Source code for airflow.example_dags.example_local_kubernetes_executor

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"""
This is an example dag for using a Local Kubernetes Executor Configuration.
"""

from __future__ import annotations

import logging
from datetime import datetime

from airflow.configuration import conf
from airflow.decorators import task
from airflow.example_dags.libs.helper import print_stuff
from airflow.models.dag import DAG

[docs]log = logging.getLogger(__name__)

[docs]worker_container_repository = conf.get("kubernetes_executor", "worker_container_repository")
[docs]worker_container_tag = conf.get("kubernetes_executor", "worker_container_tag")

try:
    from kubernetes.client import models as k8s
except ImportError:
    log.warning("Could not import DAGs in example_local_kubernetes_executor.py", exc_info=True)
    log.warning("Install Kubernetes dependencies with: pip install apache-airflow[cncf.kubernetes]")
[docs]    k8s = None

if k8s:
    with DAG(
        dag_id="example_local_kubernetes_executor",
        schedule=None,
        start_date=datetime(2021, 1, 1),
        catchup=False,
        tags=["example3"],
    ) as dag:
        # You can use annotations on your kubernetes pods!
[docs]        start_task_executor_config = {
            "pod_override": k8s.V1Pod(metadata=k8s.V1ObjectMeta(annotations={"test": "annotation"}))
        }

        @task(
            executor_config=start_task_executor_config,
            queue="kubernetes",
            task_id="task_with_kubernetes_executor",
        )
        def task_with_template():
            print_stuff()

        @task(task_id="task_with_local_executor")
        def task_with_local(ds=None, **kwargs):
            """Print the Airflow context and ds variable from the context."""
            print(kwargs)
            print(ds)
            return "Whatever you return gets printed in the logs"

        task_with_local() >> task_with_template()