DEV Community

Davide Santangelo
Davide Santangelo

Posted on • Updated on

Ruby multithreaded crawler

A Ruby multithreaded crawler is a type of web crawler that is built using the Ruby programming language and is designed to use multiple threads to crawl and process multiple pages concurrently. This can help to improve the speed and efficiency of the crawler, as it can process multiple pages at the same time rather than having to crawl and process them sequentially.

To create a multithreaded crawler in Ruby, you would need to use Ruby's threading capabilities, which allow you to create and manage multiple threads in your program. For example, you could create a new thread for each page that you want to crawl, and then use that thread to process the page and extract any relevant information from it.

If you're new to Ruby and multithreading, it's recommended that you first learn the basics of the language and how to create and manage threads in Ruby. There are many online tutorials and resources available that can help you get started with this. Once you have a basic understanding of Ruby and multithreading, you can begin to develop your own multithreaded crawler.

Here is a simple example of how you might implement a multithreaded crawler in Ruby:

require 'net/http'
require 'thread'

# Function to crawl a single page
def crawl_page(url)
  # Use the Net::HTTP library to fetch the page content
  page_content = Net::HTTP.get(url)
  # Process the page content and extract relevant information
  # ...
end

# Create an array to store the URLs of the pages we want to crawl
urls = [
  "http://example.com/page1",
  "http://example.com/page2",
  "http://example.com/page3",
  # ...
]

# Create a queue to store the URLs that we want to crawl
queue = Queue.new

# Push the URLs onto the queue
urls.each { |url| queue << url }

# Create an array to store the threads
threads = []

# Start a new thread for each URL in the queue
while !queue.empty?
  url = queue.pop
  thread = Thread.new { crawl_page(url) }
  threads << thread
end

# Wait for all threads to complete
threads.each { |thread| thread.join }
Enter fullscreen mode Exit fullscreen mode

This example creates a simple multithreaded crawler that fetches and processes multiple pages concurrently.

It uses Ruby's Net::HTTP library to fetch the page content, and then processes the page content and extracts relevant information.

To extract the title from a page, you can use the title method of the Nokogiri library in Ruby. This method allows you to parse an HTML or XML document and extract the title element from it.

Here is an example of how you might use the title method to extract the title from a page:

require 'nokogiri'

# Function to extract the title from a page
def extract_title(page_content)
  # Parse the page content using Nokogiri
  doc = Nokogiri::HTML(page_content)
  # Extract the title from the page
  doc.title
end

# Fetch the page content
page_content = Net::HTTP.get(url)
# Extract the title from the page
page_title = extract_title(page_content)
Enter fullscreen mode Exit fullscreen mode

In this example, the extract_title function uses the Nokogiri library to parse the page content and extract the title element from it. The title method returns the contents of the title element as a string, which you can then use in your application as needed.

You can also use the at_css method of the Nokogiri library to extract the title element from the page and access its attributes and other information. For example, you could use the following code to extract the title element and print its attributes:

# Extract the title element from the page
title_element = doc.at_css('title')

# Print the attributes of the title element
puts title_element.attributes
Enter fullscreen mode Exit fullscreen mode

This code would output a list of the attributes of the title element, such as its class, id, and other attributes. You can use this information to further process the title or perform other operations on it.

Overall, the title method of the Nokogiri library is a powerful and convenient way to extract the title from a page in Ruby. It allows you to easily parse an HTML or XML document and extract the title element from it, so you can use the title in your application.

Of course, this is just a simple example, and you would need to add additional code to handle errors, timeouts, and other scenarios that may arise when crawling the web. Additionally, you may want to add additional features and capabilities to your crawler, such as support for different types of web content, scheduling, and more.

If you're new to Ruby and want to learn more about how to create multithreaded applications, I recommend checking out the Ruby documentation and online tutorials for more information. There are many resources available that can help you get started with Ruby and multithreading.

With Ractors

To create a multithreaded web crawler with Ractors in Ruby, you would need to do the following:

  1. Install the Ractors library by adding it to your Gemfile and running bundle install.

  2. Import the Ractor and MonitorMixin classes from the ractors library. These classes provide the necessary functionality for creating and managing concurrent threads.
    3 .Create a class that represents a single web crawling "actor". This class should include a crawl method that takes a URL and retrieves the HTML content from that URL.

  3. In the main program, create a number of instances of the web crawling actor class using the Ractor.new method. These instances will run concurrently as separate threads.

