Modern Web Crawling service and Github Project

Modern Web Crawling service and Github Project

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6 min read

Here's a comparison of modern web crawling services and GitHub projects:

TitleDescriptionGitHub StarsType
CrawleeComplete web scraping and browser automation library with built-in anti-blocking features and support for HTTP/browser crawling12.3KLibrary
PySpiderPowerful Python-based web crawling system with web UI for monitoring and control16.3KLibrary
Apache NutchExtensible crawler for large-scale web crawling with Hadoop integration2.8KFramework
Reader (Jina AI)Modern URL-to-markdown converter optimized for LLM input4.5KService
LLM ScraperTypeScript library converting webpages to structured data using LLMsN/ALibrary
FireCrawlAPI service for converting URLs into clean, LLM-friendly markdownN/AService
ScrapeGraphAIPython library using LLM and graph logic for web scrapingN/ALibrary
Spider-FlowVisual spider framework requiring no coding to crawl websitesN/AFramework
CrawleeFast and reliable web crawler with Node.js supportN/ALibrary
PHPScraperSimple PHP-based scraper and crawlerN/ALibrary
WebCollectorMulti-threaded web crawler with simple interfacesN/ALibrary
StormCrawlerScalable crawler built on Apache StormN/AFramework

Are there any other GitHub projects similar to D4Vinci/Scrapling

Based on the search results, I'll create a comprehensive table of notable web crawling and scraping frameworks/projects:

Project NameDescriptionGitHub StarsLanguage
ScrapyHigh-level web crawling & scraping framework with extensive features and async capabilities51KPython
Crawl4AILLM-friendly web crawler optimized for AI applications15.8KPython
PySpiderPowerful web crawling system with web-based UI and JavaScript support16.3KPython
CollyFast and elegant scraping framework with clean API and high performance~10KGo
CrawleeModern web scraping library with anti-blocking features and browser automation12.3KNode.js
WebMagicFlexible Java-based scraping framework for targeted data extraction11.3KJava
Sublist3rOSINT-based subdomain enumeration tool~8KPython
PholcusDistributed, high-concurrency web crawler~5KGo
FetchbotSimple and flexible web crawler with robots.txt support~3KGo
Go-SpiderConcurrent crawler framework with extensive features~2KGo

Notable Features

Popular Features Across Projects:

  • Async/parallel crawling capabilities

  • Proxy support and rotation

  • JavaScript rendering

  • Custom middleware support

  • Data export in multiple formats

  • Rate limiting and politeness controls

  • Cookie and session handling

  • Distributed crawling options

Many of these projects are actively maintained and regularly updated with new features and security patches.

Are there any other GitHub projects similar to Firecrawl

Based on the search results, here are similar GitHub projects that focus on LLM-friendly web crawling and content processing:

Project NameDescriptionGitHub StarsKey Features
Crawl4AIOpen-source LLM-friendly web crawler & scraper15.8KJavaScript execution, custom hooks, content loading verification
FirecrawlWebsite to LLM-ready markdown converter1.4KClean markdown conversion, structured data output, built-in LangChain/LlamaIndex loaders
CrawleeWeb scraping library with LLM optimization12.3KAnti-blocking features, browser automation, proxy rotation
WebMagicTargeted web scraping framework11.3KFlexible architecture, efficient data extraction, good for specific scraping tasks

Unique Features Comparison

Content Processing:

  • Firecrawl specializes in converting websites into clean markdown with handling for images, videos, and tables

  • Crawl4AI focuses on making content LLM-friendly with JavaScript rendering support

  • Crawlee offers human-like browser fingerprints and automatic concurrency management

Integration Capabilities:

  • Firecrawl provides direct integration with LlamaIndex and LangChain

  • Most frameworks support custom middleware and export formats

  • Several options include built-in proxy support and caching mechanisms

The choice between these tools often depends on specific requirements such as scale, content type handling, and integration needs with existing LLM infrastructure.

How to crawl the uncrawlable site

Based on the search results, here's a comprehensive guide on how to crawl challenging websites:

Core Strategies

Browser Emulation

  • Use headless browsers to handle JavaScript-heavy sites and dynamic content loading

  • Implement tools like Playwright or Puppeteer for full browser rendering

  • Enable JavaScript rendering to analyze the rendered version of pages

Request Management

  • Rotate User-Agents to mimic different browsers and devices
from fake_useragent import UserAgent
ua = UserAgent()
headers = {
    'User-Agent': ua.random,
}

Anti-Detection Measures

  • Add legitimate referrer headers to appear as organic traffic

  • Watch for and avoid honeypot traps (hidden links with CSS properties like "display: none")

  • Implement proper delays between requests to avoid triggering rate limits

Advanced Techniques

IP Management

  • Use proxy rotation to avoid IP-based blocking

  • Implement VPNs for testing and debugging purposes

  • Consider residential proxies for more legitimate-appearing traffic

Content Access

  • Handle AJAX requests and infinite scrolling by:

    • Intercepting API calls

    • Simulating scroll events

    • Extracting data from XHR requests

Error Handling

  • Monitor for common blocking indicators:

    • HTTP status codes (401, 403, 429)

    • CAPTCHAs

    • Redirect chains

  • Implement CAPTCHA solving services when necessary

Best Practices

  • Run initial test crawls with low limits to identify potential issues

  • Monitor site performance impact and adjust crawl rates accordingly

  • Respect robots.txt while implementing custom crawl restrictions

  • Keep track of website layout changes and update scrapers accordingly

Following these techniques will help you successfully crawl even the most challenging websites while maintaining a legitimate appearance and avoiding blocks.

Browser Emulation crawler github project

Based on the search results, here are some notable browser emulation crawler projects:

Project NameDescriptionKey FeaturesGitHub Stars
Browsertrix CrawlerHigh-fidelity browser-based crawling systemCustomizable browser crawling, complex site handling~1.5K
SeleniumBrowser automation frameworkMulti-browser support, extensive ecosystem, comprehensive testing capabilities30.7K
Ulixee HeroWeb browser built specifically for scrapingBuilt-in DOM emulation, Chrome engine, browser profile emulation~8K

Key Features Comparison

Ulixee Hero

  • First modern headless browser designed specifically for scraping

  • Full DOM compliance in NodeJS

  • Advanced detection avoidance capabilities

  • Browser profile emulation system

  • Built-in TCP/TLS fingerprint protection

Browsertrix Crawler

  • High-fidelity crawling system

  • Complex site handling

  • Customizable browser-based crawling

  • Single container deployment

Selenium

  • Industry standard for browser automation

  • Supports multiple browsers

  • Extensive testing capabilities

  • Large ecosystem of tools and plugins

Advanced Capabilities

Anti-Detection Features:

  • Browser fingerprint manipulation

  • User behavior emulation

  • Network signature matching

  • TLS/TCP stack protection

Technical Integration:

  • Headless browser support

  • JavaScript rendering

  • Multi-container testing capabilities

  • Custom profile management

These tools are particularly useful for crawling JavaScript-heavy sites and those with advanced anti-bot measures.

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