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Realtor.com Scraper Demo with Retool and Node.js

Welcome to my demonstration of the Realtor.com Scraper application, developed as part of a take-home assessment for a job application. This project combines Node.js, Express, Cheerio, and Retool to create a powerful web scraping tool for real estate listings. In this video, I'll walk you through the app's features, the technology stack used, and provide an in-depth look at the implementation process. Repository: GitHub Repository App Link: Realtor.com Scraper App Overview: This project demonstrates a web scraping API built with Node.js, Express, and Cheerio, integrated into a Retool application. It scrapes property listings from Realtor.com based on user-defined criteria and displays the results in a responsive Retool table. This demo showcases my ability to handle high-level goals and make key decisions independently. Key Features: Search Properties by Zip Code: Users can enter a zip code to retrieve property listings. Filter Results: Filter listings by price range, number of bedrooms, and number of bathrooms. Responsive Display: Results are shown in a user-friendly and responsive Retool table. Technology Stack: Backend: Node.js, Express, Cheerio, ScraperAPI (for proxy handling) Frontend: Retool Implementation Walkthrough: Backend Development: Node.js and Express: Set up a server to handle API requests. Cheerio: Used for parsing HTML and extracting data from Realtor.com. ScraperAPI: Managed proxy handling to avoid blocking during web scraping. API Endpoint: Created an endpoint to scrape listings based on user input (zip code, price range, bed count, and bath count). Frontend Integration: Retool Setup: Resource Creation: Connected Retool to the Heroku-deployed backend. Input Components: Added text and number input fields for search criteria (zip code, min/max price, min/max beds, min/max baths). Query Configuration: Set up a GET request to fetch data from the API. Table Component: Configured to display the scraped listings dynamically. Search Button: Added functionality to trigger the search query and update the table with new data. Why This Approach? Simplicity and Efficiency: Using Node.js and Express for the backend ensures a lightweight and efficient server, while Cheerio provides powerful HTML parsing capabilities. Scalability: ScraperAPI facilitates scalable and reliable web scraping by handling proxy management. Ease of Use: Retool's user-friendly interface and powerful component library allowed for rapid development and deployment of the frontend. Conclusion: In this video, you'll see how to set up, deploy, and use the Realtor.com Scraper application. I'll also explain the rationale behind the technological choices and implementation steps, demonstrating my ability to work independently and deliver a functional and polished product.