WFIP (Web Feature Intelligence Platform)

Inspiration

The necessity of tools that make MDN Baseline data actionable during development, not after deployment.

What it does

Scans CSS/JavaScript code to detect 8 modern web features, calculates browser compatibility scores, and provides risk assessments with alternatives.

How we built it

Development approach: Research, Backend (Data models, Baseline data store, Feature detector, Risk scorer, FastAPI), Frontend (DashBoard layout, Chart.js, Feature table, Modal for feature details, Mock data for demo)

Challenges we ran into

Regex patterns miss complex usage patterns and slow scanning performance, Risk score interpretation, Mock Data vs. Real API, Multiple deployment targets (HTML demo, local server and Colab version), CORS issues in browser, Colab limitations with external servers.

Accomplishments that we're proud of

Technical: Feature detection, Risk scoring, Complete REST API, Dashboard, Multiple deployment options.

What we learned

Technical learnings: Baseline data structure, pattern recognition, API design, risk calculation, visualization Domain Learnings: Browser compatibility, developer workflows

What's next for WFIP (Web Feature Intelligence Platform)

Add 20+ more features, Replace mock data with real MDN API, Regex to AST parsing, VS Code Extension, AI recommendations.

Built With

• fastapi
• json
• mdn-bcd
• python
• react
• recharts
• tailwind-css
• uvicorn