Scrapling: Ultimate Python Web Scraping Framework
Discover Scrapling, the adaptive web scraping framework that handles everything from single requests to full-scale crawls. Bypass Cloudflare Turnstile, use smart element tracking that survives website changes, and scale with concurrent spiders featuring pause/resume. With stealth modes, proxy rotation, AI integration via MCP server, and blazing-fast performance outperforming Scrapy/Parsel, it's built for serious web scrapers. Install with pip and start scraping in minutes!
Scrapling: The Modern Web Scraping Framework That Adapts to Changes
Web scraping just got smarter with Scrapling, a battle-tested Python framework that handles everything from simple HTTP requests to enterprise-scale crawls. With 19.3k GitHub stars and daily use by hundreds of professional scrapers, this isn't just another library—it's a complete scraping ecosystem.
Key Features That Set Scrapling Apart
🕷️ Full Spider Framework
- Scrapy-like API with
start_urls, asyncparse()callbacks - Concurrent crawling with configurable limits and throttling
- Pause & Resume with checkpoint persistence (Ctrl+C friendly)
- Multi-session support: Mix HTTP, stealth browsers, and full automation
- Real-time streaming with live stats
🎯 Anti-Bot Bypass Mastery
from scrapling.fetchers import StealthyFetcher
page = StealthyFetcher.fetch('https://protected-site.com',
solve_cloudflare=True, headless=True)
- Cloudflare Turnstile/Interstitial solver out-of-the-box
- Browser fingerprint spoofing and TLS impersonation
- HTTP/3 support and stealth headers
- Automatic blocked request detection & retry
🔄 Adaptive Parsing (The Killer Feature)
Websites change. Scrapling adapts:
products = page.css('.product', adaptive=True) # Finds them even after redesign!
- Smart element relocation using similarity algorithms
- CSS, XPath, text search, regex—all with auto-recovery
- Find similar elements automatically
Lightning Performance
| Library | Text Extraction | vs Scrapling |
|---|---|---|
| Scrapling | 2.02ms | 1.0x |
| Parsel | 2.04ms | 1.01x |
| BeautifulSoup | 1584ms | 784x slower |
Quick Start in 3 Lines
from scrapling.fetchers import Fetcher
page = Fetcher.get('https://quotes.toscrape.com/')
quotes = page.css('.quote .text::text').getall()
print(quotes)
Advanced: Multi-Session Spider
class MultiSessionSpider(Spider):
def configure_sessions(self, manager):
manager.add("fast", FetcherSession())
manager.add("stealth", AsyncStealthySession(headless=True))
async def parse(self, response):
for link in response.css('a::href').getall():
if "protected" in link:
yield Request(link, sid="stealth")
else:
yield Request(link, sid="fast")
Production Ready
- 92% test coverage with full type hints
- Docker images with browsers pre-installed
- CLI tools:
scrapling shell,scrapling extract - MCP Server for AI-assisted scraping (Claude/Cursor compatible)
- PyPI:
pip install scrapling[all]
Installation
pip install "scrapling[fetchers]"
scrapling install # Downloads browsers
Scrapling respects robots.txt and ToS—use responsibly for research and authorized data collection.
Whether you're extracting product data, building datasets, or scaling crawls across thousands of domains, Scrapling delivers production-grade reliability with developer-friendly APIs.