Scraping
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Top Ruby Libraries for Web Scraping: A 2025 Toolkit Guide

Table of contents

In the realm of data extraction, web scraping serves as a potent mechanism to gather valuable information from the vast expanse of the internet. But what if this process could be made even more efficient and powerful? Enter Ruby - a high-level, multiparadigm programming language that brings a new dimension to web scraping. With its simplicity, productivity, and a rich ecosystem of Ruby libraries for web scraping, Ruby stands tall as a robust ally in your web scraping endeavors. Get ready to dig deeper into the art of web scraping with Ruby!

Key Takeaways

  • Ruby is an ideal choice for web scraping, with powerful features and a diverse library ecosystem
  • Essential Ruby gems such as Nokogiri, HTTParty and Mechanize simplify the process of extracting data from websites
  • Adhering to best practices for ethical web scraping is key to responsible data extraction from the internet
  • Advanced techniques like handling dynamic content and pagination can extend your scraping capabilities

Unlocking the Power of Ruby for Web Scraping

Ruby Web Scraping Overview

As you start your journey in web scraping, you'll realize Ruby provides numerous benefits. Not only is it easy to learn and use, but Ruby also presents an extensive array of libraries, or gems, that can simplify your web scraping tasks. With features ranging from parsing HTML documents to managing HTTP requests, these libraries can significantly streamline your web scraping workflow.

Moreover, Ruby's object-oriented nature makes it a breeze to handle complex data structures, making it an excellent choice for your web scraping needs. One of the significant strengths of Ruby lies in its flexibility and adaptability. Whether you are a novice programmer trying to scrape data for a small project or a seasoned developer working on extracting vast amounts of data from complex websites, Ruby has got you covered.

Thus, if you need an adaptable and potent tool to extract valuable web data from the internet, Ruby should top your list.

Why Choose Ruby for Your Web Scraping Needs?

You might question, given the abundance of programming languages, why opt for Ruby for web scraping? Well, the answer lies in Ruby's unique traits:

1. Readability and Ease of Use Ruby is renowned for its readability and ease of use, making it a favorite among developers. This readability translates into simpler maintenance and faster development cycles, which is a significant advantage when it comes to web scraping.

2. Rich Ecosystem of Libraries Ruby's diverse ecosystem of libraries enhances its web scraping abilities significantly. Libraries like Nokogiri can parse HTML and XML documents, Mechanize can manage cookies and sessions, and HTTParty can make HTTP requests simple and easy.

3. Dynamic Content Support For dynamic content that relies on JavaScript, Ruby offers headless browser libraries like Watir and Selenium that can render JavaScript and AJAX calls. These capabilities make Ruby a versatile and robust tool for your web scraping needs.

Essential Ruby Gems for Effective Data Scraping

Essential Ruby Gems

In the expansive world of Ruby, gems are akin to stars, each fulfilling a distinct role and improving the overall functionality of the language. For efficient web scraping, certain gems are indispensable. Nokogiri, HTTParty, and Mechanize are three such gems that serve as the bedrock of most Ruby scraping projects.

Nokogiri: The Cornerstone HTML Parser

When it comes to parsing HTML and XML documents in Ruby, Nokogiri is a gem that stands out. As the cornerstone library for web scraping tasks, Nokogiri offers a host of features that make it easy to parse HTML documents and extract the data you need.

Installation:

gem install nokogiri

Basic Usage:

require 'nokogiri'
require 'open-uri'

# Parse HTML from a URL
doc = Nokogiri::HTML(URI.open('https://example.com'))

# Find elements using CSS selectors
titles = doc.css('h1, h2, h3')
titles.each { |title| puts title.text }

# Find elements using XPath
links = doc.xpath('//a[@href]')
links.each { |link| puts "#{link.text}: #{link['href']}" }

Advanced Features:

# Parse HTML string
html = '<div class="product"><h2>Product Name</h2><span class="price">$99.99</span></div>'
doc = Nokogiri::HTML(html)

# Extract specific data
product_name = doc.css('.product h2').text
price = doc.css('.product .price').text

puts "Product: #{product_name}, Price: #{price}"

Nokogiri's strength lies in its simplicity and efficiency. Whether you're working with HTML or XML documents, Nokogiri offers an uncomplicated and user-friendly interface to parse these documents and navigate their structure.

HTTParty: Simplifying HTTP Requests

While Nokogiri takes care of parsing documents, HTTParty simplifies the process of making HTTP requests. It's like a trusted courier who reliably fetches web pages for your inspection.

