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Apache Airflow Sample BranchPythonOperator DAG file
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from datetime import datetime, timedelta | |
from airflow import DAG | |
from airflow.operators.empty import EmptyOperator | |
from airflow.decorators import task | |
from airflow.decorators.branch_python import branch_task | |
@task(task_id='beginning') | |
def beginning() -> int: | |
"""airflow.decorators.python | |
https://github.com/apache/airflow/blob/main/airflow/decorators/python.py | |
""" | |
import random | |
return random.randint(1, 3) | |
@branch_task(task_id='branching') | |
def branching(random_num: int) -> list: | |
"""airflow.decorators.branch_python | |
https://github.com/apache/airflow/blob/main/airflow/decorators/branch_python.py | |
""" | |
if random_num == 1: | |
return ['task_1'] | |
elif random_num == 2: | |
return ['task_2'] | |
elif random_num == 3: | |
return ['task_3'] | |
with DAG( | |
dag_id='sample_branching', | |
description='A Sample BranchPythonOperator DAG', | |
schedule_interval=timedelta(days=1), | |
start_date=datetime(2022, 6, 1), | |
catchup=False, | |
tags=['sample'], | |
) as dag: | |
# airflow.operators.empty | |
# https://github.com/apache/airflow/blob/main/airflow/operators/empty.py | |
task_1 = EmptyOperator(task_id='task_1') | |
task_2 = EmptyOperator(task_id='task_2') | |
task_3 = EmptyOperator(task_id='task_3') | |
# airflow.utils.trigger_rule | |
# https://github.com/apache/airflow/blob/main/airflow/utils/trigger_rule.py | |
finishing = EmptyOperator( | |
task_id='finishing', | |
trigger_rule='none_failed_min_one_success' | |
) | |
# setting up dependencies. | |
branching(beginning()) >> [task_1, task_2, task_3] >> finishing |
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