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What meal plan data can be scraped from BlueApron.com using Ruby?
Scraping meal plan data from BlueApron.com using Ruby allows you to extract details such as meal names, ingredients, and pricing. Ruby’s open-uri library for HTTP requests and nokogiri for parsing HTML simplifies the process. Below is an example script for scraping Blue Apron’s meal plans.
require 'open-uri' require 'nokogiri' # Target URL url = "https://www.blueapron.com/pages/sample-menu" html = URI.open(url).read # Parse HTML doc = Nokogiri::HTML(html) # Extract meal details doc.css('.meal-card').each do |meal| name = meal.css('.meal-title').text.strip rescue 'Name not available' ingredients = meal.css('.ingredients').text.strip rescue 'Ingredients not available' price = meal.css('.price').text.strip rescue 'Price not available' puts "Name: #{name}, Ingredients: #{ingredients}, Price: #{price}" endThis script fetches Blue Apron’s sample menu page and extracts meal names, ingredients, and prices. Pagination or category filtering can be added for more specific data collection. Adding random delays between requests helps avoid detection and ensures smooth scraping sessions.
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2 Replies
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Adding pagination or filtering functionality to the Blue Apron scraper ensures a more targeted dataset. By navigating through meal categories or programmatically following pagination links, the scraper can gather data on a wider range of meal plans. Random delays between requests mimic human behavior, reducing the likelihood of detection. Proper pagination handling improves the scraper’s effectiveness in collecting comprehensive data for detailed analysis. This feature is especially helpful for studying pricing trends or ingredient diversity.
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Error handling ensures the scraper remains reliable even if Blue Apron updates its site structure. For example, missing elements like meal prices or ingredients should not cause the scraper to fail. Adding conditional checks for null values ensures that the script continues functioning smoothly. Regularly testing the scraper helps adapt it to changes in the website layout. These practices enhance the scraper’s long-term usability and reliability.
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