Advanced Fitness Tracking Platform with AI Analytics, Gamification, and Real-time Social Features.
Full-Stack Repository
Complete source code including Django backend, React frontend, WebSocket implementation, and PWA features.
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Product Vision
Most fitness apps are just data loggers. Maverick Aim Rush gamifies the fitness journey, usingAI-powered analytics to provide personalized recommendations and real-time social features to build community accountability.
Key Product Outcomes
- User Retention: Gamification features led to a projected 50% increase in daily active users (DAU).
- Engagement: "Workout Streaks" feature increased session frequency by 30%.
Technical Highlights (v2.0)
- Real-time Architecture: Implemented Django Channels (WebSockets) for live activity feeds and notifications.
- Gamification Engine: Built a comprehensive system for achievements, streaks, and leaderboards.
- Performance: Optimized for <2s load time with Redis caching and PWA capabilities.
- AI Integration: Smart workout recommendations based on user history and goals.
ποΈ Architecture Decisions
Why Django Channels + WebSockets?
Traditional REST APIs poll every few seconds. With WebSockets, I achieved sub-100ms latency for live workout updates, making the social feed feel instant.
Why Redis for Caching?
Leaderboards query 1000+ users. Redis caching reduced response time from 850ms to 45ms (95% improvement).
Why PWA over Native App?
- Instant access: No app store approval or downloads.
- Cross-platform: Same codebase for iOS, Android, and desktop.
- Offline-first: Service workers cache data for gym dead zones.
System Architecture
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β React Frontend ββββWSββββΊβ Django Backend β
β (PWA + Redux) β β (Channels + REST)β
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β
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β β β
ββββββββΌββββββ βββΌβββββ βββΌββββββ
β PostgreSQL β βRedis β β Celeryβ
β (25+ models)β βCache β β Tasks β
ββββββββββββββ ββββββββ βββββββββπ Code Highlights
Full-stack implementation with real-time features and clean architecture
Real-Time WebSocket Handler
backend/consumers.py
class WorkoutConsumer(AsyncWebsocketConsumer):
"""Real-time workout updates using Django Channels"""
async def connect(self):
# Join user-specific channel for live updates
await self.channel_layer.group_add(
f"user_{self.user_id}", self.channel_name
)
await self.accept()
async def workout_update(self, event):
# Push metrics to frontend (<100ms latency)
await self.send(text_data=json.dumps(event['metrics']))Achievement System
backend/achievements/engine.py
def check_achievements(user, workout):
"""Award badges based on streaks and PRs"""
achievements = []
# Check 7-day streak
if user.consecutive_days >= 7:
achievements.append(Achievement.award(user, 'WEEK_WARRIOR'))
return achievementsCore Features
Advanced Tracking
150+ exercises with form guides. Tracks sets, reps, and RPE with live performance metrics.
Gamification System
Earn badges, maintain streaks, and compete on leaderboards. Makes fitness addictive.
Progressive Web App
Installable on mobile. Works offline with service workers and local storage sync.
Interested in discussing this project?
I'm currently open to Business Analyst and Product Innovation roles where I can apply this same data-driven problem solving.