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Scrapling
Adaptive web scraping that survives site changes effortlessly
Scrapling delivers adaptive web scraping that automatically adjusts to site redesigns, offering stealth, dynamic, and async fetchers, a fast parser, and a CLI for both developers and non‑programmers.
Overview
Overview
Scrapling is a Python library built for developers and data teams who need reliable web scrapers that keep working as websites evolve. Its adaptive selector engine learns from structural changes, eliminating the constant need to rewrite CSS or XPath queries.
Core Capabilities
The library ships with multiple fetchers—standard, stealthy, and full‑browser dynamic—each capable of handling anti‑bot measures, TLS fingerprint impersonation, and headless operation. A rapid parsing engine supports CSS, XPath, and BeautifulSoup‑style selectors, plus advanced navigation methods like sibling and similarity queries. Async sessions enable high‑throughput crawling, while a powerful CLI lets non‑programmers extract content directly to markdown, text, or HTML files.
Deployment
Install via pip install scrapling and integrate it into scripts, Jupyter notebooks, or CI pipelines. Use context‑aware sessions for persistent cookies and headers, or one‑off fetch calls for quick tasks. Browser‑based fetchers require a compatible Chromium/Firefox binary, which Scrapling can launch automatically in headless mode.
Highlights
Adaptive selectors that auto‑relocate after site redesigns
Stealthy and dynamic fetchers with headless browser support
Async session management for concurrent high‑volume scraping
CLI and interactive shell for no‑code content extraction
Pros
- Reduces maintenance by adapting to HTML changes
- Handles anti‑bot protections with stealth mode
- Supports both synchronous and asynchronous workflows
- Rich selector syntax across CSS, XPath, and BS4 styles
Considerations
- Browser‑based fetchers add runtime dependencies
- Adaptive mode can introduce slight performance overhead
- Learning curve for advanced session and fetcher options
- Heavier footprint compared to minimal HTML parsers
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Fit guide
Great for
- Long‑running scrapers that must survive frequent site updates
- Projects needing to bypass Cloudflare or similar anti‑bot systems
- Data pipelines requiring high‑throughput async crawling
- Users who prefer a command‑line tool for quick extraction
Not ideal when
- Simple one‑off scripts where minimal dependencies are critical
- Environments without access to a Chromium/Firefox binary
- Use cases demanding an ultra‑lightweight parsing library only
- Teams that rely exclusively on proxy rotation features not provided
How teams use it
E‑commerce price monitoring
Continues to collect product prices even after the retailer redesigns its layout, eliminating selector rewrites.
News aggregation behind Cloudflare
StealthyFetcher bypasses Cloudflare challenges to reliably extract article headlines and bodies.
Bulk data collection with async concurrency
AsyncStealthySession fetches hundreds of pages in parallel, dramatically reducing total crawl time.
Non‑programmer report generation via CLI
Users run `scrapling extract` to export web page content directly to markdown or text files without writing code.
Tech snapshot
Python98%
JavaScript2%
Dockerfile1%
Frequently asked questions
How does Scrapling's adaptive selector feature work?
When `adaptive=True` is set, Scrapling analyzes the page structure and attempts to locate the target element even if its original CSS or XPath path has changed, using similarity heuristics.
Do I need a browser installed to use Stealthy or Dynamic fetchers?
Yes, these fetchers launch a headless Chromium or Firefox instance. Scrapling will download a compatible binary if none is found on the system.
Can Scrapling be used in asynchronous Python code?
Absolutely. The library provides `AsyncStealthySession` and `AsyncDynamicSession` classes that integrate with `asyncio` for concurrent fetching.
Is there a way to run Scrapling without writing Python code?
The built‑in CLI (`scrapling extract`) lets you fetch pages and export content to HTML, markdown, or plain text directly from the command line.
What Python versions does Scrapling support?
Scrapling follows the standard Python packaging policy and supports the versions listed on its PyPI page; refer to the official documentation for the exact range.
Project at a glance
Active- Stars
- 8,817
- Watchers
- 8,817
- Forks
- 536
LicenseBSD-3-Clause
Repo age1 year old
Last commit2 days ago
Primary languagePython
Last synced yesterday