branch_python_dop_operator_3

Example DAG demonstrating the usage of BranchPythonOperator with depends_on_past=True, where tasks may be run or skipped on alternating runs.

Airflow Fundamentals


Providers:

Run this DAG

1. Install the Astronomer CLI:Skip if you already have the CLI

2. Initate the project in a local directory:

3. Copy and paste the code below into a file in the

dags
directory.

4. Run the DAG from the local directory where the project was initiated:

#
# 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
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example DAG demonstrating the usage of BranchPythonOperator with depends_on_past=True, where tasks may be run
or skipped on alternating runs.
"""
from airflow import DAG
from airflow.operators.dummy import DummyOperator
from airflow.operators.python import BranchPythonOperator
from airflow.utils.dates import days_ago
args = {
'owner': 'airflow',
'depends_on_past': True,
}
def should_run(**kwargs):
"""
Determine which dummy_task should be run based on if the execution date minute is even or odd.
:param dict kwargs: Context
:return: Id of the task to run
:rtype: str
"""
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"
with DAG(
dag_id='example_branch_dop_operator_v3',
schedule_interval='*/1 * * * *',
start_date=days_ago(2),
default_args=args,
tags=['example'],
) as dag:
cond = BranchPythonOperator(
task_id='condition',
python_callable=should_run,
)
dummy_task_1 = DummyOperator(task_id='dummy_task_1')
dummy_task_2 = DummyOperator(task_id='dummy_task_2')
cond >> [dummy_task_1, dummy_task_2]