Installation:

gem install httparty

Basic GET Request:

require 'httparty'

response = HTTParty.get('https://api.example.com/data')
puts response.body
puts response.code
puts response.headers

Advanced Usage with Headers and Parameters:

class WebScraper
  include HTTParty
  base_uri 'https://example.com'

  # Set default headers
  headers 'User-Agent' => 'Mozilla/5.0 (compatible; Ruby scraper)'

  def get_page(path, params = {})
    self.class.get(path, query: params)
  end
end

scraper = WebScraper.new
response = scraper.get_page('/search', { q: 'ruby', page: 1 })

Handling Authentication:

# Basic authentication
response = HTTParty.get('https://api.example.com/data', 
  basic_auth: { username: 'user', password: 'pass' }
)

# Custom headers for API keys
response = HTTParty.get('https://api.example.com/data',
  headers: { 'Authorization' => 'Bearer your_token_here' }
)

HTTParty's functionality extends beyond merely retrieving pages. It also allows you to customize your requests with headers and parameters, making it easier to interact with APIs and other web services.

Mechanize: The Full-Featured Web Scraping Agent

Last but not least in our trifecta of essential Ruby gems is Mechanize. This powerful library combines the functionality of several other gems to provide a comprehensive web scraping solution.

Installation:

gem install mechanize

Basic Usage:

require 'mechanize'

agent = Mechanize.new
page = agent.get('https://example.com')

# Navigate links
link = page.link_with(text: 'Products')
products_page = link.click

# Fill out forms
form = page.form_with(action: '/search')
form.q = 'ruby programming'
search_results = agent.submit(form)

Advanced Form Handling:

agent = Mechanize.new

# Set user agent to mimic a real browser
agent.user_agent_alias = 'Windows Chrome'

# Login to a website
login_page = agent.get('https://example.com/login')
login_form = login_page.form_with(action: '/login')
login_form.username = 'your_username'
login_form.password = 'your_password'

dashboard = agent.submit(login_form)

# Navigate authenticated areas
protected_data = agent.get('https://example.com/protected-data')

Cookie and Session Management:

agent = Mechanize.new

# Cookies are automatically handled
page1 = agent.get('https://example.com/set-cookie')
page2 = agent.get('https://example.com/read-cookie')  # Cookies sent automatically

# Manual cookie management
agent.cookie_jar.clear!  # Clear all cookies

Mechanize's capability to emulate a real web browser makes it an irreplaceable tool in any web scraper's toolkit. It can navigate websites just like a person would, clicking links, filling out forms, and maintaining session state.

Setting Up Your Ruby Environment for Scraping

Ruby Environment Setup

Having familiarized yourself with the key Ruby gems for web scraping, the subsequent step involves setting up your Ruby environment. A well-set-up environment is like a well-organized workspace – it increases efficiency and reduces errors.

Choosing the Right Ruby Version and Installation Method

The foundation of a robust Ruby environment starts with choosing the right version of Ruby. For web scraping tasks in 2025, Ruby 3.0 or later is recommended for optimal performance and security.

Installation Options:

macOS:

# Using Homebrew
brew install ruby

# Using rbenv (recommended for version management)
brew install rbenv
rbenv install 3.2.0
rbenv global 3.2.0

Ubuntu/Debian:

# Using package manager
sudo apt update
sudo apt install ruby-full

# Using rbenv
curl -fsSL https://github.com/rbenv/rbenv-installer/raw/HEAD/bin/rbenv-installer | bash
rbenv install 3.2.0
rbenv global 3.2.0

Windows:

# Download and install from rubyinstaller.org
# Or use Windows Subsystem for Linux (WSL)

Configuring Your Development Workspace

With Ruby installed, the next step is to configure your development workspace and install the necessary gems.

Creating a Gemfile:

# Gemfile
source 'https://rubygems.org'

gem 'nokogiri'
gem 'httparty'
gem 'mechanize'
gem 'watir'
gem 'selenium-webdriver'
gem 'csv'

group :development do
  gem 'pry'  # For debugging
  gem 'rubocop'  # For code style
end

Installing Dependencies:

bundle install

Setting Up Your Script Structure:

# scraper.rb
require 'bundler/setup'
require 'nokogiri'
require 'httparty'
require 'mechanize'
require 'csv'

class WebScraper
  def initialize
    @agent = Mechanize.new
    @agent.user_agent_alias = 'Windows Chrome'
  end

  def scrape_data(url)
    # Your scraping logic here
  end
end

Crafting Your First Ruby Scraper

Building Ruby Scraper

Having prepared your Ruby environment and equipped your toolkit with essential gems, you are now prepared to delve into the core of web scraping – building your initial Ruby scraper.