  4. Use the Ractor.select method to select a thread and send it a URL to crawl. The thread will retrieve the HTML content and return it to the main program.

  5. Repeat this process until all of the URLs have been crawled.

Overall, using Ractors to create a multithreaded web crawler in Ruby can make the crawling process more efficient by allowing multiple URLs to be crawled concurrently. However, it's important to keep in mind that concurrent programming can be difficult, so be sure to thoroughly test your code before using it in production.

Here is an example of a simple multithreaded web crawler using Ractors in Ruby:

# Import the necessary classes from the 'ractors' library
require 'ractors'
include Ractor
include MonitorMixin

# Define a web crawling actor class
class WebCrawler
  def crawl(url)
    # Retrieve the HTML content from the given URL
    # (implementation details omitted for simplicity)
    html_content = ...

    # Return the HTML content to the caller
    html_content
  end
end

# Create an array to hold the HTML content from each URL
html_content = []

# Create a number of instances of the web crawling actor
# (in this example, we will create four instances)
ractors = []
4.times do
  ractors << Ractor.new(WebCrawler.new)
end

# Define the list of URLs to crawl
urls = [
  "https://example.com/1",
  "https://example.com/2",
  "https://example.com/3",
  "https://example.com/4"
  # ...
]

# Iterate over the URLs, selecting a thread and sending it
# a URL to crawl. The thread will retrieve the HTML content
# and return it to the main program.
urls.each do |url|
  ractor, value = Ractor.select(*ractors)
  html_content << value.take(url)
end

# The HTML content from all of the URLs has now been retrieved
# and stored in the 'html_content' array.
Enter fullscreen mode Exit fullscreen mode

This code creates four instances of the WebCrawler class, which will run concurrently as separate threads. The main program then sends each thread a URL to crawl, and the thread returns the HTML content from that URL. The HTML content is then stored in an array for later use.

Keep in mind that this is just a simplified example, and you may need to add additional code to handle errors, timeouts, and other situations that can arise when crawling the web.

It can be useful to include benchmarks in your code to measure the performance of your web crawler. This can help you determine how well it is utilizing the available resources, and whether it is running efficiently.

To add benchmarks to the previous example, you could use the Benchmark module from Ruby's standard library. This module provides methods for measuring the time it takes to execute a block of code. Here is an example of how you could use the Benchmark module to measure the performance of the web crawler:

# Import the 'Benchmark' module
require 'benchmark'

# Define a web crawling actor class
class WebCrawler
  def crawl(url)
    # Retrieve the HTML content from the given URL
    # (implementation details omitted for simplicity)
    html_content = ...

    # Return the HTML content to the caller
    html_content
  end
end

# Create an array to hold the HTML content from each URL
html_content = []

# Create a number of instances of the web crawling actor
# (in this example, we will create four instances)
ractors = []
4.times do
  ractors << Ractor.new(WebCrawler.new)
end

# Define the list of URLs to crawl
urls = [
  "https://example.com/1",
  "https://example.com/2",
  "https://example.com/3",
  "https://example.com/4"
  # ...
]

# Use the 'Benchmark' module to measure the time it takes
# to crawl the URLs.
time = Benchmark.measure do
  # Iterate over the URLs, selecting a thread and sending it
  # a URL to crawl. The thread will retrieve the HTML content
  # and return it to the main program.
  urls.each do |url|
    ractor, value = Ractor.select(*ractors)
    html_content << value.take(url)
  end
end

# Print the benchmark results
puts time.real
Enter fullscreen mode Exit fullscreen mode

This code uses the Benchmark.measure method to measure the time it takes to crawl the URLs. The time.real property then gives the total time in seconds that it took to crawl the URLs. This time can be used as a measure of the performance of the web crawler.

Top comments (3)

Collapse
 
crawlbase profile image
Crawlbase

Woaw! This guide on creating a multithreaded Ruby crawler is awesome! It breaks down the process step by step, making it easy for beginners and pros alike to understand. Plus, the tip on using Ractors for faster crawling is super cool! If you're into this stuff, check out Crawlbase too for an extra boost in building your crawlers!

Collapse
 
faraazahmad profile image
Syed Faraaz Ahmad

This is pretty cool! I wonder how much better the performance could be if you use Ractors? maybe not much since most of the time here is taken by http requests?

Collapse
 
daviducolo profile image
Davide Santangelo

I just added the use of ractors