🏠 Divar Real Estate Analyzer

A powerful web-based tool for analyzing Tehran real estate market data from Divar.ir

Discover market trends • Analyze property prices • Visualize data insights

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See online:

https://divarrealstatesinthesedays.netlify.app/

✨ Features

📊 Comprehensive Data Analysis

• Real-time property data processing
• Interactive filtering by date, district, and price ranges
• Advanced statistical metrics and market insights
• Trend analysis with growth calculations

📈 Rich Visualizations

• Time Series Charts: Track property listings over time
• Price Distribution: Compare average prices across districts
• Interactive Maps: Geographic visualization with Leaflet
• Statistical Dashboard: Key market indicators at a glance

🎯 Smart Filtering

• Date range selection with Persian calendar support
• District-based filtering (Districts 1, 2, 3, 6, 15)
• Real-time data updates
• Export filtered results to CSV

🌍 User Experience

• Responsive design for all devices
• Persian/Farsi number formatting
• Dark theme with modern UI
• Fast client-side processing

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🚀 Quick Start

🌐 Try Online

Visit the live demo: divarrealstatesinthesedays.netlify.app

💻 Local Development

Prerequisites:

• .NET 8 SDK
• Modern web browser

Installation:

# Clone the repository
git clone https://github.com/yourusername/divar-analyzer.git
cd divar-analyzer

# Navigate to backend
cd Backend/DivarAnalyzer

# Restore dependencies
dotnet restore

# Run the application
dotnet run

# Open browser
# Navigate to https://localhost:5001

Using Docker Compose

docker compose up --build

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📱 How to Use

1. Load Data

🎯 Click "Click to load sample data" to generate demo data
📁 Or upload your own CSV file with property listings

2. Apply Filters

📅 Set date ranges using the date pickers
🏘️ Select specific districts (1, 2, 3, 6, 15)
🔍 Filter by price ranges and property types

3. Analyze & Visualize

📊 Click "Analyze" to generate comprehensive analysis
📈 View interactive charts and market trends
🗺️ Explore geographic distribution on the map
📋 Review detailed statistics and insights

4. Export Results

💾 Download filtered data as CSV
📑 Generate detailed market reports
📊 Share analysis results

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🏗️ Architecture

Backend Stack

🎯 ASP.NET Core 8.0        # Web API Framework
📄 CsvHelper              # CSV Processing
🌐 AngleSharp             # Web Scraping
📊 System.Text.Json       # JSON Serialization
🗄️ Entity Framework       # Data Access (Future)

Frontend Stack

⚡ Vanilla JavaScript      # Core Logic
📊 Chart.js               # Interactive Charts
🗺️ Leaflet               # Interactive Maps
📄 PapaParse              # CSV Processing
🎨 Custom CSS             # Modern UI Design

Key Components

• DivarDataAnalyzer: Core analysis engine
• DivarScraper: Data collection service
• DivarController: RESTful API endpoints
• Interactive Dashboard: Real-time visualization

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🎯 API Reference

Core Endpoints

GET  /api/divar/sample-data?count=100

Generate sample real estate data for testing

POST /api/divar/analyze
Content-Type: application/json

{
  "data": [...],
  "fromDate": "2024-01-01",
  "toDate": "2024-12-31",
  "district": "all"
}

POST /api/divar/export-csv
Content-Type: application/json

[...propertyData]

Response Format

{
  "success": true,
  "data": {
    "rawData": [...],
    "aggregatedData": [...],
    "metrics": {
      "totalListings": 1250,
      "avgTotal": 15000000000,
      "avgSqm": 85000000
    },
    "insights": [...]
  },
  "message": "Analysis completed successfully"
}

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📊 Data Model

RealEstateData

public class RealEstateData
{
    public DateTime ScrapedDate { get; set; }
    public string District { get; set; }
    public int? Size { get; set; }
    public long? TotalPrice { get; set; }
    public long? PricePerSqm { get; set; }
    public double? Latitude { get; set; }
    public double? Longitude { get; set; }
    public string Title { get; set; }
    public int? Age { get; set; }
}

Supported Districts

• District 1: Shemiran (شمیران)
• District 2: Vanak (ونک)
• District 3: Zaferaniyeh (زعفرانیه)
• District 6: Yusefabad (یوسف‌آباد)
• District 15: Shahrak (شهرک)

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🔧 Configuration

Backend Settings (appsettings.json)

{
  "DivarScraper": {
    "RequestDelayMs": 2000,
    "MaxRetryAttempts": 3,
    "RateLimitPerMinute": 30
  },
  "DataAnalysis": {
    "MaxRecordsPerAnalysis": 50000,
    "DefaultSampleSize": 100,
    "BaselineDate": "2024-06-12"
  }
}

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🚀 Deployment

Frontend (Netlify)

The frontend is deployed on Netlify with automatic builds:

• Live URL: https://divarrealstatesinthesedays.netlify.app/
• Build Command: None (static files)
• Publish Directory: Frontend/

Backend Deployment Options

# Azure App Service
az webapp up --name divar-analyzer --resource-group myResourceGroup

# Docker
docker build -t divar-analyzer .
docker run -p 5000:5000 divar-analyzer

# Railway/Heroku
git push railway main

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📈 Features Roadmap

Phase 1 ✅

• Basic data analysis and visualization
• Interactive charts and maps
• CSV export functionality
• Responsive design

Phase 2

• Real-time data scraping
• Advanced filtering options
• Price prediction models
• Historical trend analysis

Phase 3

• User authentication
• Saved searches and alerts
• API rate limiting
• Chatbot using LLM Agent for asking about the infrmations
• Database integration

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🤝 Contributing

We welcome contributions! Here's how to get started:

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

Development Guidelines

• Follow C# coding conventions
• Write meaningful commit messages
• Add tests for new features
• Update documentation

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🙏 Acknowledgments

• Divar.ir
• Chart.js - Excellent charting library
• Leaflet - Open-source mapping solution
• OpenStreetMap - Map data provider
• Netlify - Frontend hosting platform

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📞 Support

• 🐛 Bug Reports: Create an Issue
• 💡 Feature Requests: Start a Discussion
• 📧 Email: [email protected]

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