Analyzing the Target Web Page Structure

The first step in crafting a Ruby scraper is to analyze the structure of the target web page. This involves inspecting the web page's HTML code and identifying the data you want to extract.

Using Browser Developer Tools:

  1. Right-click on the element you want to scrape
  2. Select "Inspect Element"
  3. Note the CSS selectors or XPath expressions
  4. Look for patterns in the HTML structure

Example Analysis:

<div class="product-card">
  <h3 class="product-title">Product Name</h3>
  <span class="product-price">$99.99</span>
  <div class="product-rating" data-rating="4.5">★★★★☆</div>
</div>

Writing the Scraper Script

Once you have a solid understanding of the web page structure, the next step is to write the scraper script.

Complete Example - E-commerce Product Scraper:

require 'nokogiri'
require 'httparty'
require 'csv'

class ProductScraper
  def initialize(base_url)
    @base_url = base_url
    @products = []
  end

  def scrape_products(category_url)
    response = HTTParty.get(category_url, headers: headers)
    doc = Nokogiri::HTML(response.body)

    doc.css('.product-card').each do |product|
      product_data = extract_product_data(product)
      @products << product_data if product_data
    end

    @products
  end

  private

  def extract_product_data(product_element)
    {
      name: product_element.css('.product-title').text.strip,
      price: extract_price(product_element.css('.product-price').text),
      rating: product_element.css('.product-rating').attr('data-rating')&.value,
      image_url: product_element.css('img').attr('src')&.value,
      product_url: build_absolute_url(product_element.css('a').attr('href')&.value)
    }
  rescue => e
    puts "Error extracting product: #{e.message}"
    nil
  end

  def extract_price(price_text)
    price_text.gsub(/[^\d.]/, '').to_f
  end

  def build_absolute_url(relative_url)
    return nil unless relative_url
    URI.join(@base_url, relative_url).to_s
  end

  def headers
    {
      'User-Agent' => 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
      'Accept' => 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
      'Accept-Language' => 'en-US,en;q=0.5',
      'Accept-Encoding' => 'gzip, deflate',
      'Connection' => 'keep-alive'
    }
  end
end

# Usage
scraper = ProductScraper.new('https://example-shop.com')
products = scraper.scrape_products('https://example-shop.com/electronics')

puts "Scraped #{products.length} products"
products.each { |product| puts "#{product[:name]} - $#{product[:price]}" }

Storing and Handling Scraped Data

Once you've successfully scraped data from a web page, the next step is to store and handle the data.

Saving to CSV:

require 'csv'

def save_to_csv(products, filename)
  CSV.open(filename, 'w', write_headers: true, headers: ['Name', 'Price', 'Rating', 'URL']) do |csv|
    products.each do |product|
      csv << [product[:name], product[:price], product[:rating], product[:product_url]]
    end
  end
end

save_to_csv(products, 'scraped_products.csv')

Saving to JSON:

require 'json'

def save_to_json(products, filename)
  File.write(filename, JSON.pretty_generate(products))
end

save_to_json(products, 'scraped_products.json')

Database Storage:

require 'sqlite3'

def save_to_database(products)
  db = SQLite3::Database.new 'products.db'

  db.execute <<-SQL
    CREATE TABLE IF NOT EXISTS products (
      id INTEGER PRIMARY KEY,
      name TEXT,
      price REAL,
      rating REAL,
      url TEXT,
      scraped_at DATETIME DEFAULT CURRENT_TIMESTAMP
    );
  SQL

  products.each do |product|
    db.execute("INSERT INTO products (name, price, rating, url) VALUES (?, ?, ?, ?)",
               [product[:name], product[:price], product[:rating], product[:product_url]])
  end

  db.close
end

save_to_database(products)

Advanced Techniques in Ruby Web Scraping

Advanced Ruby Scraping

Now that you've got the basics of web scraping with Ruby under your belt, it's time to tackle some more advanced techniques. While the basics will get you far, there are times when you'll need to handle more complex scenarios.

