class_docstr: The selective execution configuration, which defines a subset of pipeline steps to run in
  
  another SageMaker pipeline run.
docstr: Create a `SelectiveExecutionConfig`.
  
  Args:
      source_pipeline_execution_arn (str): The ARN from a reference execution of the
          current pipeline. Used to copy input collaterals needed for the selected
          steps to run. The execution status of the pipeline can be `Stopped`, `Failed`, or
          `Succeeded`.
      selected_steps (List[str]): A list of pipeline steps to run. All step(s) in all
          path(s) between two selected steps should be included.
      reference_latest_execution (bool): Whether to reference the latest execution if
          `source_pipeline_execution_arn` is not provided.
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code: def __init__(
      self,
      selected_steps: List[str],
      source_pipeline_execution_arn: str = None,
      reference_latest_execution: bool = True,
  ):
      """Create a `SelectiveExecutionConfig`.
  
      Args:
          source_pipeline_execution_arn (str): The ARN from a reference execution of the
              current pipeline. Used to copy input collaterals needed for the selected
              steps to run. The execution status of the pipeline can be `Stopped`, `Failed`, or
              `Succeeded`.
          selected_steps (List[str]): A list of pipeline steps to run. All step(s) in all
              path(s) between two selected steps should be included.
          reference_latest_execution (bool): Whether to reference the latest execution if
              `source_pipeline_execution_arn` is not provided.
      """
      self.source_pipeline_execution_arn = source_pipeline_execution_arn
      self.selected_steps = selected_steps
      self.reference_latest_execution = reference_latest_execution
  
imports: from __future__ import absolute_import
  from typing import List
  from sagemaker.workflow.entities import RequestType
label_desc: Use image node_id 1 to create a new SelectiveExecutionConfig object  with example: obj = SelectiveExecutionConfig(selected_steps, source_pipeline_execution_arn, reference_latest_execution)