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Scrape seller information from Unieuro Italy using Ruby
Unieuro is one of the most popular electronics and appliance retailers in Italy, offering a wide range of products both online and offline. Scraping seller information from Unieuro involves extracting details about the seller displayed on the product page. This information typically includes the seller’s name, customer ratings, and any additional policies, such as return or warranty conditions. Using Ruby with the Nokogiri gem, you can efficiently parse and extract this data from the HTML of a product page.
The first step is to inspect the HTML structure of the Unieuro website using browser developer tools. The seller details are usually located near the product title or price, often wrapped in specific classes or tags for easy identification. Once the correct structure is identified, you can set up the scraper to locate and extract this information. Below is the complete Ruby script for extracting seller information from Unieuro Italy:require 'nokogiri' require 'open-uri' # URL of the Unieuro product page url = 'https://www.unieuro.it/online/product-page' # Fetch the page content doc = Nokogiri::HTML(URI.open(url)) # Scrape seller information seller_section = doc.at_css('.seller-info') if seller_section seller_name = seller_section.at_css('.seller-name')&.text&.strip || 'No seller name available' seller_rating = seller_section.at_css('.seller-rating')&.text&.strip || 'No rating available' seller_policies = seller_section.at_css('.seller-policies')&.text&.strip || 'No policies available' puts "Seller Name: #{seller_name}" puts "Seller Rating: #{seller_rating}" puts "Seller Policies: #{seller_policies}" else puts "No seller information found." end -
4 Replies
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The script could be improved by adding functionality to scrape seller information for multiple products. By iterating over a list of product URLs, the scraper could gather seller data for a broader range of items on the website.
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Adding error handling for network failures or missing elements would enhance the script’s reliability. For example, wrapping the scraping code in a begin-rescue block would ensure that the script continues running even if it encounters an error on one page.
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Integrating proxy support and rotating user agents would make the scraper less detectable to Unieuro’s anti-bot mechanisms. This would allow for consistent access when collecting data from multiple pages.
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Saving the scraped seller information into a database, rather than printing it to the console, would improve scalability. A database would enable efficient querying and facilitate integration with other tools for analysis or reporting.
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