Dealing with Dynamic Pages Using Watir

Dealing with dynamic pages can be a challenge in web scraping, as these pages often rely on JavaScript to load or display content. This is where the Watir library comes in.

Installation:

gem install watir
gem install webdrivers  # Automatically manages browser drivers

Basic Watir Usage:

require 'watir'

browser = Watir::Browser.new :chrome, headless: true
browser.goto 'https://example.com'

# Wait for JavaScript to load content
browser.div(class: 'dynamic-content').wait_until(&:present?)

# Interact with the page
search_box = browser.text_field(name: 'search')
search_box.set 'ruby programming'
browser.button(text: 'Search').click

# Wait for results to load
browser.div(class: 'search-results').wait_until(&:present?)

# Extract data
results = browser.divs(class: 'result-item').map do |result|
  {
    title: result.h3.text,
    description: result.p.text,
    url: result.a.href
  }
end

browser.close
puts "Found #{results.length} results"

Advanced JavaScript Handling:

class DynamicScraper
  def initialize
    @browser = Watir::Browser.new :chrome, headless: true
  end

  def scrape_infinite_scroll(url)
    @browser.goto url
    data = []

    loop do
      # Extract current page data
      current_items = extract_items
      data.concat(current_items)

      # Scroll to bottom
      @browser.execute_script("window.scrollTo(0, document.body.scrollHeight);")

      # Wait for new content to load
      sleep 2

      # Check if new items loaded
      new_items = extract_items
      break if new_items.length == current_items.length
    end

    data
  end

  private

  def extract_items
    @browser.divs(class: 'item').map do |item|
      {
        title: item.h3.text,
        content: item.p.text
      }
    end
  end
end

Managing Pagination and Multiple Requests

Handling pagination and multiple requests is crucial for comprehensive data extraction.

Pagination Handling:

class PaginationScraper
  def initialize
    @agent = Mechanize.new
    @agent.user_agent_alias = 'Windows Chrome'
  end

  def scrape_all_pages(base_url)
    all_data = []
    page_num = 1

    loop do
      puts "Scraping page #{page_num}..."

      current_url = "#{base_url}?page=#{page_num}"
      page = @agent.get(current_url)

      # Extract data from current page
      page_data = extract_page_data(page)
      break if page_data.empty?

      all_data.concat(page_data)
      page_num += 1

      # Be polite - add delay between requests
      sleep rand(1..3)

      # Check if there's a next page
      next_link = page.link_with(text: /next|→/i)
      break unless next_link
    end

    all_data
  end

  private

  def extract_page_data(page)
    page.search('.item').map do |item|
      {
        title: item.at('.title')&.text&.strip,
        description: item.at('.description')&.text&.strip
      }
    end.compact
  end
end

Concurrent Requests with Thread Pool:

require 'concurrent-ruby'

class ConcurrentScraper
  def initialize(max_threads: 5)
    @pool = Concurrent::ThreadPoolExecutor.new(
      min_threads: 1,
      max_threads: max_threads,
      max_queue: 100
    )
  end

  def scrape_urls(urls)
    futures = urls.map do |url|
      Concurrent::Future.execute(executor: @pool) do
        scrape_single_url(url)
      end
    end

    # Wait for all requests to complete and collect results
    results = futures.map(&:value)
    @pool.shutdown
    @pool.wait_for_termination

    results.compact
  end

  private

  def scrape_single_url(url)
    response = HTTParty.get(url, headers: headers, timeout: 10)
    doc = Nokogiri::HTML(response.body)

    {
      url: url,
      title: doc.at('title')&.text&.strip,
      data: extract_data(doc)
    }
  rescue => e
    puts "Error scraping #{url}: #{e.message}"
    nil
  end

  def headers
    {
      'User-Agent' => 'Mozilla/5.0 (compatible; Ruby scraper)',
      'Accept' => 'text/html,application/xhtml+xml'
    }
  end
end

Rate Limiting and Respectful Scraping

class RespectfulScraper
  def initialize(requests_per_minute: 60)
    @rate_limiter = RateLimiter.new(requests_per_minute)
  end

  def scrape_with_rate_limit(urls)
    urls.map do |url|
      @rate_limiter.wait_if_needed
      scrape_url(url)
    end
  end
end

class RateLimiter
  def initialize(requests_per_minute)
    @requests_per_minute = requests_per_minute
    @last_request_time = Time.now - 60
    @request_count = 0
  end

  def wait_if_needed
    current_time = Time.now
    time_since_last = current_time - @last_request_time

    if time_since_last >= 60
      @request_count = 0
      @last_request_time = current_time
    end

    if @request_count >= @requests_per_minute
      sleep_time = 60 - time_since_last
      sleep(sleep_time) if sleep_time > 0
      @request_count = 0
      @last_request_time = Time.now
    end

    @request_count += 1
  end
end

Best Practices for Ethical Web Scraping with Ruby

While web scraping serves as a potent tool for drawing data from the web, responsible usage is imperative. Ethical web scraping involves respect for the website you're scraping, adherence to legal guidelines, and mindful use of resources.

