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Free software libraries, packages, and SDKs for web crawling? Or is it a web scraper that you need?
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If you're tired of the limitations and costs of proprietary web scraping tools or being locked into a single vendor, open-source web crawlers and scrapers offer a flexible, customizable alternative.
But not all open-source tools are the same.
Some are full-fledged libraries capable of handling large-scale data extraction projects, while others excel at dynamic content or are ideal for smaller, lightweight tasks. The right tool depends on your project’s complexity, the type of data you need, and your preferred programming language.
The libraries, frameworks, and SDKs we cover here take into account the diverse needs of developers, so you can choose a tool that meets your requirements.
Open-source web crawlers and scrapers let you adapt code to your needs without the cost of licenses or restrictions. Crawlers gather broad data, while scrapers target specific information. Open-source solutions like the ones below offer community-driven improvements, flexibility, and scalability—free from vendor lock-in.
Language: Node.js, Python | GitHub: 15.4K stars | link
Crawlee is a complete web scraping and browser automation library designed for quickly and efficiently building reliable crawlers. With built-in anti-blocking features, it makes your bots look like real human users, reducing the likelihood of getting blocked.
Available in both Node.js and Python, Crawlee offers a unified interface that supports HTTP and headless browser crawling, making it versatile for various scraping tasks. It integrates with libraries like Cheerio and Beautiful Soup for efficient HTML parsing and headless browsers like Puppeteer and Playwright for JavaScript rendering.
The library excels in scalability, automatically managing concurrency based on system resources, rotating proxies to enhance efficiency, and employing human-like browser fingerprints to avoid detection. Crawlee also ensures robust data handling through persistent URL queuing and pluggable storage for data and files.
Check out Crawlee
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? Crawlee web scraping tutorial for Node.js
Best for: Crawlee is ideal for developers and teams seeking to manage simple and complex web scraping and automation tasks in JavaScript/TypeScript and Python. It is particularly effective for scraping web applications that combine static and dynamic pages, as it allows easy switching between different types of crawlers to handle each scenario.
Deploy your scraping code to the cloud
Language: Python | GitHub: 52.9k stars | link
Scrapy is one of the most complete and popular web scraping frameworks within the Python ecosystem. It is written using Twisted, an event-driven networking framework, giving Scrapy asynchronous capabilities.
As a comprehensive web crawling framework designed specifically for data extraction, Scrapy provides built-in support for handling requests, processing responses, and exporting data in multiple formats, including CSV, JSON, and XML.
Its main drawback is that it cannot natively handle dynamic websites. However, you can configure Scrapy with a browser automation tool like Playwright or Selenium to unlock these capabilities.
? Learn more about using Scrapy for web scraping
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Best for: Scrapy is ideally suited for developers, data scientists, and researchers embarking on large-scale web scraping projects who require a reliable and scalable solution for extracting and processing vast amounts of data.
? Run multiple Scrapy spiders in the cloud
Read the docs
Language: Python | GitHub: 4.7K stars | link
MechanicalSoup is a Python library designed to automate website interactions. It provides a simple API to access and interact with HTML content, similar to interacting with web pages through a web browser, but programmatically. MechanicalSoup essentially combines the best features of libraries like Requests for HTTP requests and Beautiful Soup for HTML parsing.
Now, you might wonder when to use MechanicalSoup over the traditional combination of BS4 Requests. MechanicalSoup provides some distinct features particularly useful for specific web scraping tasks. These include submitting forms, handling login authentication, navigating through pages, and extracting data from HTML.
MechanicalSoup makes it possible by creating a StatefulBrowser object in Python that can store cookies and session data and handle other aspects of a browsing session.
However, while MechanicalSoup offers some browser-like functionalities akin to what you'd expect from a browser automation tool such as Selenium, it does so without launching an actual browser. This approach has its advantages but also comes with certain limitations, which we'll explore next:
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Best for: MechanicalSoup is a more efficient and lightweight option for more basic scraping tasks, especially for static websites and those with straightforward interactions and navigation.
? Learn more about MechanicalSoup
Language: Node.js | GitHub: 6.7K stars | link
Node Crawler, often referred to as 'Crawler,' is a popular web crawling library for Node.js. At its core, Crawler utilizes Cheerio as the default parser, but it can be configured to use JSDOM if needed. The library offers a wide range of customization options, including robust queue management that allows you to enqueue URLs for crawling while it manages concurrency, rate limiting, and retries.
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Best for: Node Crawler is a great choice for developers familiar with the Node.js ecosystem who need to handle large-scale or high-speed web scraping tasks. It provides a flexible solution for web crawling that leverages the strengths of Node.js's asynchronous capabilities.
