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D4Vinci
Scrapling
Adaptive Python scraping framework: selectors that relearn when sites redesign, stealth fetchers that pass Cloudflare, spiders with proxy rotation and an MCP server — request to full crawl.
76,755 7,680 Python BSD-3-Clauseupdated 3 days ago
Curator's take
The modern-web answer to scraping's two chronic pains: selectors break (its parser relearns elements after redesigns via auto-save/auto-match) and bots get blocked (StealthyFetcher passes Cloudflare Turnstile out of the box). The MCP server is a quiet killer feature — your coding agent can scrape through it directly. NOT the veteran choice: younger ecosystem than Scrapy with fewer third-party answers when you're deep in the weeds, and the adaptive magic needs its cache warmed — first-run breakage still lands on you.
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Continue your stack
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Why it fitsBoth are Python scraping frameworks; Scrapling rebuilds the stack for the hostile modern web — adaptive selectors that survive redesigns, Cloudflare-passing stealth fetchers — where Scrapy relies on its ecosystem for both.
crawlee
Apify's web scraping and browser automation library for Node.js/TypeScript — HTTP and headless-browser crawlers with human-like anti-blocking defaults, queues, storage and proxies.
Why it fitsThe two modern anti-bot-aware crawling frameworks, split by language: Scrapling for Python (adaptive parsing, MCP server), Crawlee for Node/TypeScript (browser switching, Apify ecosystem).
crawl4ai
The 74k-star LLM-native crawler: turns any site into clean, RAG-ready Markdown — adaptive crawling, JS rendering, extraction strategies, Docker deploy. Python, Apache-2.0.
Why it fitsSame Python scraping job, different bets: Scrapling bets on resilience (self-healing selectors, Cloudflare-passing stealth); Crawl4AI bets on LLM-ready output and crawl orchestration. Hostile targets → Scrapling; RAG pipelines → Crawl4AI.