Source code for airflow.example_dags.example_branch_python_dop_operator_3

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"""
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()
[docs]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:
[docs]    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]