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Updated on Aug 18, 2025

15 Best Open Source Web Crawlers: Python, Java, & JavaScript Options

Web crawlers are specialized bots designed to navigate websites and extract data automatically and at scale. Instead of building these complex tools from scratch, developers can leverage open-source crawlers.

These freely available and modifiable solutions provide a powerful foundation for creating scalable and highly customized data extraction pipelines.

Compare the top open-source web crawlers, based on their architecture, programming language, and capability to handle the JavaScript-heavy web:

Updated at 08-18-2025
Web crawlerLanguage written inRuns onSource code
Apache NutchJavaWindows
Mac
Linux
GitHub
Apify CrawleeJavaScriptWindows
Mac
Linux
GitHub
BUbiNGJavaLinuxGitHub
HeritrixJavaLinuxGitHub
JSpiderJavaWindows
Mac
Linux
GitHub
Node CrawlerJavaScriptWindowsGitHub
NokogiriRubyWindows
Mac
Linux
GitHub
Norconex HTTP CollectorJavaWindows
Mac
Linux
GitHub
OpenSearchServerJavaWindows
Mac
Linux
GitHub
PoritaJavaScriptWindows
Mac
Linux
GitHub
PySpiderPythonWindowsGitHub
ScrapyPythonWindows
Mac
Linux
GitHub
StormCrawlerJavaLinuxGitHub
WebHarvestJavaWindows
Mac
Linux
GitHub
WebSphinxJavaWindows
Mac
Linux
GitHub

Top 15 open-source web crawlers and web scrapers

1. Crawlee

Crawlee is an open-source Node.js library for scraping tasks and a browser automation library created by Apify. Crawlee has three crawler classes: CheerioCrawler, PuppeteerCrawler, and PlaywrightCrawler (browser-based crawlers).

CheerioCrawler is an HTTP crawler with HTML parsing and no JavaScript rendering, making it ideal for static content. PuppeteerCrawler / PlaywrightCrawler is ideal for JS-heavy pages with automatic browser management.

Advantages of Crawlee:

  • Includes anti-blocking tools out of the box, such as auto-generated human-like headers and TLS fingerprints, proxy rotation, and session management.
  • Offers a type-hinted API supporting both HTTP crawlers and browser-based crawlers.

2. Apache Nutch

Apache Nutch is developed in Java by the Apache Software Foundation for both enterprise and research-scale crawling. Nutch excels in batch-processing and distributed crawling via Hadoop MapReduce.

Advantages of Apache Nutch:

  • Leverages Apache Hadoop’s MapReduce framework for crawling and processing data at scale.
  • Built on a modular plugin system (e.g., Tika for parsing, Solr/Elasticsearch for indexing).
  • Handles a wide array of content types (HTML, XML, PDFs, Office formats, and RSS feeds).

3. BUbiNG

BUbiNG is designed for high-throughput, fully distributed crawling written in Java by the Laboratory. The tool is extensively customizable via configuration files and supports reflection-based components. It informs users about tailored filters, data flow, and crawl logic.

Advantages of BUbiNG:

  • Crawling speed scales linearly with the number of agents; a single agent can crawl thousands of pages per second.
  • Enforces customizable delays both per host and per IP.

4. Heritrix

Heritrix is an archival-quality web crawler written in Java, primarily used for web archiving. It returns site snapshots in standardized formats, such as ARC and its successor, preserving both HTTP headers and full responses in large, grouped files.

Advantages of Heritrix:

  • Offers both a web-based UI and a command-line interface, allowing flexible management of crawl jobs and schedules.
  • Supports components for fetching, parsing, scoping, and politeness rules.

5. JSpider

JSpider is a Java-powered web spider that offers a plugin-oriented design. You can add functionalities such as dead link detection, performance testing, and sitemap creation. It can be run via the command line or invoked as a library in Java applications.

Advantages of JSpider:

  • Supports custom plugin development
  • Offers a user manual in PDF format, covering installation, configuration, usage, and extension development.

