branch_python_dop_operator

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:

Apache Airflow

Modules:

DummyOperator

BranchPythonOperator

Last Updated: May. 3, 2022

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:

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#
# 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 ``@task.branch`` TaskFlow API decorator with depends_on_past=True,
where tasks may be run or skipped on alternating runs.
"""
from __future__ import annotations

import pendulum

from airflow.decorators import task
from airflow.models.dag import DAG
from airflow.operators.empty import EmptyOperator


@task.branch()
def should_run(**kwargs) -> str:
    """
    Determine which empty_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
    """
    print(
        f"------------- exec dttm = {kwargs['execution_date']} and minute = {kwargs['execution_date'].minute}"
    )
    if kwargs["execution_date"].minute % 2 == 0:
        return "empty_task_1"
    else:
        return "empty_task_2"


with DAG(
    dag_id="example_branch_dop_operator_v3",
    schedule="*/1 * * * *",
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    catchup=False,
    default_args={"depends_on_past": True},
    tags=["example"],
) as dag:
    cond = should_run()

    empty_task_1 = EmptyOperator(task_id="empty_task_1")
    empty_task_2 = EmptyOperator(task_id="empty_task_2")
    cond >> [empty_task_1, empty_task_2]

branch_python_dop_operator_3

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