headless-web-scraping
Acerca de
Esta habilidad proporciona un robusto raspado web para sitios protegidos contra bots y con contenido renderizado en JavaScript, utilizando el sistema de captura de tres niveles de la biblioteca scrapling. Selecciona automáticamente el método apropiado—desde HTTP básico hasta Chromium sigiloso o automatización completa del navegador—basándose en las defensas del sitio y configura la navegación sin interfaz gráfica. Los desarrolladores deben usarla cuando WebFetch falle, necesitando extracción de datos estructurados mediante selectores CSS y recorrido del DOM en páginas complejas.
Instalación rápida
Claude Code
Recomendadonpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/headless-web-scrapingCopia y pega este comando en Claude Code para instalar esta habilidad
Documentación
Headless Web Scraping
Extract from resistant pages (JS-rendered, Cloudflare, dynamic SPAs) via scrapling 3-tier fetcher + CSS extraction.
Use When
- JS rendering (SPA, React, Vue)
- Anti-bot (Cloudflare Turnstile, TLS fingerprint)
- Structured multi-element via CSS
WebFetch/requests.get()empty or blocked- Tabular/list/repeated DOM at scale
In
- Required: URL(s)
- Required: data to extract (CSS selectors, field names, target desc)
- Optional: fetcher tier override (default: auto)
- Optional: out format (default JSON; CSV, dict)
- Optional: rate limit sec (default 1)
Do
Step 1: Select tier
# Decision matrix:
# 1. Fetcher — static HTML, no JS, no anti-bot (fastest)
# 2. StealthyFetcher — Cloudflare/Turnstile, TLS fingerprint checks
# 3. DynamicFetcher — JS-rendered SPAs, click/scroll interactions
# Quick probe: try Fetcher first, escalate on failure
from scrapling import Fetcher
fetcher = Fetcher()
response = fetcher.get("https://example.com/target-page")
if response.status == 200 and response.get_all_text():
print("Fetcher tier sufficient")
else:
print("Escalate to StealthyFetcher or DynamicFetcher")
| Signal | Recommended Tier |
|---|---|
| Static HTML, no protection | Fetcher |
| 403/503, Cloudflare challenge page | StealthyFetcher |
| Page loads but content area is empty | DynamicFetcher |
| Need to click buttons or scroll | DynamicFetcher |
| altcha CAPTCHA present | None (cannot be automated) |
→ 1 of 3 tiers. Modern sites → StealthyFetcher usual start.
If err: all 3 blocked → check altcha CAPTCHA (PoW, cannot bypass). Document limitation + manual extraction.
Step 2: Configure
from scrapling import Fetcher, StealthyFetcher, DynamicFetcher
# Tier 1: Fast HTTP with TLS fingerprint impersonation
fetcher = Fetcher()
fetcher.configure(
timeout=30,
retries=3,
follow_redirects=True
)
# Tier 2: Headless Chromium with anti-detection
fetcher = StealthyFetcher()
fetcher.configure(
headless=True,
timeout=60,
network_idle=True # wait for all network requests to settle
)
# Tier 3: Full browser automation
fetcher = DynamicFetcher()
fetcher.configure(
headless=True,
timeout=90,
network_idle=True,
wait_selector="div.results" # wait for specific element before extracting
)
→ Fetcher configured + ready. No err on init. Stealth/Dynamic → Chromium auto-managed first run.
If err:
playwright/ browser binary missing →python -m playwright install chromiumconfigure()timeout → increase timeout or check network- Import err →
pip install scrapling
Step 3: Fetch + extract
# Fetch the page
response = fetcher.get("https://example.com/target-page")
# Single element extraction
title = response.find("h1.page-title")
if title:
print(title.get_all_text())
# Multiple elements
items = response.find_all("div.result-item")
for item in items:
name = item.find("span.name")
price = item.find("span.price")
print(f"{name.get_all_text()}: {price.get_all_text()}")
# Get attribute values
links = response.find_all("a.product-link")
urls = [link.get("href") for link in links]
# Get raw HTML content of an element
detail_html = response.find("div.description").html_content
API ref:
| Method | Purpose |
|---|---|
response.find("selector") | First matching element |
response.find_all("selector") | All matching elements |
element.get("attr") | Attribute value (href, src, data-*) |
element.get_all_text() | All text content, recursively |
element.html_content | Raw inner HTML |
→ Extracted data matches visible content. Non-None elements, non-empty text on populated pages.
