code: def compile(self):
      from airflow import DAG
  
      # Airflow 2.0.0 cannot import this, so we have to do it this way.
      # `XComArg` is needed for dynamic task mapping and if the airflow installation is of the right
      # version (+2.3.0) then the class will be importable.
      XComArg = get_xcom_arg_class()
  
      _validate_minimum_airflow_version()
  
      if self._metadata["contains_foreach"]:
          _validate_dynamic_mapping_compatibility()
          # We need to verify if KubernetesPodOperator is of version > 4.2.0 to support foreachs / dynamic task mapping.
          # If the dag uses dynamic Task mapping then we throw an error since the `resources` argument in the `KubernetesPodOperator`
          # doesn't work for dynamic task mapping for `KubernetesPodOperator` version < 4.2.0.
          # For more context check this issue :  https://github.com/apache/airflow/issues/24669
          _check_foreach_compatible_kubernetes_provider()
  
      params_dict = self._construct_params()
      # DAG Params can be seen here :
      # https://airflow.apache.org/docs/apache-airflow/2.0.0/_api/airflow/models/dag/index.html#airflow.models.dag.DAG
      # Airflow 2.0.0 Allows setting Params.
      dag = DAG(
          params=params_dict, **self._dag_instantiation_params.arguments
      )
      dag.fileloc = (
          self._file_path
          if self._file_path is not None
          else dag.fileloc
      )
  
      def add_node(node, parents, dag):
          """
          A recursive function to traverse the specialized
          graph_structure datastructure.
          """
          if type(node) == str:
              task = self.states[node].to_task()
              if parents:
                  for parent in parents:
                      # Handle foreach nodes.
                      if self.states[node].is_mapper_node:
                          task = task.expand(mapper_arr=XComArg(parent))
                      parent >> task
              return [task]  # Return Parent
  
          # this means a split from parent
          if type(node) == list:
              # this means branching since everything within the list is a list
              if all(isinstance(n, list) for n in node):
                  curr_parents = parents
                  parent_list = []
                  for node_list in node:
                      last_parent = add_node(
                          node_list, curr_parents, dag
                      )
                      parent_list.extend(last_parent)
                  return parent_list
              else:
                  # this means no branching and everything within the list is not a list and can be actual nodes.
                  curr_parents = parents
                  for node_x in node:
                      curr_parents = add_node(node_x, curr_parents, dag)
                  return curr_parents
  
      with dag:
          parent = None
          for node in self.graph_structure:
              parent = add_node(node, parent, dag)
  
      return dag
  
imports: import hashlib
  import json
  import sys
  import platform
  from collections import defaultdict
  from datetime import datetime, timedelta
label_desc: Use image node_id 9 for calling the Workflow obj's underlying member method code with example usage: obj.compile() and returns: dag, list, parent_list, curr_parents