Building an Efficient Web Scraping Application for Price Comparison Across Supermarkets

A sophisticated web scraping application has been developed that efficiently compares product prices across multiple supermarkets. This innovative solution combines several modern technologies to deliver accurate, up-to-date pricing information in a user-friendly interface.

Technology Stack

The application leverages a robust technology stack including:

• Node.js with Express for the backend infrastructure
• React for the responsive frontend interface
• PuPeteer for efficient web scraping capabilities
• Microsoft SQL Server for reliable data storage and management

How It Works

The scraping process begins when a user initiates it through the interface by clicking the “actualize” button. This action triggers the frontend to send a request to the backend, which then begins scraping product information from various supermarket websites. Once the scraping process is complete, the gathered information is inserted into the database and displayed in a filterable table.

To ensure data accuracy, each product listing includes a verification button labeled “Ver en el sitio.” Clicking this button redirects users to the original webpage from which the data was extracted, allowing for manual verification of the pricing information.

Database Structure

The application’s database consists of three primary tables:

1. Product Table: Stores all the scraped results, including current pricing data
2. Product Snow Table: Contains the source information for the scraper, including products and selectors that PuPeteer needs to retrieve information
3. Supermarkets Table: Stores information about the various supermarkets being monitored

User Interface and Management

The frontend provides comprehensive product management capabilities. Users can add new products to be tracked by completing a simple form. The application also includes a product management section where users can edit or delete products from the scraping list, facilitating easy maintenance of the system.

Key Code Components

The application’s architecture includes several important components:

• Server.js: Handles API endpoints, including the route that initiates the scraping process using Node.js child processes
• CRUD Implementation: Provides complete create, read, update, and delete functionality for managing products
• Home Component: Controls the rendering of the products table and manages user interactions
• Fetch Products Function: Demonstrates how the frontend communicates with the backend API to retrieve product data
• Handle Actualize Function: Shows how the frontend triggers the scraping process and manages loading states to provide user feedback

Summary

This application represents an efficient solution for obtaining and comparing product information across multiple supermarkets. By automating the price comparison process, it provides users with current and accurate information, potentially saving them time and money when making purchasing decisions. The combination of modern web technologies ensures both performance and reliability in this practical application of web scraping techniques.