CreateDataPipelineRequestBody

pydantic model openapi_client.models.create_data_pipeline_request_body.CreateDataPipelineRequestBody

POST /data-pipelines body. Glue (default) requires DataPipelineName, Nodes, Graph, Description, Keywords. Name is 3-50 alphanumeric/underscore (IPV-1004 / IPV-1018). MaxConcurrentRuns defaults to 1 (max 600). AI create (DataPipelineType=ai) allows only DataPipelineName, DataPipelineType, Description, Nodes, DefaultExecutionProperties, Graph, Keywords (IPV-1078 for extra keys). Glue graph validation failures return HTTP 501 DP-1010.

Fields:

• additional_properties (Dict[str, Any])

• cost_tags (List[openapi_client.models.data_pipeline_cost_tag.DataPipelineCostTag] | None)

• data_pipeline_name (str)

• data_pipeline_type (str | None)

• default_execution_properties (Dict[str, str] | None)

• description (str | None)

• graph (Dict[str, openapi_client.models.data_pipeline_graph_successors.DataPipelineGraphSuccessors] | None)

• keywords (List[str] | None)

• max_concurrent_runs (int | None)

• nodes (List[openapi_client.models.data_pipeline_node.DataPipelineNode] | None)

• notification_configuration (List[openapi_client.models.data_pipelines_notification_configuration_inner.DataPipelinesNotificationConfigurationInner] | None)

field data_pipeline_name: StrictStr [Required] (alias 'DataPipelineName')

Constraints:

• strict = True

field description: Optional[StrictStr] = None (alias 'Description')

field data_pipeline_type: Optional[StrictStr] = None (alias 'DataPipelineType')

Omit or glue for Glue workflows. ai selects Bedrock Flow create.

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

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

field default_execution_properties: Optional[Dict[str, StrictStr]] = None (alias 'DefaultExecutionProperties')

String-to-string map. Keys 1-255 characters. AI executions may read InputString from here.

field notification_configuration: Optional[List[DataPipelinesNotificationConfigurationInner]] = None (alias 'NotificationConfiguration')

List of notification configurations for data pipeline events.

field nodes: Optional[List[DataPipelineNode]] = None (alias 'Nodes')

field graph: Optional[Dict[str, DataPipelineGraphSuccessors]] = None (alias 'Graph')

Directed acyclic graph. Glue keys are NodeNames. AI Flow keys are NodeName.port (for example FlowInput.document) with success/failure targets also as NodeName.port. Each value is {success, failure} lists. Shared by create, update, details, and execution payloads.

field max_concurrent_runs: Optional[Annotated[int, Field(le=600, strict=True, ge=1)]] = 1 (alias 'MaxConcurrentRuns')

field additional_properties: Dict[str, Any] = {}

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 CreateDataPipelineRequestBody 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.

• Fields in self.additional_properties are added to the output dict.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of CreateDataPipelineRequestBody from a dict

Return type:

Optional[Self]