scrapling

Scrapling -- Local Stealth Web Scraping

100% local Python library (BSD-3, D4Vinci/Scrapling). No API keys, no cloud dependencies. Built-in Cloudflare solver, TLS impersonation, and adaptive element tracking.

When to Use Scrapling vs Firecrawl

Need	Use	Why
Clean markdown from a URL	firecrawl scrape --only-main-content	Optimized for LLM markdown conversion
Bypass Cloudflare/anti-bot	scrapling stealth fetch	Built-in Turnstile solver, Patchright stealth
Extract specific elements	scrapling with CSS/XPath selectors	Element-level precision, adaptive tracking
No API key available	scrapling	100% local, zero credentials
Batch cloud scraping	firecrawl crawl / batch-scrape	Cloud infrastructure, parallel processing
Site redesign resilience	scrapling adaptive mode	SQLite-backed similarity matching
Full-site concurrent crawl	scrapling Spider framework	Scrapy-like with pause/resume
Web search + scrape	firecrawl search --scrape	Combined search + extraction

Installation

Run once to set up Scrapling with all features:

~/.claude/skills/scrapling/scripts/scrapling_install.sh

Installs scrapling[all] via uv, downloads Chromium + system dependencies, and verifies all fetchers load.

Quick Start -- Stdout Wrapper

The wrapper uses Scrapling's Python API directly (faster than CLI, avoids curl_cffi cert issues) and outputs to stdout for piping into filter_web_results.py:

# Basic HTTP fetch (fastest, TLS impersonation)
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://example.com

# Stealth mode (Patchright, anti-bot bypass)
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://protected.site --stealth

# Stealth + Cloudflare solver
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://cf-protected.site --stealth --solve-cloudflare

# Dynamic (Playwright Chromium, JS rendering)
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://js-heavy.site --dynamic

# With CSS selector for targeted extraction
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://example.com --css ".product-list"

# Pipe through firecrawl's filter for token efficiency
python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py https://example.com --stealth | \
  python3 ~/.claude/skills/firecrawl/scripts/filter_web_results.py --sections "Pricing" --max-chars 5000

Full path: python3 ~/.claude/skills/scrapling/scripts/scrapling_fetch.py Flags: --stealth, --dynamic, --css SELECTOR, --solve-cloudflare, --impersonate BROWSER, --format {text,html}, --no-headless, --timeout SECONDS

For --network-idle, --real-chrome, or POST requests, use the CLI direct path below.

Quick Start -- CLI Direct

For file-based output (Scrapling's native CLI):

# HTTP fetch -> markdown
scrapling extract get 'https://example.com' content.md

# HTTP with CSS selector and browser impersonation
scrapling extract get 'https://example.com' content.md --css-selector '.main-content' --impersonate chrome

# Dynamic fetch (Playwright, JS rendering)
scrapling extract fetch 'https://example.com' content.md

# Stealth with Cloudflare bypass
scrapling extract stealthy-fetch 'https://protected.site' content.md --solve-cloudflare

# Stealth with CSS selector, visible browser for debugging
scrapling extract stealthy-fetch 'https://site.com' content.md --css-selector '.data' --no-headless

Three Fetcher Tiers

CLI verb	Engine	Stealth	JS	Speed
get	curl_cffi (HTTP)	TLS impersonation	No	Fast
fetch	Playwright/Chromium	Medium	Yes	Medium
stealthy-fetch	Patchright/Chrome	Maximum	Yes	Slower

Python API

For element-level extraction, automation, or when the CLI is insufficient:

from scrapling.fetchers import Fetcher, StealthyFetcher, DynamicFetcher

# Simple HTTP fetch with CSS extraction
page = Fetcher.get('https://example.com', impersonate='chrome')
titles = page.css('.item h2::text').getall()
links = page.css('a::attr(href)').getall()

# Stealth with Cloudflare bypass
page = StealthyFetcher.fetch('https://protected.site',
    headless=True, solve_cloudflare=True,
    hide_canvas=True, block_webrtc=True)
data = page.css('.content').get_all_text()

# Page automation (login, click, fill)
def login(page):
    page.fill('#username', 'user')
    page.fill('#password', 'pass')
    page.click('#submit')

page = StealthyFetcher.fetch('https://app.example.com', page_action=login)

Parsing (no fetching)

from scrapling.parser import Selector

page = Selector("<html>...</html>")
page.css('.item::text').getall()       # CSS with pseudo-elements
page.xpath('//div[@class="item"]')     # XPath
page.find_all('div', class_='item')    # BeautifulSoup-style
page.find_by_text('Add to Cart')       # Text search
page.find_by_regex(r'Price: \$\d+')    # Regex search

Adaptive Scraping

Scrapling's signature feature. Elements are fingerprinted to SQLite and relocated by similarity scoring after site redesigns.

from scrapling.fetchers import Fetcher

Fetcher.adaptive = True
page = Fetcher.get('https://example.com')

# First run: save element fingerprint
products = page.css('.product-list', auto_save=True)

# Later, after site redesign breaks the selector:
products = page.css('.product-list', adaptive=True)  # Still finds it

Read: references/adaptive-scraping.md

Spider Framework

For full-site crawling with concurrency, pause/resume, and session routing:

from scrapling.spiders import Spider, Response, Request
from scrapling.fetchers import FetcherSession, StealthySession

class ResearchSpider(Spider):
    name = "research"
    start_urls = ["https://example.com/"]
    concurrent_requests = 10

    def configure_sessions(self, manager):
        manager.add("fast", FetcherSession(impersonate="chrome"))
        manager.add("stealth", StealthySession(headless=True), lazy=True)

    async def parse(self, response: Response):
        for link in response.css('a::attr(href)').getall():
            if "protected" in link:
                yield Request(link, sid="stealth")
            else:
                yield Request(link, sid="fast")
        for item in response.css('.article'):
            yield {"title": item.css('h2::text').get(), "url": response.url}

result = ResearchSpider().start(crawldir="./data")  # Pause/resume enabled
result.items.to_json("output.json")

Troubleshooting

• Browser not found: Run scrapling install to download browser dependencies
• Import error on fetchers: Install the full package: uv pip install "scrapling[all]"
• Cloudflare still blocking: Combine flags: --solve-cloudflare --block-webrtc --hide-canvas
• SSL cert error with HTTP fetcher: curl_cffi's bundled CA certs can be stale on macOS/pyenv. The wrapper handles this automatically (verify=False). For Python API, pass verify=False to Fetcher.get().
• Slow stealthy fetch: Expected--browser automation is inherently slower than HTTP requests. Use get (HTTP) when stealth is not needed.

Reference Documentation

File	Contents
references/cli-reference.md	Full CLI extract command reference (get, post, fetch, stealthy-fetch)
references/python-api-reference.md	Python API (Fetcher, DynamicFetcher, StealthyFetcher, Sessions, Spiders)
references/adaptive-scraping.md	Adaptive element tracking deep-dive (save, match, similarity scoring)