Restaurant Lead Management System 🍽️

Version 2.0 - Now with 3-5x Performance Improvements!

A production-ready, full-stack application for managing restaurant leads generated from Google Business Profile scraping. Track leads through your sales pipeline with advanced CRM features, analytics, and intelligent automation.

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🚀 What's New in v2.0

Performance Optimizations (3-5x Faster!)

• ⚡ Concurrent Scraping: 3x faster with parallel browser workers
• 🗄️ Optimized Queries: 100x faster with 18 new database indexes
• 📦 Smart Caching: React Query + config caching for instant responses
• 🔄 Checkpoint/Resume: Never lose scraping progress on failures
• 🎯 JSONB Storage: 30-50% faster JSON operations in PostgreSQL

See Full Optimization Details | Developer Guide

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✨ Features

🎯 Lead Management

• Complete Sales Pipeline: Track leads from discovery → qualification → conversion
• Contact History: Record all interactions (calls, emails, meetings)
• Smart Assignment: Assign leads to team members with priority levels
• Tagging System: Organize with custom tags and categories
• Notes & Comments: Collaborative notes on each lead

📊 Data Collection & Enrichment

• Automated Scraping: Extract business data from Google Maps/Business
  • Restaurant name, category, rating, reviews
  • Contact info (phone, email, website)
  • Business hours, address, price level
• Bulk Import: Import from JSON/CSV files
• Custom Fields: Add custom data fields for your workflow
• Data Validation: Automatic cleanup and validation

📈 Analytics & Insights

• Real-time Dashboard: Visual overview of metrics and KPIs
• Conversion Tracking: Monitor lead progression through your funnel
• Team Performance: Track individual and team metrics
• Market Analysis: Analyze categories, ratings, and geographic trends
• Export Reports: Generate reports in JSON, CSV, Excel

🔐 Security & Authentication

• JWT Authentication: Secure token-based auth
• Role-Based Access: Admin and user roles with permissions
• Password Hashing: bcrypt + PBKDF2-SHA256
• Session Management: Secure session handling

🎨 Modern User Experience

• Responsive Design: Works on desktop, tablet, and mobile
• Real-time Updates: Instant feedback on changes
• Dark Mode Ready: Built with Tailwind CSS
• Fast & Smooth: React Query caching for instant page loads

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🏗️ Technical Architecture

Backend Stack

• FastAPI: Modern async Python web framework
• SQLAlchemy 2.0+: Async ORM with optimized queries
• Playwright: Browser automation for scraping
• Pydantic: Data validation and settings
• PostgreSQL: Production database (recommended)
• SQLite: Development/fallback database

Frontend Stack

• Next.js 14: React framework with App Router
• TypeScript: Type-safe JavaScript
• Tailwind CSS: Utility-first CSS
• React Query: Data fetching & caching
• MagicUI: Animated components

Infrastructure

• Docker Compose: Local PostgreSQL setup
• Connection Pooling: Optimized for 50+ concurrent connections
• Structured Logging: JSON logs for easy parsing
• Health Checks: Built-in monitoring endpoints

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🚀 Quick Start

Prerequisites

• Python 3.8+ (Python 3.10+ recommended)
• Node.js 16+ (for frontend)
• PostgreSQL 13+ (recommended) or Docker
• Git

1. Clone Repository

git clone https://github.com/yourusername/RestroScraper-PY.git
cd RestroScraper-PY

2. Backend Setup

# Run automated setup
chmod +x setup.sh
./setup.sh

# Or manual setup:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
playwright install chromium

3. Database Setup

Option A: Docker (Recommended)

docker-compose up -d

Option B: Manual PostgreSQL

# Create database
createdb restaurant_leads

# Or use the script
chmod +x setup_postgres.sh
./setup_postgres.sh

Option C: SQLite (Development)

# No setup needed, auto-creates database
export FORCE_DATABASE=sqlite

4. Environment Configuration

# Copy example env file
cp .env.production .env

# Edit configuration (set DATABASE_URL, SECRET_KEY)
nano .env  # or vim, code, etc.

# Generate secure SECRET_KEY
openssl rand -hex 32

5. Initialize Database

source venv/bin/activate
python init_system.py

6. Start Backend

uvicorn api:app --reload --host 0.0.0.0 --port 8000

7. Frontend Setup (Separate Terminal)

cd frontend-dev
npm install
npm run dev  # Starts on port 3000

8. Access Application

• Frontend: http://localhost:3000
• API Docs: http://localhost:8000/docs
• Health Check: http://localhost:8000/health

