class_docstr: Pipeline config for AirflowDagRunner.
class_docstr_tok: ["Pipeline","config","for","AirflowDagRunner","."]
docstr: Creates an instance of AirflowPipelineConfig.
  
  Args:
    airflow_dag_config: Configs of Airflow DAG model. See
      https://airflow.apache.org/_api/airflow/models/dag/index.html#airflow.models.dag.DAG
        for the full spec.
    **kwargs: keyword args for PipelineConfig.
docstr_tok: ["Creates","an","instance","of","AirflowPipelineConfig",".","Args",":","airflow_dag_config",":","Configs","of","Airflow","DAG","model",".","See","https",":","\/\/airflow.apache.org\/_api\/airflow\/models\/dag\/index.html","#","airflow.models.dag.DAG","for","the","full","spec",".","*","*","kwargs",":","keyword","args","for","PipelineConfig","."]
code: def __init__(
      self,
      airflow_dag_config: Optional[Dict[str, Any]] = None,
      **kwargs,
  ):
      """Creates an instance of AirflowPipelineConfig.
  
      Args:
        airflow_dag_config: Configs of Airflow DAG model. See
          https://airflow.apache.org/_api/airflow/models/dag/index.html#airflow.models.dag.DAG
            for the full spec.
        **kwargs: keyword args for PipelineConfig.
      """
  
      super().__init__(**kwargs)
      self.airflow_dag_config = airflow_dag_config or {}
  
imports: import os
  import typing
  from typing import Any, Dict, Optional, Union
  import warnings
  from airflow import models
  from tfx.dsl.components.base import base_component
  from tfx.orchestration import pipeline
  from tfx.orchestration import tfx_runner
  from tfx.orchestration.airflow import airflow_component
  from tfx.orchestration.config import config_utils
  from tfx.orchestration.config import pipeline_config
  from tfx.orchestration.data_types import RuntimeParameter
  from tfx.utils.json_utils import json
label_desc: Use image node_id 1 to create a new AirflowPipelineConfig object from inherited base classes: pipeline_config with example: obj = AirflowPipelineConfig(airflow_dag_config)