NOTE: Unfortunately, I am not actively maintaining this repository anymore. Please use at your own risk. Feel free to contribute if you can. I would be more than happy to review any PR's. Thanks !

Airflow Backfill Plugin

Backfilling made easy. With UI built with Bootstrap 4, backfilling is just a piece of cake. No need to login in your Airflow Environment VM/Setup every time to run command line for backfill and clearing DAG runs. This plugin easily integrates with Airflow webserver and makes your tasks easier by giving you the same control as command line does. This plugin works with Python 3 and Airflow 1.10.3. Now supports RBAC as well.

How to Use

• Plugin is easily navigable from "Admin" menu link
• Enter your DAG name, start date, end date. Select whether you want to run backfill OR clear. You can also select "Run in Background", in case you want to just submit the job and close the backfill window. If "Run in background" is unchecked then you would be able to see realtime logs of the job you've submitted.
• History tab shows you jobs so far along with their last runtime

RBAC Support

RBAC support is added in this project, when you change rbac in [webserver] section, the plugin will auto switch between two mode.

Plugin Directory Structure

├── __init__.py
├── backfill
│   ├── __init__.py
│   ├── main.py
│   └── requirements.txt
└── templates
    └── backfill_page.html

• backfill folder contains main.py file. This contains the backend logic for the backfill plugin. For e.g. executing airflow CLI commands on user request
• template folder contains web page from which user runs/request backfill OR clear commands
• __init__.py file contains backfill plugin instantiation logic with Airflow webserver

Setup

1. Clone the repository in your system
2. Plugin configuration
   • If it's a fresh Airflow Environment, simple put the plugins folder inside your codebase and modify plugin_folder=<plugin_path> option in your airflow.cfg file.
   • If it's an existing Airflow Environment. Navigate to existing plugins folder in your code base. Extend your existing __init__.py file by __init__.py of this plugin.
3. There is one dependency for this plugin. Just run pip install shelljob in your Airflow Environment.
4. Set your Airflow home path in the main.py file and make sure the logs folder exists
5. All done ! Just restart your webserver and you are good to go.

Feels Awesome ! Start contributing.