Essential Ethical Guidelines

1. Respect robots.txt

require 'robots'

def check_robots_txt(url, user_agent = '*')
  robots = Robots.new(user_agent)
  robots.allowed?(url)
end

# Usage
if check_robots_txt('https://example.com/data')
  # Proceed with scraping
else
  puts "Scraping not allowed by robots.txt"
end

2. Implement Rate Limiting

class EthicalScraper
  def initialize
    @last_request = Time.now - 1
    @min_delay = 1  # Minimum 1 second between requests
  end

  def polite_get(url)
    time_since_last = Time.now - @last_request
    if time_since_last < @min_delay
      sleep(@min_delay - time_since_last)
    end

    @last_request = Time.now
    HTTParty.get(url)
  end
end

3. Handle Errors Gracefully

def robust_scrape(url, max_retries: 3)
  retries = 0

  begin
    response = HTTParty.get(url, timeout: 10)

    case response.code
    when 200
      return response
    when 429  # Too Many Requests
      wait_time = response.headers['retry-after']&.to_i || 60
      puts "Rate limited. Waiting #{wait_time} seconds..."
      sleep(wait_time)
      raise "Rate limited"
    when 404
      puts "Page not found: #{url}"
      return nil
    else
      raise "HTTP #{response.code}"
    end

  rescue => e
    retries += 1
    if retries <= max_retries
      puts "Retry #{retries}/#{max_retries} for #{url}: #{e.message}"
      sleep(2 ** retries)  # Exponential backoff
      retry
    else
      puts "Failed to scrape #{url} after #{max_retries} retries"
      nil
    end
  end
end

4. Use Appropriate User Agents

USER_AGENTS = [
  'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
  'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36',
  'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36'
]

def random_user_agent
  USER_AGENTS.sample
end

Legal Considerations

  • Check Terms of Service: Always review the website's terms of service before scraping
  • Respect Copyright: Don't republish copyrighted content without permission
  • Public Data Only: Focus on publicly available information
  • Commercial Use: Be extra cautious when scraping for commercial purposes

Ruby Web Scraping in Action: Real-World Examples

Let's explore some practical examples of Ruby web scraping across different industries:

E-commerce Price Monitoring

class PriceMonitor
  def initialize(products)
    @products = products
    @agent = Mechanize.new
  end

  def check_prices
    @products.map do |product|
      current_price = scrape_price(product[:url])
      price_change = current_price - product[:last_price]

      {
        name: product[:name],
        last_price: product[:last_price],
        current_price: current_price,
        change: price_change,
        change_percent: (price_change / product[:last_price] * 100).round(2)
      }
    end
  end

  private

  def scrape_price(url)
    page = @agent.get(url)
    price_text = page.at('.price')&.text
    price_text.gsub(/[^\d.]/, '').to_f
  end
end

News Article Collection

class NewsAggregator
  def initialize
    @agent = Mechanize.new
    @articles = []
  end

  def scrape_news_site(base_url)
    main_page = @agent.get(base_url)
    article_links = main_page.links.select { |link| link.href.include?('/article/') }

    article_links.each do |link|
      article = scrape_article(link.href)
      @articles << article if article
      sleep 1  # Be respectful
    end

    @articles
  end

  private

  def scrape_article(url)
    page = @agent.get(url)

    {
      title: page.at('h1')&.text&.strip,
      author: page.at('.author')&.text&.strip,
      date: parse_date(page.at('.date')&.text),
      content: extract_content(page),
      url: url
    }
  rescue => e
    puts "Error scraping article #{url}: #{e.message}"
    nil
  end

  def extract_content(page)
    content_paragraphs = page.search('.article-content p')
    content_paragraphs.map(&:text).join("\n\n")
  end
end

