从YAML文件动态构建Airflow DAGs
项目描述
dag-factory
dag-factory 是一个用于从YAML配置文件动态生成 Apache Airflow DAGs 的库。
安装
要安装 dag-factory,请运行 pip install dag-factory。它需要Python 3.6.0+ 和 Apache Airflow 2.0+。
用法
在您的Airflow环境中安装 dag-factory 后,创建DAGs有两个步骤。首先,我们需要创建一个YAML配置文件。例如
example_dag1:
  default_args:
    owner: 'example_owner'
    start_date: 2018-01-01  # or '2 days'
    end_date: 2018-01-05
    retries: 1
    retry_delay_sec: 300
  schedule_interval: '0 3 * * *'
  concurrency: 1
  max_active_runs: 1
  dagrun_timeout_sec: 60
  default_view: 'tree'  # or 'graph', 'duration', 'gantt', 'landing_times'
  orientation: 'LR'  # or 'TB', 'RL', 'BT'
  description: 'this is an example dag!'
  on_success_callback_name: print_hello
  on_success_callback_file: /usr/local/airflow/dags/print_hello.py
  on_failure_callback_name: print_hello
  on_failure_callback_file: /usr/local/airflow/dags/print_hello.py
  tasks:
    task_1:
      operator: airflow.operators.bash_operator.BashOperator
      bash_command: 'echo 1'
    task_2:
      operator: airflow.operators.bash_operator.BashOperator
      bash_command: 'echo 2'
      dependencies: [task_1]
    task_3:
      operator: airflow.operators.bash_operator.BashOperator
      bash_command: 'echo 3'
      dependencies: [task_1]
然后,在您的Airflow环境中的DAGs文件夹中,您需要创建一个这样的Python文件
from airflow import DAG
import dagfactory
dag_factory = dagfactory.DagFactory("/path/to/dags/config_file.yml")
dag_factory.clean_dags(globals())
dag_factory.generate_dags(globals())
这个DAG将在Airflow中生成并准备好运行!
如果您有多个配置文件,可以像这样导入它们
# 'airflow' word is required for the dagbag to parse this file
from dagfactory import load_yaml_dags
load_yaml_dags(globals_dict=globals(), suffix=['dag.yaml'])
注意
HttpSensor(自0.10.0版本起)
包airflow.sensors.http_sensor与所有支持的Airflow版本兼容。在Airflow 2.0+中,可以在操作符值中使用新的包名:airflow.providers.http.sensors.http
以下示例展示了在Python文件中response_check逻辑
task_2:
      operator: airflow.sensors.http_sensor.HttpSensor
      http_conn_id: 'test-http'
      method: 'GET'
      response_check_name: check_sensor
      response_check_file: /path/to/example1/http_conn.py
      dependencies: [task_1]
response_check逻辑也可以作为lambda提供
task_2:
      operator: airflow.sensors.http_sensor.HttpSensor
      http_conn_id: 'test-http'
      method: 'GET'
      response_check_lambda: 'lambda response: "ok" in reponse.text'
      dependencies: [task_1]
优势
- 无需了解Python即可构建DAG
- 无需学习Airflow原语即可构建DAG
- 避免重复代码
- 每个人都喜欢YAML! ;)
贡献
欢迎贡献力量!只需提交Pull Request或Github Issue。
项目详情
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         dag-factory-0.19.0.tar.gz  (16.2 kB 查看散列)
      
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         dag_factory-0.19.0-py2.py3-none-any.whl  (17.0 kB 查看散列)