? Related: Web scraping with Node.js guide
Language: Multi-language | GitHub: 30.6K stars | link
Selenium is a widely-used open-source framework for automating web browsers. It allows developers to write scripts in various programming languages to control browser actions. This makes it suitable for crawling and scraping dynamic content. Selenium provides a rich API that supports multiple browsers and platforms, so you can simulate user interactions like clicking buttons, filling forms, and navigating between pages. Its ability to handle JavaScript-heavy websites makes it particularly valuable for scraping modern web applications.
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Best for: Selenium is ideal for developers and testers needing to automate web applications or scrape data from sites that heavily rely on JavaScript. Its versatility makes it suitable for both testing and data extraction tasks.
? Related: How to do web scraping with Selenium in Python
Language: Java | GitHub: 2.8K stars | link
Heritrix is open-source web crawling software developed by the Internet Archive. It is primarily used for web archiving - collecting information from the web to build a digital library and support the Internet Archive's preservation efforts.
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Best for: Heritrix is best suited for organizations and projects that aim to archive and preserve digital content on a large scale, such as libraries, archives, and other cultural heritage institutions. Its specialized nature makes it an excellent tool for its intended purpose but less adaptable for more general web scraping needs.
Language: Java | GitHub: 2.9K stars | link
Apache Nutch is an extensible open-source web crawler often used in fields like data analysis. It can fetch content through protocols such as HTTPS, HTTP, or FTP and extract textual information from document formats like HTML, PDF, RSS, and ATOM.
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Best for: Apache Nutch is ideal for organizations building large-scale search engines or collecting and processing vast amounts of web data. Its capabilities are especially useful in scenarios where scalability, robustness, and integration with enterprise-level search technologies are required.
Language: Java | GitHub: 11.4K stars | link
Webmagic is an open-source, simple, and flexible Java framework dedicated to web scraping. Unlike large-scale data crawling frameworks like Apache Nutch, WebMagic is designed for more specific, targeted scraping tasks, which makes it suitable for individual and enterprise users who need to extract data from various web sources efficiently.
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Best for: WebMagic is a suitable choice for developers looking for a straightforward, flexible Java-based web scraping framework that balances ease of use with sufficient power for most web scraping tasks. It's particularly beneficial for users within the Java ecosystem who need a tool that integrates smoothly into larger Java applications.
Language: Ruby | GitHub: 6.1K stars | link
Like Beautiful Soup, Nokogiri is also great at parsing HTML and XML documents via the programming language Ruby. Nokogiri relies on native parsers such as the libxml2 libxml2, libgumbo, and xerces. If you want to read or edit an XML document using Ruby programmatically, Nokogiri is the way to go.
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Best for: Nokogiri is particularly well-suited for developers already working within the Ruby ecosystem and needs a robust, efficient tool for parsing and manipulating HTML and XML data. Its speed, flexibility, and Ruby-native design make it an excellent choice for a wide range of web data extraction and transformation tasks.
Language: Java | GitHub: 4.5K stars | link
Crawler4j is an open-source web crawling library for Java, which provides a simple and convenient API for implementing multi-threaded web crawlers. Its design focuses on simplicity and ease of use while providing essential features needed for effective web crawling.
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Best for: Crawler4j is a good choice for Java developers who need a straightforward, efficient tool for web crawling that can be easily integrated into Java applications. Its ease of use and performance capabilities make it suitable for a wide range of crawling tasks, particularly where large-scale operations are not required.
Language: Go | GitHub: 11.1k | link
Katana is a web scraping framework focused on speed and efficiency. Developed by Project Discovery, it is designed to facilitate data collection from websites while providing a strong set of features tailored for security professionals and developers. Katana lets you create custom scraping workflows using a simple configuration format. It supports various output formats and integrates easily with other tools in the security ecosystem, which makes it a versatile choice for web crawling and scraping tasks.
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Best for: Katana is best suited for security professionals and developers looking for a fast, efficient framework tailored to web scraping needs within the cybersecurity domain. Its integration capabilities make it particularly useful in security testing scenarios where data extraction is required.
Apify is a full-stack web scraping and browser automation platform for building crawlers and scrapers in any programming language. It provides infrastructure for successful scraping at scale: storage, integrations, scheduling, proxies, and more.
So, whichever library you want to use for your scraping scripts, you can deploy them to the cloud and benefit from all the features the Apify platform has to offer.
Apify also hosts a library of ready-made data extraction and automation tools (Actors) created by other developers, which you can customize for your use case. That means you don't have to build everything from scratch.
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