformation settings for Streams datasources.
- Fields:
- field data_transformation_entity_id: Optional[StrictStr] = None (alias 'DataTransformationEntityId')¶
ID of the transformation function entity. Required when IsDataTransformationEnabled is true.
- field data_transformation_entity_name: Optional[StrictStr] = None (alias 'DataTransformationEntityName')¶
Name of the transformation function entity.
- field data_transformation_buffer_size: Optional[StrictInt] = None (alias 'DataTransformationBufferSize')¶
Buffer size in MB for transformation. Allowed values are 1, 2, and 3. Default is 3.
- field data_transformation_buffer_interval: Optional[StrictInt] = None (alias 'DataTransformationBufferInterval')¶
Buffer interval in seconds. Valid range is 0 to 900. Default is 60.
- 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 DatasourceFlowsUpdateDataflowConfigDataTransformationConfiguration 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 DatasourceFlowsUpdateDataflowConfigDataTransformationConfiguration from a dict
- Return type:
Optional[Self]