6. Node Crawler

Node Crawler is a widely adopted library for building web crawlers in Node.js. Node Crawler integrates Cheerio by default to provide server-side parsing.

Advantages of Node Crawler:

  • Supports configurable concurrency, retries, rate limiting, and a priority-based request queue.
  • Includes built-in charset detection, UTF-8 by default, automatic conversion, and retry logic for resilience.

7. Nokogiri

Nokogiri is an HTML and XML parsing library in the Ruby ecosystem, combining the performance of native C-based parsers with a user-friendly API. The system offers multiple parsing modes:

  • DOM parser for in-memory document handling
  • SAX (streaming) parser for large documents
  • Builder DSL to generate XML/HTML programmatically, plus XSLT and XML schema validation support.

Advantages of Nokogiri:

  • Includes precompiled native libraries for easy installation, eliminating manual dependencies.
  • Supports document traversal and querying using both CSS3 selectors and XPath 1.0 expressions.
  • Handles malformed markup, supports streaming (SAX), and lets users build XML/HTML via a DSL.

8. Norconex HTTP Collector

Norconex HTTP Collector, or Norconex Web Crawler, is a Java-based, open-source enterprise crawler. Norconex employs a two-tier design, where a Collector orchestrates execution by delegating crawling tasks to one or more Crawler instances.

Advantages of Norconex HTTP Collector:

  • Supports full and incremental crawls, adaptive scheduling, and hit intervals customized per schedule.
  • Offers content extraction across various formats (HTML, PDF, Office, images), along with language detection, metadata extraction, and the capture of featured images.
  • Supports advanced content manipulation such as deduplication, URL normalization, sitemap parsing, canonical handling, external scripting, and dynamic title generation.

9. OpenSearchServer

OpenSearchServer is an open-source search engine framework built on Lucene. Its integrated web crawling capabilities make it especially fitting for applications that combine crawling, indexing, and full-text search workflows.

Advantages of OpenSearchServer:

  • Supports HTTP/HTTPS crawling for web pages. It allows URL parameter filtering, crawl session settings, and URL browser UI to check link status.
  • Crawls local and remote file systems (NFS, CIFS, FTP, FTPS) to capture attributes for indexing.
  • Offers built-in parsers that scrape data and metadata from formats like HTML/XHTML.
  • Supports multilingual indexing (up to 18 languages).

10. Porita

Portia is a browser-based tool that enables users to create web scrapers without writing a single line of code. It’s designed to allow visual data extraction through intuitive page annotations. Portia can also be deployed via Docker or Vagrant for self-hosting.

Advantages of Porita:

  • When you annotate a sample page by clicking on elements you want to collect. The tool learns the structure and automatically applies it to similar pages.
  • Stops crawling if fewer than 200 items are scraped within an hour by default to prevent endless loops.
  • Configures login requirements or enables JavaScript rendering with Splash.

11. PySpider

PySpider is a Python-based web crawling framework that provides a browser-based interface, including a script editor, task monitor, project manager, and results viewer. Users can schedule periodic crawls, prioritize tasks, and re-crawl based on content age.

Advantages of PySpider:

  • Can handle dynamic content loading and user interactions.
  • Divides the crawl process into modular components like “Scheduler, Fetcher, Processor, Monitor, and Result Worker”.

12. Scrapy

Scrapy is an open-source Python framework used for web data extraction and web crawling. Scrapy provides a Selector API wrapping lxml for parsing HTML/XML. Both can be mixed in one spider.

However, Scrapy alone can’t execute JavaScript. You need to use Scrapy-Splash (a headless browser service) or integrate Playwright/Selenium.

Advantages of Scrapy:

  • Fetches web content using asynchronous HTTP.
  • Modify requests/responses before they reach spiders or after they are downloaded.
  • Queues requests and decides which one to process next.

