6.6 KiB
6.6 KiB
Dubai DLD Analytics API - Implementation Summary
✅ Completed Implementation
1. Gap Analysis
- ✅ Analyzed all JSON data files (transactions, rents, projects, buildings, lands, valuations, brokers)
- ✅ Mapped requirements to available data
- ✅ Identified minor gaps (non-blocking)
- ✅ Verified data quality and coverage
2. Project Structure
dubai-dld-analytics/
├── src/
│ ├── app.js # Main Express application
│ ├── models/
│ │ └── database.js # MySQL connection pool
│ ├── services/
│ │ ├── nlpService.js # NLP query parsing
│ │ ├── sqlGenerator.js # SQL query generation
│ │ └── chartFormatter.js # Chart.js data formatting
│ ├── routes/
│ │ ├── api.js # API endpoints
│ │ └── static.js # Static file serving
│ ├── middleware/
│ │ └── validation.js # Request validation
│ └── utils/
│ ├── dateUtils.js # Date utilities
│ └── textProcessor.js # Text processing utilities
├── public/
│ └── index.html # Frontend demo dashboard
├── tests/
│ └── api.test.js # API tests
├── package.json # Dependencies
├── 2.sql # Database schema
├── README.md # Full documentation
├── QUICK_START.md # Quick start guide
├── setup.sh # Automated setup script
└── .gitignore # Git ignore rules
3. Core Services
NLP Service (nlpService.js)
- ✅ Natural language query parsing using Natural.js
- ✅ Extract time periods (months, weeks, years)
- ✅ Extract Dubai area names (from actual data)
- ✅ Extract property types
- ✅ Extract room types (BHK)
- ✅ Intent classification (trend, compare, average, summary)
- ✅ Dubai-specific terminology support
Available Endpoints
Main Query Endpoint
POST /api/query
{
"query": "Give me the last 6 months rental price trend for Business Bay"
}
Predefined Endpoints
GET /api/queries/rental-trend/:area- Rental trendsGET /api/queries/top-areas- Top performing areasGET /api/queries/project-summary- Project summariesGET /api/queries/commercial-leasing- Commercial analysisGET /api/queries/residential-leasing- Residential analysis
Utility Endpoints
GET /health- Health checkGET /api/database/info- Database statisticsGET /api/queries/available- Available query typesGET /- Interactive dashboard
Chart.js Integration
The API returns data in Chart.js format:
- Line Charts: Time series trends
- Bar Charts: Area comparisons
- Pie Charts: Distribution analysis
- Cards: Summary statistics
Example Response
{
"success": true,
"data": {
"text": "Rental price trend for Business Bay",
"visualizations": [
{
"type": "line",
"title": "Monthly Rental Price Trend",
"data": {
"labels": ["2024-01", "2024-02", "2024-03"],
"datasets": [{
"label": "Average Rental Price (AED)",
"data": [85000, 87000, 89000],
"borderColor": "rgb(75, 192, 192)",
"backgroundColor": "rgba(75, 192, 192, 0.2)"
}]
}
}
],
"cards": [
{
"title": "Average Price",
"value": "92,500 AED",
"subtitle": "Last 6 months",
"trend起了+15.3%"
}
],
"sql_queries": ["SELECT ..."]
}
}
Supported Queries
Rental Analysis
- ✅ "Give me the last 6 months rental price trend for Business Bay"
- ✅ "Show me rental prices for apartments"
- ✅ "What's the average rental price in Downtown?"
Project Analysis
- ✅ "Brief about the Project"
- ✅ "List of fast moving projects in last 6 months"
- ✅ "Which areas have off-plan projects?"
Area Performance
- ✅ "Which area is having more rental transactions?"
- ✅ "Top 5 areas for Commercial leasing and why?"
- ✅ "Top 5 areas for Residential leasing and why?"
- ✅ "Avg price of 3BHK apartment by area"
Installation & Setup
Quick Setup
# 1. Install dependencies
npm install
# 2. Configure database (.env)
DB_HOST=localhost
DB_NAME=dubai_dld
DB_USER=root
DB_PASSWORD=your_password
# 3. Import database
mysql -u root -p < 2.sql
# 4. Start server
npm run dev
Or use the automated setup script:
chmod +x setup.sh
./setup.sh
Testing
Manual Testing
# Health check
curl http://localhost:3000/health
# Custom query
curl -X POST http://localhost:3000/api/query \
-H "Content-Type: application/json" \
-d '{"query": "Give me the last 6 months rental price trend for Business Bay"}'
# Predefined query
curl http://localhost:3000/api/queries/top-areas
Automated Tests
npm test
Features
✅ Implemented
- Natural language query processing
- Multiple query types (trend, compare, average, summary)
- Chart.js compatible responses
- Hardcoded SQL for all queries
- Dubai-specific area recognition
- Time period extraction
- Property type filtering
- Room type filtering (BHK)
- Predefined query endpoints
- Interactive dashboard
- Rate limiting
- Security headers
- Input validation
- Error handling
- Health checks
- Database statistics
- Automated setup script
Architecture
- Clean layered architecture
- Service-oriented design
- Middleware for validation and error handling
- Utility functions for common operations
- Database connection pooling
- RESTful API design
- Frontend-backend separation
Next Steps (Optional Enhancements)
Future Improvements
- Add Redis for caching
- Add authentication/authorization
- Add query history tracking
- Add more complex NLP patterns
- Add support for Arabic language
- Add real-time data updates
- Add export functionality (CSV, PDF)
- Add advanced filtering options
- Add drill-down capabilities
- Add comparison between areas
Documentation
- 📖 README.md: Complete documentation
- 🚀 QUICK_START.md: Quick start guide
- 💻 Code Comments: Inline documentation
- 🧪 Tests: API test suite
Support
For issues or questions:
- Check
README.mdfor detailed documentation - Review
QUICK_START.mdfor common issues - Check the console logs for error messages
- Verify database connection in
.env
License
MIT License - See package.json for details.
Status: ✅ Fully functional and ready to use Version: 1.0.0 Last Updated: 2024