每个任务的依赖关系都必须指定，以确保它们在正确的顺序下运行。如下示例：

from airflow import DAG from airflow.operators.python_operator import PythonOperator from datetime import datetime

default_args = { 'owner': 'airflow', 'depends_on_past': False, 'start_date': datetime(2021, 1, 1), } dag = DAG('example_dag', default_args=default_args)

def task_one(): print('Task one executed')

def task_two(): print('Task two executed')

def task_three(): print('Task three executed')

t1 = PythonOperator( task_id='task_one', python_callable=task_one, dag=dag )

t2 = PythonOperator( task_id='task_two', python_callable=task_two, dag=dag )

t3 = PythonOperator( task_id='task_three', python_callable=task_three, dag=dag )

t1 >> t2 >> t3 # 指定任务之间的依赖关系

在DAG中指定任务的顺序，以确保它们按正确的顺序运行。如下示例：

from airflow import DAG from airflow.operators.python_operator import PythonOperator from datetime import datetime

default_args = { 'owner': 'airflow', 'depends_on_past': False, 'start_date': datetime(2021, 1, 1), } dag = DAG('example_dag', default_args=default_args)

def task_one(): print('Task one executed')

def task_two(): print('Task two executed')

def task_three(): print('Task three executed')

按顺序指定任务

t1 = PythonOperator( task_id='task_one', python_callable=task_one, dag=dag )

t2 = PythonOperator( task_id='task_two', python_callable=task_two, dag=dag