code: def tutorial_taskflow_api():
      """
      ### TaskFlow API Tutorial Documentation
      This is a simple data pipeline example which demonstrates the use of
      the TaskFlow API using three simple tasks for Extract, Transform, and Load.
      Documentation that goes along with the Airflow TaskFlow API tutorial is
      located
      [here](https://airflow.apache.org/docs/apache-airflow/stable/tutorial_taskflow_api.html)
      """
      # [END instantiate_dag]
  
      # [START extract]
      @task()
      def extract():
          """
          #### Extract task
          A simple Extract task to get data ready for the rest of the data
          pipeline. In this case, getting data is simulated by reading from a
          hardcoded JSON string.
          """
          data_string = (
              '{"1001": 301.27, "1002": 433.21, "1003": 502.22}'
          )
  
          order_data_dict = json.loads(data_string)
          return order_data_dict
  
      # [END extract]
  
      # [START transform]
      @task(multiple_outputs=True)
      def transform(order_data_dict: dict):
          """
          #### Transform task
          A simple Transform task which takes in the collection of order data and
          computes the total order value.
          """
          total_order_value = 0
  
          for value in order_data_dict.values():
              total_order_value += value
  
          return {"total_order_value": total_order_value}
  
      # [END transform]
  
      # [START load]
      @task()
      def load(total_order_value: float):
          """
          #### Load task
          A simple Load task which takes in the result of the Transform task and
          instead of saving it to end user review, just prints it out.
          """
  
          print(f"Total order value is: {total_order_value:.2f}")
  
      # [END load]
  
      # [START main_flow]
      order_data = extract()
      order_summary = transform(order_data)
      load(order_summary["total_order_value"])
  
imports: from __future__ import annotations
  import json
  import pendulum
  from airflow.decorators import dag, task
label_desc: Use image node_id 1 for calling a global function with example usage: tutorial_taskflow_api() and returns: order_data_dict, dict