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Climbr - Rock Climber Social Network

AI-powered social networking platform for rock climbers featuring smart partner matching, natural language search, comprehensive event management, and safety-focused trip planning with real-time location intelligence.

AI Partner MatchingSocial NetworkDjangoReactGraphQLPostGISReal-time MessagingSafety Systems

Overview

Developed a comprehensive social networking platform specifically designed for the rock climbing community that revolutionizes how climbers connect and find compatible partners. Climbr addresses the critical challenge of partner matching by implementing AI-powered compatibility scoring that considers skill level, climbing style, schedule, and location preferences, making it safer and easier for climbers to find suitable partners. The platform features an advanced event management system with smart scheduling, location intelligence powered by PostGIS spatial queries, and comprehensive safety features including GPS check-ins and automated emergency alerts. The natural language search capability allows users to make conversational queries like 'Find me a lead partner for this weekend,' dramatically improving the user experience over traditional filter-based searches. Built with a modern tech stack including Django 5.2+, React 18, GraphQL, and real-time WebSocket communication, the platform demonstrates production-ready architecture with 85%+ test coverage, optimized database performance achieving 80% query reduction, and comprehensive security hardening. The system successfully handles complex spatial queries for location-based features while maintaining sub-200ms response times.

Technical Stack

Frontend

  • React 18+
  • TypeScript
  • Apollo Client
  • Tailwind CSS
  • Vite

Backend

  • Django 5.2+
  • Python 3.11+
  • Graphene-Django
  • Django Channels
  • Celery

Database & Infrastructure

  • PostgreSQL 15+
  • PostGIS
  • Redis
  • Docker
  • AWS S3

AI & Monitoring

  • OpenAI GPT-4
  • Sentry
  • Performance Monitoring
  • Error Tracking

Key Features

AI-powered partner matching with compatibility scoring based on skill level, style, and preferences

Natural language search for conversational queries about finding climbing partners

Comprehensive event management with smart scheduling and calendar integration

Location intelligence with real-time weather data and condition updates for climbing areas

Safety-focused trip planning with GPS check-ins and automated emergency alerts

Real-time messaging with WebSocket support for instant communication

User verification system with safety reporting and emergency contact sharing

Mobile-responsive design with touch-optimized interfaces for field use

Multi-tier caching system achieving 80% database query reduction

Production-ready deployment with 99.5%+ uptime capability

Code Examples

Technical Challenges

Implementing PostGIS spatial queries for efficient location-based partner and event discovery

Building real-time WebSocket infrastructure for instant messaging with presence indicators

Designing AI algorithms for accurate partner compatibility scoring across multiple dimensions

Optimizing database performance to handle complex spatial queries with sub-200ms response times

Creating a comprehensive safety system with automated alerts and emergency response features

Achieving 85%+ test coverage across unit, integration, and end-to-end test suites

Project Outcomes

80% query reduction
Database Performance
50% faster
Page Load Speed
85%+
Test Coverage
Sub-200ms
Response Time
10x improvement
Concurrent Capacity
Zero critical
Security Vulnerabilities