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What menu details can I scrape from Grubhub.com using Ruby?
Scraping menu details from Grubhub.com using Ruby allows you to collect restaurant names, menu items, and pricing. Ruby’s open-uri library for HTTP requests and nokogiri for parsing HTML makes the process efficient. Below is a sample script for extracting menu data from Grubhub.
require 'open-uri' require 'nokogiri' # Target URL url = "https://www.grubhub.com/" html = URI.open(url).read # Parse HTML doc = Nokogiri::HTML(html) # Extract restaurant and menu details doc.css('.restaurant-card').each do |restaurant| name = restaurant.css('.restaurant-name').text.strip rescue 'Name not available' menu_item = restaurant.css('.menu-item-name').text.strip rescue 'Menu item not available' price = restaurant.css('.menu-item-price').text.strip rescue 'Price not available' puts "Restaurant: #{name}, Menu Item: #{menu_item}, Price: #{price}" endThis script fetches Grubhub restaurant and menu details, parsing the page to extract names, menu items, and prices. Pagination or filtering by location can be added to gather more specific data. Adding delays between requests reduces the risk of detection by anti-scraping measures.
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2 Replies
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Handling pagination is essential for scraping all restaurant and menu data from Grubhub. Menu items and restaurants are often spread across multiple pages, so automating navigation ensures comprehensive data collection. Adding random delays between requests helps mimic human behavior and reduces detection risks. With pagination, the scraper can collect a more complete dataset for analysis. This functionality is particularly useful for studying pricing trends across different locations.
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Error handling ensures the scraper continues to function even if Grubhub updates its layout. Missing elements, such as prices or menu item names, should not cause the script to fail. Adding conditional checks for null values ensures that the scraper skips problematic entries without crashing. Logging skipped entries provides insights into potential issues and helps refine the script. Regular updates ensure the scraper remains reliable over time.
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