13. StormCrawler

StormCrawler is an open-source SDK for building distributed web crawlers in Java. Instead of the request–response loop, StormCrawler uses Storm topologies (directed acyclic graphs (DAGs) of processing components). The tool enables users to swap or customize URL sources, parsers, and storage. It requires knowledge of Java and Apache Storm.

Advantages of StormCrawler:

  • Offers regex-based or custom filters to control which URLs to crawl.
  • Support for HTTPS, cookies, and compression.
  • Fetches and processes pages continuously, rather than in batch jobs.
  • Tracks crawl progress and schedules recrawls.

14. Web Harvest

Web Harvest is configured using XML files. Users can define the data collection logic by specifying a sequence of processors and actions in an XML file.

Web Harvest heavily relies on technologies such as XPath, XSLT, and Regular Expressions to extract all the data from HTML and XML documents.

It includes a graphical user interface (GUI) that helps developers create their scraping configurations. The latest official version, 1.0, was released in October 2007, and the last news was posted in March 2013.

Advantages of Web Harvest:

  • Allows for the embedding of scripting languages such as Groovy and BeanShell within its XML configurations.
  • Has processors for control flow, such as loops to iterate over a list of items found on a page.

15. WebSphinx

WebSphinx (also written as SPHINX) is a Java-based web crawler toolkit. Users can develop, run, and visualize crawls, often without writing any code for simple tasks. It doesn’t render JavaScript, as it is designed for a much simpler, static web.

Advantages of WebSphinx:

  • Includes a graphical user interface (GUI) called the “Crawler Workbench” that could run in a web browser as a Java applet.
  • Offers components called “classifiers” that could be attached to a crawler to analyze and label pages and links with useful attributes.

What are open source web crawlers?

Open source web crawlers are software programs that automatically browse the internet and extract data. They are used for indexing websites for search engines, web archiving, SEO monitoring, and data mining.

Developers can modify the source code for specific needs. For example, you can change how they discover web pages, what data they extract, and how they store it.

FAQs about open-source web crawlers

How to choose the right open source crawler?

To choose the right open source crawler for your business or scientific purposes, make sure to follow best practices:

Participate in the community: Open-source crawlers typically have a large and active community where users share new code or ways to fix bugs. Businesses can engage with the community to quickly find solutions to their problems and discover effective crawling methods.

Update open-source crawlers regularly: Businesses should track open-source software updates and deploy them to patch security vulnerabilities and add new features.

Choose an extensible crawler: It is important to select an open-source crawler that can handle new data formats and fetch protocols used to request access to pages. It is also crucial to choose a tool that can be run on the types of devices used in the organization (Mac, Windows machines, etc.)

How to program a web crawler in-house?

Depending on the frequency and scale of your web crawling needs, you may find programming your web crawler more productive in the long run. In-house web crawlers will likely need technical maintenance.

Therefore, if you do not have technical resources built into your team and will outsource the web crawling effort, using an open source tool or working with web scrapers may be less hassle-free, given that you would be dependent on a technical freelancer for the in-house solution as well.

Open-source crawlers are legal to use. Legality depends on factors such as compliance with website terms of service, respecting robots.txt, or ethical crawling.

What programming languages are most common for open-source crawlers?

Open-source crawlers are built in a variety of programming languages, including (e.g., Apache Nutch, Heritrix, BUbiNG), JavaScript/Node.js (Crawlee or Node Crawler), Ruby (Nokogiri), and Python library (Scrapy, BeautifulSoup, and PySpider).

Can open-source crawlers handle JavaScript-heavy websites?

Yes, but not all of them. Static crawlers only fetch raw HTML and can’t capture content rendered by JavaScript. Crawlers with JavaScript rendering support, such as headless browsers, web automation frameworks, and rendering services.

Can I run open-source crawlers in the cloud?

Yes. Common cloud deployment options include Docker containers, Serverless Functions, and managed services.
Running crawlers in the cloud enables them to operate 24/7 without requiring your own machine to be on.

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Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 55% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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