If err:
find()→None→ inspectresponse.html_contentfor actual HTML; selectors may differ- Empty
get_all_text()→ shadow DOM / iframe →DynamicFetcherw/wait_selector - NO
.css_first()→ not scrapling API (other lib confusion)
Step 4: Handle failures + edge cases
import time
def scrape_with_fallback(url, selector):
"""Try each fetcher tier in order, with CAPTCHA detection."""
tiers = [
("Fetcher", Fetcher),
("StealthyFetcher", StealthyFetcher),
("DynamicFetcher", DynamicFetcher),
]
for tier_name, tier_class in tiers:
fetcher = tier_class()
fetcher.configure(headless=True, timeout=60)
try:
response = fetcher.get(url)
except Exception as error:
print(f"{tier_name} failed: {error}")
continue
# Detect CAPTCHA / challenge pages
page_text = response.get_all_text().lower()
if "altcha" in page_text or "proof of work" in page_text:
print(f"altcha CAPTCHA detected -- cannot automate")
return None
if response.status == 403 or response.status == 503:
print(f"{tier_name} blocked (HTTP {response.status}), escalating")
continue
result = response.find(selector)
if result and result.get_all_text().strip():
return result.get_all_text()
print(f"{tier_name} returned empty content, escalating")
print("All tiers exhausted. Manual extraction required.")
return None
→ Returns text on success, None + diagnostic on fail. CAPTCHA detected + reported not retried.
If err:
- All 403 → site blocks all automation (WIPO, TMview, gov DBs). Document as manual access.
- Timeout → slow CDN → increase to 120s.
- Session/cookie errs → login required → add cookie handling / auth.
Step 5: Rate limit + ethical
import time
import urllib.robotparser
def check_robots_txt(base_url, target_path):
"""Check if scraping is allowed by robots.txt."""
rp = urllib.robotparser.RobotFileParser()
rp.set_url(f"{base_url}/robots.txt")
rp.read()
return rp.can_fetch("*", f"{base_url}{target_path}")
def scrape_urls(urls, selector, delay=1.0):
"""Scrape multiple URLs with rate limiting."""
results = []
fetcher = StealthyFetcher()
fetcher.configure(headless=True, timeout=60)
for url in urls:
response = fetcher.get(url)
data = response.find(selector)
if data:
results.append(data.get_all_text())
time.sleep(delay) # respect the server
return results
Ethical checklist:
robots.txtfirst → respectDisallow- Min 1-sec delay
- Descriptive User-Agent
- No personal data w/o legal basis
- Cache locally → avoid redundant reqs
- 429 → stop immediately
→ Controlled rate. robots.txt checked pre-bulk. No 429.
If err:
- 429 → increase delay 3-5 sec, or stop + retry later
robots.txtdisallow → respect, do not override- IP ban → stop immediately. If legit access (public, ToS-permit, robots-respect) must continue → see
rotate-scraping-proxiesfor network-layer escalation
Check
- Correct tier (not over/under)
-
configure()used (not deprecated constructor kwargs) - Selectors match actual structure (verified vs source)
-
.find()/.find_all()used (not.css_first()) - CAPTCHA detection (altcha reported, not retried)
- Rate limit for multi-URL
-
robots.txtchecked pre-bulk - Extracted data non-empty + correct
Traps
.css_first()instead.find(): scrapling uses.find()/.find_all()..css_first()= diff lib →AttributeError.- Start w/ DynamicFetcher: try Fetcher first. Dynamic 10-50× slower (full browser startup).
- Constructor kwargs: scrapling v0.4.x deprecated → always
configure(). - Ignore altcha: no tier solves altcha PoW → detect early + fallback manual.
- No rate limit: even w/o 429 → IP ban / service degradation.
- Stable selectors: CSS changes frequently → validate before each campaign.
→
rotate-scraping-proxies— network-layer escalation when client-side stealth exhausteduse-graphql-api— GraphQL endpoint > scrapingserialize-data-formats— JSON/CSV conversiondeploy-searxng— self-hosted aggregatorforage-solutions— broader info gathering
Repositorio GitHub
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