GitHub Performance Dashboard

This project provides a dashboard for monitoring key statistics about branches and pull requests (PRs) across GitHub repositories within an organization. It collects data from GitHub, stores it in a local database, and visualizes trends over time.

Features

• Tracks the number of open branches.
• Calculates the average lifetime of branches (from creation to merge).
• Calculates the average lifetime of pull requests (from open to merge).
• Calculates the average time gap between branch creation and PR opening.
• Displays interactive plots of these statistics over time on a web-based dashboard.

Architecture

The project consists of two main components:

1. Data Collector: A Python script (src/data_collector.py) that periodically fetches data from the GitHub API and updates a SQLite database.
2. Dashboard: A Flask web application (src/dashboard.py) that reads data from the database, calculates statistics, and presents them on a dashboard using Plotly.

Getting Started

Prerequisites

• Docker: Ensure you have Docker installed on your system.
• GitHub Personal Access Token: Generate a GitHub Personal Access Token with the necessary permissions to access repository data (read access to repo).

Installation

1. Clone the repository:

   git clone https://your-repository-url.git

2. Set up environment variables:

   • Copy the .env.example file to .env.
   • Fill in the values for GITHUB_TOKEN (your GitHub Personal Access Token), ORG_NAME (your GitHub organization name), and REPOSITORIES (a comma-separated list of the repositories you want to track).

3. Start the application:

   docker-compose up -d --build

4. Access the dashboard:

   • Open your web browser and navigate to http://localhost:8080 (or your server's IP/domain if deployed).

Customization

• Statistics: You can modify the StatsCalculator class in src/database/stats.py to add or customize the statistics you want to track.
• Dashboard: The src/dashboard.py file and the src/templates/index.html template can be modified to change the appearance and functionality of the dashboard.

Deployment

• Docker: The provided Dockerfile and docker-compose.yml files are designed to make it easy to deploy the application using Docker.
• Production: For production deployment, consider using a production-grade WSGI server (e.g., Gunicorn) for the Flask app and configuring a process manager (e.g., Supervisor) to keep the containers running.

Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.

License

This project is licensed under the MIT License.