python – airflow
时间: 2023-10-21 08:29:28 浏览: 40
Airflow是一个用于编排、调度和监控工作流程的开源平台。它使用Python编写,并提供了一个易于使用的界面来管理工作流程。Airflow可以帮助用户创建复杂的工作流程,其中包含多个任务和依赖关系,并且可以自动执行这些任务。它还提供了强大的调度和监控功能,使用户能够按需运行任务,并实时查看任务的状态和日志。Airflow还支持插件和扩展,可以与其他工具和平台集成,提供更多的功能和灵活性。
相关问题
PythonOperator Airflow 使用教程
PythonOperator 是 Airflow 中常用的一个 Operator,用于执行 Python 脚本。以下是 PythonOperator 的使用教程:
1. 导入 PythonOperator
```
from airflow.operators.python_operator import PythonOperator
```
2. 定义 Python 函数
```
def my_python_function():
# your python code here
```
3. 创建 PythonOperator 实例
```
my_operator = PythonOperator(
task_id='my_task',
python_callable=my_python_function,
dag=my_dag,
)
```
4. 参数说明
- `task_id`: 任务的 ID,必须唯一。
- `python_callable`: 要执行的 Python 函数。
- `dag`: 任务所属的 DAG。
5. 添加任务依赖
```
my_other_task >> my_operator
```
6. 完整示例
```
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
default_args = {
'owner': 'airflow',
'start_date': datetime(2021, 1, 1),
'retries': 1,
'retry_delay': timedelta(minutes=5),
}
dag = DAG(
'my_dag',
default_args=default_args,
schedule_interval=timedelta(days=1),
)
def my_python_function():
# your python code here
my_operator = PythonOperator(
task_id='my_task',
python_callable=my_python_function,
dag=dag,
)
my_other_task >> my_operator
```
希望这个 PythonOperator 的使用教程能够帮助到您!
airflow pythonoperator
Airflow PythonOperator is a task in Apache Airflow that allows you to execute a Python function as a task within an Airflow DAG (Directed Acyclic Graph). It is one of the most commonly used operators in Airflow.
The PythonOperator takes a python_callable argument, which is the function you want to execute, and any other necessary arguments for that function. When the task is executed, Airflow will call the specified Python function and perform the logic inside it.
Here's an example of how to use PythonOperator in an Airflow DAG:
```python
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from datetime import datetime
def my_python_function():
# Your logic here
print("Hello, I am running inside a PythonOperator")
dag = DAG(
'my_dag',
start_date=datetime(2022, 1, 1),
schedule_interval='@daily'
)
my_task = PythonOperator(
task_id='my_task',
python_callable=my_python_function,
dag=dag
)
```
In this example, we define a DAG called 'my_dag' with a daily schedule interval. We then create a PythonOperator called 'my_task' that executes the function `my_python_function`. Whenever the DAG is triggered, Airflow will execute the logic inside `my_python_function`.
You can add more parameters to the PythonOperator based on your requirements, such as providing arguments to the python_callable function or defining the pool for task execution. The output of the function can also be used by downstream tasks in the DAG.
I hope this answers your question about the Airflow PythonOperator! Let me know if you have any further queries.