DatasourceFlowsUpdate

pydantic model openapi_client.models.datasource_flows_update.DatasourceFlowsUpdate

PUT body for updating a dataflow. Editable fields vary by DataflowType.

Fields:

• cdc_tracking_method (str | None)

• create_dataset (bool | None)

• data_format (str | None)

• dataflow_config (openapi_client.models.datasource_flows_update_dataflow_config.DatasourceFlowsUpdateDataflowConfig | None)

• dataflow_description (str | None)

• dataflow_name (str | None)

• dataflow_type (str | None)

• dataset_details (List[openapi_client.models.datasource_flows_update_dataset_details_inner.DatasourceFlowsUpdateDatasetDetailsInner] | None)

• items_config (List[openapi_client.models.datasource_flows_update_items_config_inner.DatasourceFlowsUpdateItemsConfigInner] | None)

• process_type (str | None)

• registered_datasets (str | None)

• reload_option (str | None)

• reload_tables (List[openapi_client.models.datasource_flows_update_reload_tables_inner.DatasourceFlowsUpdateReloadTablesInner] | None)

• target_location (str | None)

field dataflow_name: Optional[StrictStr] = None (alias 'DataflowName')

Display name of the dataflow.

field process_type: Optional[StrictStr] = None (alias 'ProcessType')

Load mode, such as full-load, cdc, or full-load-and-cdc.

field cdc_tracking_method: Optional[StrictStr] = None (alias 'CDCTrackingMethod')

How CDC changes are tracked for ArcGIS datasources.

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

Where ingested data is written, such as s3, s3athena, or redshift.

field dataflow_type: Optional[StrictStr] = None (alias 'DataflowType')

Type of dataflow, such as tasks, kafka-connect, flows, arcgis, or consumers.

field create_dataset: Optional[StrictBool] = None (alias 'CreateDataset')

Whether the dataflow creates new Amorphic datasets or uses existing ones.

field dataset_details: Optional[List[DatasourceFlowsUpdateDatasetDetailsInner]] = None (alias 'DatasetDetails')

Updated per-table or per-dataset configuration for the dataflow.

field dataflow_description: Optional[StrictStr] = None (alias 'DataflowDescription')

Free-text description of the dataflow.

field data_format: Optional[StrictStr] = None (alias 'DataFormat')

Output file format for the dataflow, such as csv, json, or parquet.

field registered_datasets: Optional[StrictStr] = None (alias 'RegisteredDatasets')

Dataset ID linked to a Streams dataflow. Editable on Streams update when CreateDataset is false.

field reload_tables: Optional[List[DatasourceFlowsUpdateReloadTablesInner]] = None (alias 'ReloadTables')

Tables to reload when action is reload-tables on JDBC Bulkload. Each entry needs SchemaName and TableName. Maximum of 10 unique tables per request.

field reload_option: Optional[StrictStr] = None (alias 'ReloadOption')

Optional DMS reload mode for JDBC Bulkload reload-tables. Supported values are data-reload and validate-only.

field items_config: Optional[List[DatasourceFlowsUpdateItemsConfigInner]] = None (alias 'ItemsConfig')

Updated ArcGIS items and layers for the dataflow.

field dataflow_config: Optional[DatasourceFlowsUpdateDataflowConfig] = None (alias 'DataflowConfig')

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 DatasourceFlowsUpdate 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 DatasourceFlowsUpdate from a dict

Return type:

Optional[Self]