Scrapling

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name: scrapling description: Web scraping and data extraction using the Python Scrapling library. Use to scrape static HTML pages, JavaScript-rendered pages (Playwright), and anti-bot or Cloudflare-protected sites (stealth browser). Supports CSS selectors, XPath, adaptive DOM relocation so selectors survive site redesigns, session-based scraping with cookie persistence, and outputs to JSON or Markdown. Use when asked to scrape a URL, extract text/links/tables/prices from a webpage, crawl a site, or automate web data collection.

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Scrapling

Extract structured website data with resilient selection patterns, adaptive relocation, and the right Scrapling fetcher mode for each target.

Workflow

1. Identify target type before writing code: - Use Fetcher for static pages and API-like HTML responses. - Use DynamicFetcher when JavaScript rendering is required. - Use StealthyFetcher when anti-bot protection or browser fingerprinting issues are likely. 2. Choose output contract first: - Return JSON for pipelines/automation. - Return Markdown/text for summarization or RAG ingestion. - Keep stable field names even if selector strategy changes. 3. Implement selectors in this order: - Start with CSS selectors and pseudo-elements (for example ::text, ::attr(href)). - Fall back to XPath for ambiguous DOM structure. - Enable adaptive relocation for brittle or changing pages. 4. Add safety controls: - Respect target site terms and legal boundaries. - Add timeouts, retries, and explicit error handling. - Log status code, URL, and selector misses for debugging. 5. Validate on at least 2 pages: - Test one happy path and one edge case page. - Confirm required fields are non-empty. - Keep extraction deterministic (no hidden random choices).

Quick Setup

1. Install base package: - pip install scrapling 2. Install fetchers when browser-based fetching is needed: - pip install "scrapling[fetchers]" - scrapling install - python3 -m playwright install (required for DynamicFetcher and StealthyFetcher) 3. Install optional extras as needed: - pip install "scrapling[shell]" for shell + extract commands - pip install "scrapling[ai]" for MCP capabilities

Execution Patterns

Pattern: One-off terminal extraction

Use Scrapling CLI for fastest no-code extraction:

scrapling extract get "https://example.com" content.md --css-selector "main"

Pattern: Python extraction script

Use the bundled helper:

# Static page (default)
python scripts/extract_with_scrapling.py --url "https://example.com" --css "h1::text"
JavaScript-rendered page
python scripts/extract_with_scrapling.py --url "https://example.com" --fetcher dynamic --css "h1::text"
Anti-bot protected page
python scripts/extract_with_scrapling.py --url "https://example.com" --fetcher stealthy --css "h1::text"

Pattern: Session-based scraping

Use session classes when cookies/state must persist across requests.

from scrapling.fetchers import FetcherSession
session = FetcherSession()
login_page = session.post("https://example.com/login", data={"user": "...", "pass": "..."})
protected_page = session.get("https://example.com/dashboard")
headline = protected_page.css_first("h1::text")

Use StealthySession or DynamicSession as drop-in replacements for anti-bot or JS-rendered targets.

Pattern: DOM change resilience

Use auto_save=True on initial capture and retry with adaptive selection on later runs when selectors break.

from scrapling.fetchers import Fetcher
First run: saves DOM snapshot so adaptive relocation can work later
page = Fetcher.auto_match("https://example.com", auto_save=True, disable_adaptive=False)
price = page.css_first(".price::text")
Later runs: automatically relocates the selector even if the DOM changed
page = Fetcher.auto_match("https://example.com", auto_save=False, disable_adaptive=False)
price = page.css_first(".price::text")

References

Use scrapling-reference.md for fetcher/API examples and selector patterns.

Use extract_with_scrapling.py for a reusable CLI script template.