How can I return lists from Python Operator in airflow and use it as argument for subsequent task in dags

Question

I have 3 tasks to run in same dags. While Task1 return list of dictionary task2 and task3 try to use one dictionary element from result return by task1.

def get_list():
    ....
    return listOfDict

def parse_1(example_dict):
    ...

def parse_2(example_dict):
    ...

dag = DAG('dagexample', default_args=default_args)
data_list = PythonOperator(
task_id='get_lists',
python_callable=get_list,
dag=dag)
for data in data_list:
    sub_task1 = PythonOperator(
        task_id='data_parse1' + data['id'],
        python_callable=parse_1,
        op_kwargs={'dataObject': data},
        dag=dag,
     )
    sub_task2 = PythonOperator(
        task_id='data_parse2' + data['id'],
        python_callable=parse_2,
        op_kwargs={'dataObject': data},
        dag=dag,
     )

Answer 1

You should use XCom for passing variables/messages between different task. Take a look at this example: https://github.com/apache/incubator-airflow/blob/master/airflow/example_dags/example_xcom.py

For your case, it should be something similar as below:

default_args = {
    'owner': 'airflow',
    'start_date': airflow.utils.dates.days_ago(2),
    'provide_context': True, # This is needed
}


def get_list():
    ....
    return listOfDict

def parse_1(**kwargs):
    ti = kwargs['ti']

    # get listOfDict
    v1 = ti.xcom_pull(key=None, task_ids='get_lists')

    # You can now use this v1 dictionary as a normal python dict
    ...

def parse_2(**kwargs):
    ti = kwargs['ti']

    # get listOfDict
    v1 = ti.xcom_pull(key=None, task_ids='get_lists')
    ...

dag = DAG('dagexample', default_args=default_args)
data_list = PythonOperator(
    task_id='get_lists',
    python_callable=get_list,
    dag=dag)

for data in get_list():
    sub_task1 = PythonOperator(
        task_id='data_parse1' + data['id'],
        python_callable=parse_1,
        op_kwargs={'dataObject': data},
        dag=dag,
     )

    sub_task2 = PythonOperator(
        task_id='data_parse2' + data['id'],
        python_callable=parse_2,
        op_kwargs={'dataObject': data},
        dag=dag,
     )

Answer 2

You can use XComs as they are designed for inter-task communication. If your dictionary is very big, then I recommend storing it as a csv file. Generally, tasks in Airflow don't share data between them, so XComs are a way to achieve them but are limited to small amounts of data.