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PropXml.com

XML Data Feed Generator for Real Estate Listings

Project Overview

SaaS application that automates the conversion of real estate property listings into XML data feeds, optimized for platforms like Zillow, Facebook, and Realtor.com. This tool streamlines the entire process—from data extraction via web crawling, through data refinement in an intuitive dashboard, to the generation of XML feeds in multiple industry-standard formats.

Capable of handling large-scale data efficiently, the application is designed with scalability and adaptability in mind, ensuring quick processing and compliance with evolving XML standards. Ideal for real estate agents and companies looking to automate their data workflow and reduce manual effort.

Tools Used

Laravel PHP Python JavaScript Alpine.js MySQL HTML Tailwind CSS GitHub Actions

Project Details

  • Designed and implemented the database schema using MySQL, ensuring optimal normalization and indexing for performance.
  • Developed the backend using Laravel and the frontend with Blade templates combined with Alpine.js for user interactivity and dynamic content rendering.
  • Wrote custom web scrapers in Python using Selenium to extract property data from websites, handling various website structures and ensuring data accuracy.
  • Set up a CI/CD pipeline for automatic deployment using GitHub Actions to streamline updates and ensure continuous delivery.
  • Implemented a user interface for users to review and refine imported listings before generating XML feeds, ensuring user control and customization.
  • Integrated validation mechanisms to check data consistency and ensure compatibility with XML feed standards.
  • Deployed the application on an AWS EC2 LAMP stack with proper security configurations, including SSL/TLS encryption and firewall rules.
  • Optimized server performance to handle large-scale property data efficiently, ensuring high availability and low latency.
  • Wrote automated unit and feature tests using PHPUnit to ensure platform reliability and catch potential regressions.
  • Implemented logging and monitoring for key application metrics to identify and resolve issues proactively.
  • Ensured the application adhered to industry security standards, including secure data storage and protection against common web vulnerabilities (e.g., SQL injection, XSS).
  • Documented the codebase and deployment process to enable easier maintenance and onboarding for future developers.
  • Conducted end-to-end testing and quality assurance to verify functionality across different use cases and platforms.