from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.operators.bash import BashOperator

# 默认参数定义
default_args = {
    'owner': 'xiaozhang',
    'depends_on_past': False,
    'email_on_failure': False,
    "on_failure_callback":xx,
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
}

# dag = DAG(
#     dag_id='hello_world',
#     default_args=default_args,
#     start_date=datetime(2023, 1, 1),
#     schedule_interval='@daily',
#     catchup=False,
#     tags= ["demo"]
# )

# 定义任务
def print_hello():
    print("Hello, World!")

# 实例化DAG
with DAG(
    dag_id='hello_world',
    default_args=default_args,
    description="这个是一个样例",
    start_date=datetime(2024, 10, 1),
    schedule_interval='@daily',
    catchup=True,
    tags= ["demo","xiaozhang"]
) as dag:

    task1 = PythonOperator(
        task_id='print_hello',
        python_callable=print_hello
    )

    task2 = BashOperator(
        task_id='run_bash_command',
        bash_command='echo "This is a Bash command"',
    )

    # 定义依赖关系
    task1 >> task2  # task2将在task1完成后执行
    # task1.set_downstream(task2) # 这种写法也可以，但是不太推荐，因为不够直观