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  • Which is better: Python or Ruby for scraping product reviews from eBay?

    Posted by Michael Woo on 12/05/2024 at 3:23 pm

    Scraping product reviews from eBay can be a challenging yet rewarding task. Python and Ruby are both popular choices for web scraping, but which one works better for this purpose? Python is known for its powerful scraping libraries like BeautifulSoup and Scrapy, making it ideal for handling static and dynamic content. Ruby, on the other hand, offers a clean and intuitive syntax with Nokogiri, which is excellent for parsing HTML efficiently. But how do these languages handle eBay’s dynamic loading of reviews? Can Python’s Selenium or Ruby’s Watir handle JavaScript-heavy pages more effectively?
    Let’s start with a Python implementation using BeautifulSoup to scrape static reviews. While it works well for non-dynamic content, it might need Selenium for JavaScript-rendered reviews.

    import requests
    from bs4 import BeautifulSoup
    # URL of an eBay product page
    url = "https://www.ebay.com/product-page"
    headers = {"User-Agent": "Mozilla/5.0"}
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.content, "html.parser")
        reviews = soup.find_all("div", class_="review-item")
        for idx, review in enumerate(reviews, 1):
            reviewer = review.find("span", class_="reviewer-name").text.strip() if review.find("span", class_="reviewer-name") else "Anonymous"
            comment = review.find("p", class_="review-text").text.strip() if review.find("p", class_="review-text") else "No comment"
            print(f"Review {idx}: {reviewer} - {comment}")
    else:
        print("Failed to fetch the page. Status code:", response.status_code)
    

    Now, let’s consider Ruby, using Nokogiri. Its syntax is straightforward and works well for static HTML:

    require 'nokogiri'
    require 'open-uri'
    # URL of an eBay product page
    url = 'https://www.ebay.com/product-page'
    # Fetch and parse the HTML
    doc = Nokogiri::HTML(URI.open(url))
    # Scrape reviews
    reviews = doc.css('.review-item')
    if reviews.any?
      reviews.each_with_index do |review, index|
        reviewer = review.at_css('.reviewer-name')&.text&.strip || 'Anonymous'
        comment = review.at_css('.review-text')&.text&.strip || 'No comment'
        puts "Review #{index + 1}: #{reviewer} - #{comment}"
      end
    else
      puts "No reviews found."
    end
    

    Both implementations have their pros and cons. Python provides more flexibility when handling dynamic content, while Ruby offers clean and concise syntax for static content. If you’re dealing with paginated reviews or JavaScript-rendered elements, Python’s Selenium might be a better choice.

    Elias Dorthe replied 1 day, 1 hour ago 8 Members · 7 Replies
  • 7 Replies
  • Alexis Pandeli

    Member
    12/18/2024 at 10:50 am

    Python’s extensive library ecosystem, such as Scrapy and Selenium, makes it more versatile for complex scraping tasks. It is especially useful for handling JavaScript-rendered reviews on dynamic pages.

  • Anne Santhosh

    Member
    12/20/2024 at 10:40 am

    Ruby’s Nokogiri is lightweight and simple to use, making it ideal for beginners or for scraping static HTML. However, it may struggle with dynamic content without additional libraries like Watir.

  • Egzona Zawisza

    Member
    12/20/2024 at 11:11 am

    For paginated reviews, both Python and Ruby can be enhanced to iterate through multiple pages. Python’s Scrapy framework, for example, provides built-in support for handling pagination efficiently.

  • Janiya Jeanette

    Member
    12/21/2024 at 6:08 am

    When dealing with large-scale scraping, Python’s multiprocessing capabilities give it a performance edge. Ruby, while elegant, might require more manual handling for parallel requests.

  • Jayesh Jacky

    Member
    12/21/2024 at 7:04 am

    Dynamic content rendering on eBay could benefit from Python’s Selenium integration. It can simulate browser behavior and ensure all reviews are fully loaded before scraping.

  • Luka Jaakob

    Member
    12/21/2024 at 7:23 am

    Ruby’s community and libraries are great for smaller projects, but Python’s vast resources make it more suitable for scraping tasks that require data analysis or machine learning integration.

  • Elias Dorthe

    Member
    12/21/2024 at 7:40 am

    To improve reliability, both implementations could include error handling for network issues and missing elements. Logging missing data and retrying failed requests would make the scrapers more robust.

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