1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | # -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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"""
Example DAG demonstrating the usage of BranchPythonOperator with depends_on_past=True, where tasks may be run
or skipped on alternating runs.
"""
from airflow.models import DAG
from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.python_operator import BranchPythonOperator
from airflow.utils.dates import days_ago
args = {
'owner': 'Airflow',
'start_date': days_ago(2),
'depends_on_past': True,
}
# BranchPython operator that depends on past
# and where tasks may run or be skipped on
# alternating runs
dag = DAG(
dag_id='example_branch_dop_operator_v3',
schedule_interval='*/1 * * * *',
default_args=args,
tags=['example']
)
def should_run(**kwargs):
print('------------- exec dttm = {} and minute = {}'.
format(kwargs['execution_date'], kwargs['execution_date'].minute))
if kwargs['execution_date'].minute % 2 == 0:
return "dummy_task_1"
else:
return "dummy_task_2"
cond = BranchPythonOperator(
task_id='condition',
provide_context=True,
python_callable=should_run,
dag=dag,
)
dummy_task_1 = DummyOperator(task_id='dummy_task_1', dag=dag)
dummy_task_2 = DummyOperator(task_id='dummy_task_2', dag=dag)
cond >> [dummy_task_1, dummy_task_2]
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