dags/single_task.py

from airflow import DAG
from datetime import datetime
from airflow.operators.bash import BashOperator
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator
from airflow.configuration import conf

namespace = conf.get("kubernetes", "NAMESPACE")


# set the name that will be printed
name = "luoyulong"

# instantiate the DAG
with DAG(
        start_date=datetime(2022,6,1),
        catchup=False,
        schedule_interval='@daily',
        dag_id="single_task"
) as dag:
    
        op_6aeed233_0951_4637_99e8_4736262edc94 = KubernetesPodOperator(
        task_id="6aeed233-0951-4637-99e8-4736262edc94",
        image="SXKJ:32775/pod_python:1.1",
        in_cluster=True,
        namespace=namespace,
        name="PythonNode1",
        random_name_suffix=True,
        labels={'app':'backend', 'env':'dev'},
        reattach_on_restart=True,
        is_delete_operator_pod=False,
        get_logs=True,
        log_events_on_failure=True,
        cmds=['/bin/bash', '-c', 'echo -e "$SCRIPT" > run.py && python run.py '],
        env_vars={'SCRIPT': "import numpy as np\nimport os\n\n\ndef hello():\n    for i in range(10):\n        print(f'{i}: ok!')\n    print(os.environ)\n\n\nif __name__ == '__main__':\n    hello()\n"}
        )