Effortless Web Scraping for the Modern Web

<strong>Selection methods</strong>
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<strong>Fetchers</strong>
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<strong>Spiders</strong>
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<strong>Proxy Rotation</strong>
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<strong>CLI</strong>
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<strong>MCP</strong>

Scrapling is an adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl.

Its parser learns from website changes and automatically relocates your elements when pages update. Its fetchers bypass anti-bot systems like Cloudflare Turnstile out of the box. And its spider framework lets you scale up to concurrent, multi-session crawls with pause/resume, automatic proxy rotation, and a crawl speed that adapts to how fast each website responds and backs off when it starts blocking you - all in a few lines of Python. One library, zero compromises.

Blazing fast crawls with real-time stats and streaming. Built by Web Scrapers for Web Scrapers and regular users, there's something for everyone.

from scrapling.fetchers import Fetcher, AsyncFetcher, StealthyFetcher, DynamicFetcher
StealthyFetcher.adaptive = True
p = StealthyFetcher.fetch('https://example.com', headless=True, network_idle=True)  # Fetch website under the radar!
products = p.css('.product', auto_save=True)                                        # Scrape data that survives website design changes!
products = p.css('.product', adaptive=True)                                         # Later, if the website structure changes, pass `adaptive=True` to find them!

Or scale up to full crawls

from scrapling.spiders import Spider, Response

class MySpider(Spider):
  name = "demo"
  start_urls = ["https://example.com/"]

  async def parse(self, response: Response):
      for item in response.css('.product'):
          yield {"title": item.css('h2::text').get()}

MySpider().start()

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