Social Media Data Collection

class SocialMediaScraper
  def initialize
    @browser = Watir::Browser.new :chrome, headless: true
  end

  def scrape_posts(hashtag, limit: 50)
    @browser.goto "https://example-social.com/hashtag/#{hashtag}"

    posts = []
    scroll_count = 0
    max_scrolls = limit / 10

    while posts.length < limit && scroll_count < max_scrolls
      # Scrape current posts
      current_posts = extract_posts
      posts.concat(current_posts)

      # Load more content
      @browser.execute_script("window.scrollTo(0, document.body.scrollHeight);")
      sleep 3
      scroll_count += 1
    end

    posts.first(limit)
  ensure
    @browser.close
  end

  private

  def extract_posts
    @browser.divs(class: 'post').map do |post|
      {
        username: post.span(class: 'username').text,
        content: post.div(class: 'content').text,
        likes: extract_number(post.span(class: 'likes').text),
        shares: extract_number(post.span(class: 'shares').text),
        timestamp: post.time.attribute_value('datetime')
      }
    end
  end

  def extract_number(text)
    text.gsub(/[^\d]/, '').to_i
  end
end

Performance Optimization Tips

Memory Management

# Use streaming for large datasets
def process_large_dataset(urls)
  urls.each_slice(100) do |url_batch|
    process_batch(url_batch)
    GC.start  # Force garbage collection
  end
end

# Avoid storing large HTML documents
def extract_data_efficiently(url)
  response = HTTParty.get(url)
  doc = Nokogiri::HTML(response.body)

  # Extract only what you need
  data = {
    title: doc.at('title')&.text,
    price: doc.at('.price')&.text
  }

  # Don't keep references to the parsed document
  doc = nil
  data
end

Connection Pooling

require 'net/http/persistent'

class PooledScraper
  def initialize
    @http = Net::HTTP::Persistent.new
  end

  def scrape_urls(urls)
    urls.map do |url|
      uri = URI(url)
      response = @http.request(uri)
      process_response(response)
    end
  ensure
    @http.shutdown
  end
end

Summary

In conclusion, Ruby offers a powerful, versatile, and user-friendly platform for web scraping tasks in 2025. From its easy-to-use syntax to its rich ecosystem of libraries, Ruby makes web scraping accessible to both beginners and experienced developers.

Key advantages of Ruby for web scraping:

  • Clean, readable syntax that's easy to maintain
  • Rich ecosystem of specialized gems (Nokogiri, HTTParty, Mechanize, Watir)
  • Excellent support for both static and dynamic content
  • Strong community and extensive documentation
  • Built-in support for various data formats (JSON, CSV, XML)

Whether you're scraping data for a small project or extracting large amounts of data from complex websites, Ruby has the tools and capabilities to meet your needs. Remember to always scrape responsibly, respect robots.txt files, implement appropriate rate limiting, and consider the legal and ethical implications of your scraping activities.

Frequently Asked Questions

What makes Ruby a good choice for web scraping in 2025?

Ruby's readability, simplicity of use, and comprehensive library ecosystem make it an ideal choice for web scraping. Its object-oriented nature and extensive gem collection provide powerful tools for handling complex scraping tasks efficiently.

How does Nokogiri help in web scraping?

Nokogiri provides a convenient way to parse HTML and XML documents with CSS selectors and XPath expressions. It offers fast, efficient parsing capabilities and integrates seamlessly with other Ruby libraries for complete scraping solutions.

What's the difference between HTTParty and Mechanize for web scraping?

HTTParty is primarily an HTTP client library that simplifies making requests, while Mechanize is a full-featured web automation library that includes form handling, cookie management, and session persistence. Mechanize is better for complex interactions, while HTTParty is ideal for simple data fetching.

How can I handle JavaScript-heavy websites with Ruby?

Use browser automation libraries like Watir or Selenium WebDriver. These tools control real browsers (Chrome, Firefox) that can execute JavaScript, handle AJAX requests, and wait for dynamic content to load before extracting data.

What are the best practices for ethical web scraping with Ruby?

Always respect robots.txt files, implement rate limiting between requests, use appropriate User-Agent headers, handle errors gracefully, and avoid overloading target servers. Consider the website's terms of service and applicable laws in your jurisdiction.

How do I handle pagination when scraping multiple pages?

Implement a loop that follows pagination links or increments page parameters in URLs. Use libraries like Mechanize to click "Next" buttons, or construct URLs with page parameters. Always include delays between requests and check for the end of pagination.

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