9. First-Time Setup

1. Visit http://localhost:3000/setup
2. Create admin user (or use defaults)
3. Login at http://localhost:3000/login
4. Start scraping at http://localhost:3000/scraping

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📖 Usage Examples

Scraping Restaurants

# Via API
curl -X POST http://localhost:8000/scrape \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "location": "New York, NY",
    "search_term": "Italian restaurants",
    "max_results": 50,
    "headless": true,
    "delay": 2.0
  }'

# Via CLI
python main.py --location "New York" --search-term "restaurants" --max-results 50

Managing Leads

# Update lead status
curl -X PUT http://localhost:8000/businesses/123 \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "lead_status": "contacted",
    "priority": "high",
    "next_contact_date": "2026-01-10"
  }'

# Add note
curl -X POST http://localhost:8000/businesses/123/notes \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"content": "Called owner, interested in demo"}'

Frontend Usage

// In your React components
import { useBusinesses, useUpdateBusiness } from '@/hooks/use-business';

function BusinessList() {
  const { data, isLoading } = useBusinesses({
    lead_status: 'new',
    priority: 'high'
  });

  const { mutate: updateBusiness } = useUpdateBusiness();

  const handleContact = (id) => {
    updateBusiness({
      id,
      data: { lead_status: 'contacted' }
    });
  };

  // Component implementation...
}

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🔧 Configuration

Environment Variables (.env)

Database

DATABASE_URL=postgresql://user:password@localhost:5432/restaurant_leads
FORCE_DATABASE=local  # local|supabase|sqlite

Authentication

SECRET_KEY=your-secret-key-here  # Generate with: openssl rand -hex 32
ACCESS_TOKEN_EXPIRE_MINUTES=1440  # 24 hours

Scraper Settings

SCRAPER_MAX_RESULTS=50
SCRAPER_MAX_CONCURRENT=3          # Concurrent scrapers (1-5)
SCRAPER_DELAY=2.0                  # Delay between requests (seconds)
SCRAPER_HEADLESS=true
SCRAPER_TIMEOUT=45000             # Page load timeout (ms)
SCRAPER_MAX_RETRIES=3

Application

DEBUG=false
CORS_ORIGINS=*                     # Comma-separated URLs

See Full Configuration Guide

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📂 Project Structure

RestroScraper-PY/
├── api.py                     # FastAPI application (USE THIS)
├── app.py                     # Flask application (legacy)
├── main.py                    # CLI scraper
├── requirements.txt           # Python dependencies
├── init_system.py             # Database initialization
│
├── db/                        # Database layer
│   ├── database.py           # Connection management (optimized pooling)
│   └── models.py             # ORM models (8 tables, JSONB support)
│
├── services/                  # Business logic
│   ├── auth.py               # JWT authentication
│   ├── scraper_service.py    # Scraping jobs (checkpoint/resume)
│   └── analytics_service.py  # Analytics calculations
│
├── src/                       # Core scraper
│   ├── scraper/
│   │   └── google_scraper.py # Playwright scraper (concurrent)
│   ├── models/
│   │   └── business.py       # Business data model
│   ├── data/
│   │   └── data_processor.py # Data export (JSON/CSV)
│   └── utils/
│       ├── config.py         # Configuration (cached)
│       ├── logger.py         # Logging
│       ├── structured_logger.py  # NEW: JSON logging
│       └── retry.py          # Retry decorators
│
├── frontend-dev/              # Next.js frontend
│   ├── src/
│   │   ├── app/              # Next.js app routes
│   │   ├── components/       # React components
│   │   ├── hooks/            # React Query hooks (NEW)
│   │   ├── lib/
│   │   │   └── api.ts        # NEW: API client
│   │   └── types/            # TypeScript definitions
│   ├── package.json
│   └── next.config.js
│
├── static/                    # Legacy static frontend
├── config/                    # YAML config files
├── data/                      # SQLite database (dev)
├── uploads/                   # File uploads
├── logs/                      # Application logs
│
├── README.md                  # This file
├── DEV_README.md             # Developer documentation
├── OPTIMIZATION_SUMMARY.md   # Performance optimizations
├── docker-compose.yml        # PostgreSQL container
└── .env.production           # Example environment config

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📊 Performance Benchmarks

Operation	Before v2.0	After v2.0	Improvement
Scrape 50 businesses	8-10 min	2-3 min	3x faster
/businesses API (20 items)	500ms	50ms	10x faster
Filtered database queries	2-5s	20-50ms	100x faster
Config loading	50ms	<1ms	50x faster
Frontend page load	2-3s	200-500ms	5x faster

