airflow-embedash 0.2.0

Add embeded dashboars to Airflow

Airflow Embedash

A Python package for embedding dashboards in Apache Airflow UI. This plugin allows you to easily integrate Metabase, Datadog and Grafana dashboards into your Airflow environment, providing a seamless way to view data visualizations alongside your workflows.

Features

• Easy Dashboard Integration: Embed Metabase dashboards directly into Apache Airflow UI
• Flexible Configuration: Customize menu labels and authentication tokens
• Multiple Airflow Versions Support: Compatible with Airflow 2.x and 3.x
• Secure Access: Supports Metabase token-based authentication for private dashboards

Installation

Install the package using pip:

pip install airflow-embedash

Or in development mode:

pip install -e .

Usage

Basic Setup

1. Configure Metabase Settings: Set the required Airflow variables:

   • embeded_dashboards_metabase_token: Your Metabase API token for private dashboards

2. Configure Menu Label:

   • Default menu label is "Dashboards"
   • Override by setting the embeded_dashboards_menu_label environment variable

3. Add new dashboards

   • Go to settings menu and add new dashboard
   • Restart the service

Package Structure

airflow_embedash/
├── __init__.py          # Package initialization
├── plugin/              # Plugin implementation directory
│   ├── __init__.py      # Plugin entry point
│   ├── airflow2.py      # Airflow 2.x compatibility layer
│   └── templates/       # HTML templates for dashboard views
│       ├── add_dashboard.html  # Add dashboard form
│       ├── edit_dashboard.html # Edit dashboard form
│       ├── settings.html       # Settings view
│       ├── view_not_set_up.html # Not configured view
│       └── view.html          # Main dashboard view
└── plugin/__init__.py   # Plugin initialization

Development

To contribute to this project:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Ensure all tests pass:

   make test
   

5. Submit a pull request

Development Setup

The project includes development containers and Docker configurations:

1. Using Docker:

   docker-compose up -d
   

2. Local Development:

   • Install development dependencies: pip install -e ".[dev]"
   • Run tests: make test

Configuration Options

Environment Variables

Variable	Description	Required
embeded_dashboards_metabase_token	Metabase API token for private dashboards	Optional
embeded_dashboards_menu_label	Custom menu label in Airflow UI	Optional

Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Submit a pull request

License

This project is licensed under the MIT License.