Skip to content

QUICK_START.md

Latest commit

 

History

History
239 lines (158 loc) · 4.12 KB

QUICK_START.md

File metadata and controls

239 lines (158 loc) · 4.12 KB
Raw

🚀 Wanna Fit - Quick Start Guide

⚡ Get Started in 5 Minutes

Prerequisites

  • Python 3.11+
  • Git
  • (Optional) Docker Desktop

🏃‍♂️ Option 1: Local Development (Recommended)

1. Clone and Setup

git clone https://github.com/TahaKhan998/wanna-fit.git
cd wanna-fit

2. Quick Setup (Windows)

# Run the automated setup script
.\scripts\setup-dev.ps1

3. Start Development Server

python run_dev.py

4. Access the Application

🐳 Option 2: Docker Development

1. Start All Services

docker-compose up -d

2. Access Services

3. Stop Services

docker-compose down

☸️ Option 3: Kubernetes Production

1. Prerequisites

  • Kubernetes cluster (minikube, EKS, GKE, AKS)
  • kubectl configured

2. Deploy Infrastructure

# Deploy storage
kubectl apply -f k8s/storage.yaml

# Deploy database and cache
kubectl apply -f k8s/postgres.yaml
kubectl apply -f k8s/redis.yaml
kubectl apply -f k8s/kafka.yaml

# Deploy monitoring
kubectl apply -f k8s/monitoring/

3. Deploy Application

# Deploy to production
.\scripts\deploy.ps1 -Environment production

# Or manually
kubectl apply -f k8s/production/

🎯 Key Features to Explore

1. User Management

  • Register new account
  • Complete profile setup
  • Set fitness goals

2. Nutrition Tracking

  • Log meals and foods
  • View nutritional analysis
  • Get ML-powered food recommendations

3. Workout Management

  • Create custom workouts
  • Log workout sessions
  • Track progress over time

4. Intelligent Planning

  • AI-generated meal plans
  • Personalized workout recommendations
  • Goal-based planning

5. Analytics & Insights

  • Dashboard with key metrics
  • Progress tracking
  • Performance analytics

🔧 Development Commands

Database Operations

# Run migrations
python manage.py migrate

# Create superuser
python manage.py createsuperuser

# Load sample data
python manage.py loaddata nutrition_data.csv

ML Operations

# Train ML models
python manage.py train_ml_model

# Generate recommendations
python manage.py generate_recommendations

Testing

# Run tests
python manage.py test

# Run with coverage
coverage run --source='.' manage.py test
coverage report

📊 Monitoring & Health Checks

Health Endpoints

  • Liveness: /health/live/ - Is the app running?
  • Readiness: /health/ready/ - Is the app ready to serve requests?
  • Health: /health/ - Comprehensive health check

Metrics

  • Prometheus: /metrics/ - Application metrics
  • Custom Metrics: User activity, ML performance, system health

🚨 Troubleshooting

Common Issues

Server Won't Start

# Check if port 8000 is in use
netstat -an | findstr :8000

# Kill process using port 8000
taskkill /PID <PID> /F

Database Issues

# Reset database
python manage.py flush

# Recreate migrations
python manage.py makemigrations
python manage.py migrate

Dependencies Issues

# Reinstall dependencies
pip install -r requirements.txt --force-reinstall

📚 Documentation

🎉 Success!

Your Wanna Fit application is now running with:

  • ✅ ML-powered recommendations
  • ✅ Real-time data processing
  • ✅ Comprehensive monitoring
  • ✅ Production-ready infrastructure
  • ✅ Enterprise-grade security

Ready to impress your supervisors! 🚀