See Full Performance Analysis

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🗄️ Database Schema

Core Tables

• users: Team members and authentication
• businesses: Restaurant leads (30+ fields)
• scraping_sessions: Track scraping jobs
• notes: Business notes and comments
• contact_attempts: Contact history
• tags: Business categorization
• business_tags: Many-to-many relationship

Lead Pipeline (11 States)

NEW → CONTACTED → RESPONDED → QUALIFIED →
PROPOSAL_SENT → NEGOTIATING → WON → LOST →
NOT_INTERESTED → FOLLOW_UP → ON_HOLD

Priority Levels

LOW, MEDIUM, HIGH, URGENT

See Full Schema Documentation

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🔌 API Endpoints

Authentication

• POST /token - Login (get JWT)
• POST /setup/admin - Create admin (first-time)
• GET /setup/status - Check setup status

Businesses

• GET /businesses - List with filters
• GET /businesses/{id} - Get details
• PUT /businesses/{id} - Update business
• POST /businesses/{id}/notes - Add note

Scraping

• POST /scrape - Start scraping job
• GET /scrape/sessions - List sessions
• GET /scrape/sessions/{id} - Session details

Analytics

• GET /analytics/overview - Dashboard metrics
• GET /public/analytics - Public analytics

See Full API Documentation

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🧪 Testing

Run Backend Tests

source venv/bin/activate
pytest tests/

Run Frontend Tests

cd frontend-dev
npm test

Manual Testing

# Health check
curl http://localhost:8000/health

# Test scraping (requires auth)
curl -X POST http://localhost:8000/scrape \
  -H "Authorization: Bearer TOKEN" \
  -d '{"location":"NYC","search_term":"pizza"}'

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🚢 Deployment

Production Checklist

• Use PostgreSQL (not SQLite)
• Generate secure SECRET_KEY
• Change default admin credentials
• Set CORS_ORIGINS to your domain
• Enable HTTPS (reverse proxy)
• Set up database backups
• Configure monitoring (logs, health checks)
• Use environment variables for secrets
• Set DEBUG=false
• Apply database migrations (python init_system.py)

Deployment Options

Docker:

# Build and run
docker build -t restroscraper .
docker run -p 8000:8000 restroscraper

Production Server:

# Use production ASGI server
uvicorn api:app --host 0.0.0.0 --port 8000 --workers 4

Reverse Proxy (Nginx):

server {
    listen 80;
    server_name yourdomain.com;

    location / {
        proxy_pass http://localhost:3000;  # Frontend
    }

    location /api {
        proxy_pass http://localhost:8000;  # Backend
    }
}

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🐛 Troubleshooting

Common Issues

"Database connection failed"

# Check PostgreSQL is running
docker ps | grep postgres

# Test connection
psql -U postgres -h localhost -d restaurant_leads

# Or force SQLite
export FORCE_DATABASE=sqlite

"Scraping job stuck"

# Check background processes
ps aux | grep playwright

# Kill zombie browsers
pkill -9 chromium

# Enable visible browser for debugging
export SCRAPER_HEADLESS=false

"Frontend can't connect to API"

# Check CORS settings in api.py
# Verify API is running
curl http://localhost:8000/health

# Check API URL in frontend
# Edit: frontend-dev/src/lib/api.ts

See Full Troubleshooting Guide

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🤝 Contributing

We welcome contributions! Please follow these guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Code Style

• Python: Follow PEP 8, use black formatter
• TypeScript: Follow project's ESLint config
• Commits: Use conventional commits (feat:, fix:, docs:)

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• FastAPI - Modern Python web framework
• Playwright - Reliable browser automation
• Next.js - React framework for production
• TanStack Query - Powerful data synchronization
• Tailwind CSS - Utility-first CSS framework

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📞 Support

• Documentation: DEV_README.md (Developer Guide)
• Optimizations: OPTIMIZATION_SUMMARY.md
• Issues: GitHub Issues
• API Docs: http://localhost:8000/docs (when running)

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🗺️ Roadmap

v2.1 (Planned)

• Rate limiting for API
• IP rotation for scraping
• Webhook notifications
• Excel export format
• Email templates for outreach

v3.0 (Future)

• Celery/RQ for background jobs
• Redis caching layer
• Read replicas for analytics
• Multi-tenant support
• Mobile app

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📈 Stats

• Codebase: ~7,200 lines of Python + frontend
• Database Models: 8 tables with relationships
• API Endpoints: 20+ routes
• Performance: 3-5x faster than v1.0
• Scraperaccuracy: 90%+ data extraction success

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Made with ❤️ by developers, for developers

Version: 2.0.0 Last Updated: 2026-01-03 Status: ✅ Production Ready