Dynamic Web Scraper: From Category Links to Product Details
A Python scraper that uses Selenium and BeautifulSoup to pull product listings from an e-commerce site, navigating categories and parsing detailed product pages into a JSON file.
The Idea
I started this project when I needed a quick way to pull data from a complex online store. The site loads products with JavaScript, so a simple requests‑based approach wouldn’t work.
How It Works
The scraper opens the site in a real browser, scrolls until all lazy‑loaded items appear, and then grabs the HTML. BeautifulSoup walks that markup to pull titles, prices, and links. Next, it visits each product page to capture description, color, size, and more images.
Running It
You’ll need a virtual environment and a few packages. Once set up, run python navigator.py. The script writes everything to data.json.
Real‑World Numbers
During a test run, the scraper fetched 5 product listings from a single category in under 30 seconds. That’s the baseline you can scale from.
Why It Matters
Data‑driven decisions start with accurate information. With this tool, you can keep product catalogs up‑to‑date without manual copying, saving hours of repetitive work.