airflow example_local_kubernetes_executor 源码
airflow example_local_kubernetes_executor 代码
文件路径：/airflow/example_dags/example_local_kubernetes_executor.py
#
# Licensed to the Apache Software Foundation (ASF) under one
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# 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
#
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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 import DAG
from airflow.configuration import conf
from airflow.decorators import task
from airflow.example_dags.libs.helper import print_stuff
log = logging.getLogger(__name__)
worker_container_repository = conf.get('kubernetes_executor', 'worker_container_repository')
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]")
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!
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()
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