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Pycharm调试Airflow

Pycharm调试Airflow

作者: zfylin | 来源:发表于2020-11-11 14:42 被阅读0次

    本机Airflow 安装

    # 1. 配置airflow环境变量  
    echo '\nexport AIRFLOW_HOME=~/opt/airflow' > ~/.bashrc
    source ~/.bashrc
    
    # 2. 安装airflow
    pip install apache-airflow
    airflow initdb
    
    # 3. 启动airflow
    airflow webserver -D
    airflow scheduler -D
    
    # 4. 创建dags目录
    mkdir ~/opt/airflow/dags
    

    Pycharm 配置

    设置Interpreter

    python env 选择安装airflow的python, 这样pycharm的环境才会包含airflow的依赖。

    image-20201110140343519.png image-20201110140410115.png

    新建Dag

    pycharm打开 ${AIRFLOW_HOME} 目录,在dags目录下新建hello dag

    image-20201110141137000.png
    # hello.py
    # -*- coding: utf-8 -*-
    from datetime import timedelta
    
    from airflow import DAG
    from airflow.operators.dummy_operator import DummyOperator
    from airflow.operators.python_operator import PythonOperator
    from airflow.utils.dates import days_ago
    
    args = {
        'owner': 'airflow',
    }
    dag = DAG(
        dag_id='hello',
        default_args=args,
        schedule_interval=None,
        start_date=days_ago(1),
        dagrun_timeout=timedelta(minutes=60)
    )
    
    
    def print_hello():
        print('Hello airflow!!')
        return 'Hello airflow!!'
    
    
    dummy_operator = DummyOperator(task_id='start', retries=3, dag=dag)
    
    hello_operator = PythonOperator(task_id='hello', python_callable=print_hello, dag=dag)
    
    dummy_operator >> hello_operator
    
    

    Airflow test

    # airflow test
    # usage: airflow test [-h] [-sd SUBDIR] [-dr] [-tp TASK_PARAMS] [-pm] dag_id task_id execution_date
    airflow test hello hello 2020-10-10
    
    image-20201110141334555.png

    Pycharm run

    image-20201110142744922.png

    然后run hello.py

    image-20201110142905241.png

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