Project Overview
Problem: Django ORM is powerful but lacks intuitive tools for query optimization. Developers often struggle to debug inefficient queries or identify bottlenecks.
Solution: Extend Django Debug Toolbar with:
- Query Flow Visualization – Interactive graphs of query execution (using D3.js).
- Profiling Dashboard – Metrics like execution time, index usage, and join analysis.
- AI-Powered Hints – Automated suggestions (e.g., “Add an index to
user.email”).
Impact:
- Accelerate query debugging for Django developers.
- Reduce database bottlenecks in production apps.
Technical Approach
- Frontend: JavaScript (React/Vue) + D3.js for visualizations.
- Backend: Django Debug Toolbar integration (new panel).
- Database: PostgreSQL/MySQL (
EXPLAIN ANALYZE,SHOW PROFILE). - AI: Lightweight pre-trained models (scikit-learn?) for pattern detection.
Timeline
| Phase | Key Tasks | Duration |
|---|---|---|
| Community Bonding | Research, discuss design with mentors | 3 weeks |
| Phase 1 | Query visualization module | 6 weeks |
| Phase 2 | Profiling dashboard + Toolbar integration | 6 weeks |
| Phase 3 | AI recommendations + docs | 6 weeks |
| Final | Testing, polishing | 2 weeks |
Why Me?
- Built Django apps with complex queries (optimized via
EXPLAIN ANALYZE). - Contributed to open-source (GitHub: kamivinnu).
- Passionate about performance tooling.
Questions for the Community
- Would you find a query visualization tool useful in Django Debug Toolbar?
- Any specific pain points with query debugging I should prioritize?
- Suggestions for balancing AI hints vs. manual analysis?
Future Roadmap
- NoSQL support (MongoDB).
- Query rewriting for performance.
Links: