As a developer, I'm always looking for ways to automate repetitive tasks. Recently, I needed to scrape product details from a UK home decor site for a price comparison tool. Here's a quick Python script using BeautifulSoup and requests to extract product names and prices from a door accessories collection page.
python
import requests
from bs4 import BeautifulSoup
url = 'https://infinitydecor.co.uk/collections/door-accessories'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
products = []
for item in soup.select('.product-item'):
name = item.select_one('.product-title').text.strip()
price = item.select_one('.price').text.strip()
products.append({'name': name, 'price': price})
print(products[:5])
This gave me a clean list of front door hardware options in seconds. The trick is inspecting the HTML structure first—most e-commerce sites use predictable class names. Have you tried scraping product data for any projects?
Top comments (1)
Nice, clean script! I've done similar scraping for price tracking, but I usually include error handling for cases where a product might be out of stock and the price element is missing. How do you handle those edge cases?