OSS_Dev_Analytics

Helping open-source contributors understand the health and efficiency of their communities through data-driven insights.

Overview

OSS_Dev_Analytics provides a centralized dashboard for the Open Source with SLU community. We transform raw GitHub activity into actionable metrics, helping maintainers and contributors identify bottlenecks and celebrate progress.

Tech Stack

• Backend: Python 3.x, Pandas (Data processing), PyGithub (GitHub API Wrapper).
• Frontend: React.js, Vite, Tailwind CSS.
• Data Pipeline: Sprint-based filtering and JSON-structured analytics.

Project Architecture

• Data Acquisition: Python scripts fetch data from GitHub via the REST API.
• Sprint Filtering: Activity is categorized into predefined two-week sprints.
• Preprocessing: Pandas is used to calculate "Time to Merge," "Lead Time," and "Velocity."
• Visualization: A React + Vite frontend consumes the processed JSON to render interactive charts.

🤝 Getting Started

Are you interested in contributing to our organization-wide analytics?

1. Check out our Onboarding Document.
2. Join the conversation in the #oss-dev-analytics Slack channel.
3. Look for "Good First Issues" in our repository!

Communication:

All communication is held via the

OSS_Dev_Analytics Slack group chat: https://oss-slu.slack.com/archives/C09C1AQ181L

and

OS SLU Slack: