Project Overview

This project involved building a custom Python script to extract structured product and pricing data from e-commerce websites. Using advanced HTML parsing and pattern recognition, the scraper can automate repetitive data collection for analysis or reporting.

Key Features

Automated Scraping

Collects product names, prices, and links from retail websites with minimal human input.

HTML Navigation

Leverages BeautifulSoup to traverse and extract nested elements from dynamic DOM trees.

Smart Filtering

Extracts relevant data only – filtering out ads, pagination, or redundant sections.

Export to CSV

Outputs structured data to spreadsheet-ready formats for easy analysis.

Tech & Tools

Sample Output

Product Name             | Price    | URL
------------------------|----------|---------------------------------
Wireless Mouse          | $15.99   | example.com/product/123
Laptop Stand            | $29.99   | example.com/product/456
Bluetooth Headphones    | $59.99   | example.com/product/789
...
Exported to: products.csv