Estate Fetch

Estate Fetch is a comprehensive full-stack educational web application designed to assist users in efficiently discovering real estate deals and listings. This innovative platform seamlessly combines both frontend and backend functionalities, all housed within a single repository.

Table of Contents

• API Routes
• Features
• Tech Stack
• Known Limitations

🚀 Getting Started

You can access the deployed application version by clicking here: Estate Fetch

If you wish to run Estate Fetch locally, follow these steps:

Frontend (Angular)

1. Open a terminal in the root of the project and navigate to the frontend folder, where the frontend code is located.

   cd frontend
   

   cd estate-fetch
   

2. Install the required dependencies by running the following command:

   npm install
   

3. Start the Angular development server using the following command:

   ng serve
   

4. Open your web browser and go to http://localhost:4200/ to access the frontend of the application.

Backend (Express & Node.js)

1. Open a separate terminal in the root of the project and navigate to the backend folder, where the backend code is located.

   cd backend
   

2. Install the required dependencies by running the following command:

   npm install
   

3. Start the server using the following command:

   npm start
   

4. The backend server will start and be accessible at http://localhost:8000/.

MongoDB Atlas Database

• Estate Fetch utilizes MongoDB Atlas, a cloud-based database service, to store and retrieve the scraped real estate data.

• Currently using a free M0 512 MB cluster provided by MongoDB Atlas to host the database. This cluster offers a cost-effective solution for the project's needs.

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🌐 Backend API Routes

Here are all of the available API routes for interacting with the backend server:

Route	Description	Method	Headers	Parameters / Request Body
/	Welcome message	GET	None	None
/api/scrape	Scrape and save data to DB (protected route)	GET	x-secret-token	None
/api/estates	Get all estates	GET	None	None
/api/estates/search	Search all estates	GET	None	None
/api/estates/:id	Get estate by ID	GET	None	None

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🔑 Features

Backend Functionality

• The backend scrapes data from imot.bg and saves it to MongoDB Atlas.
• Data is processed and stored, including property details and realtor information.
• The backend serves as a central data repository for the frontend.

Local Scraper Setup

To run the scraper locally, follow these steps:

1. Copy the contents of the .env.example file to a new file named .env in the backend directory.

2. Set your MongoDB connection string in the MONGODB_URL variable.

3. Customize the SECRET_TOKEN in the .env file. This token is used to authenticate requests to initiate the scraping process.

4. Open your terminal and navigate to the backend directory.

5. Run the following commands to install dependencies and start the local server:

   npm install
   npm run dev
   

6. Once the server is running and your database is connected, make a GET request to http://localhost:8000/api/scrape with your chosen API client (e.g., cURL or Postman) and include the SECRET_TOKEN in the request header. Ensure that the header is named x-secret-token.

Scraper Demo

https://github.com/user-attachments/assets/f1b4bbc7-7b32-43f6-bda7-12a929476416

Note: The scraping functionality is designed for personal and educational use. Please be responsible and do not misuse it. Be mindful of the legal considerations associated with web scraping.

Frontend Functionality

• Users can perform partial searches by keywords that match the title, location, and description fields to find listings matching their criteria.
• The frontend displays property details, including keen-slider image carousel, ng-gallery for image lightbox functionality, title, price, location, description, floor, construction type, square meters price, area, and realtor information.
• Catalog page displays property previews, including thumbnails, prices, descriptions, and buttons for viewing details/accessing external listings.

Search Filters

• Price Range:

  • Finds properties within the specified minimum and maximum price range (can be used separately or together).

• Location:

  • Provides a list of cities across Bulgaria to filter by.

• Construction Type:

  • Filters properties based on available construction types.

• Area Size:

  • Defines the minimum area size of properties.

• Number of Rooms:

  • Specifies the number of rooms.

• Apply / Reset Filters:

  • Click the Apply button to activate your selected filters or use the Reset button to clear all filters.

Sort Options

• Relevance:

  • Properties based on relevance.

• Price Ascending:

  • Properties from the lowest to the highest price.

• Price Descending:

  • Properties from the highest to the lowest price.

• Newest Listings:

  • Latest property listings.

• Oldest Listings:

  • Earliest property listings.

• Most Views:

  • Properties based on the highest number of views.

• Least Views:

  • Properties based on the lowest number of views.

The chosen filters/sorting preferences are encoded in the URL, allowing for sharing of searches with others.

Home Page

• Home page includes a hero section, scraper overview, features section, frequently asked questions (FAQ), and data origins section.
• It provides an informative and engaging landing experience for users.

User-Friendly Experience

• No registration or payment is required to access all features.
• The app is designed to be user-friendly and intuitive for quick real estate searches.
• It is fully responsive across all devices, thanks to Tailwind CSS.
• Optimized for dark mode using darkreader, with a switch available in the header to toggle between dark and light modes.

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📦 Tech Stack and Tools

The app relies on the following technologies and libraries:

• Frontend: Angular
• HTTP Requests: Angular’s HttpClient
• Image Carousel: keen-slider
• Image Lightbox: ng-gallery
• Styling: Tailwind CSS
• Dark Mode: darkreader
• Backend: Node.js with Express
• Web Scraping: Puppeteer and Cheerio
• CORS Handling: cors
• Data Storage: MongoDB Atlas
• Deployment Platform: Vercel

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❗ Known Limitations

1. Monolithic Architecture: The application follows a monolithic architecture where the frontend and backend are tightly coupled within the same repository.

2. Limited Data Sources: Currently, the data scraping functionality is limited to imot.bg. Data sources will be expanded to provide a more comprehensive real estate dataset.

3. Browser Compatibility: Estate Fetch is optimized for modern web browsers. While it should work well in most browsers, some features may not function as expected in older or less common browsers.

4. User Profiles and Authentication: User profiles and authentication features are not yet implemented in the application. Users can access all features without the need for registration.

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