Effortless Web Scraping for the Modern Web

Selection methods · Fetchers · Spiders · Proxy Rotation · CLI · MCP

Scrapling is an adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl. Its parser learns from website changes and automatically relocates your elements when pages update. Its fetchers bypass anti-bot systems like Cloudflare Turnstile out of the box. And its spider framework lets you scale up to concurrent, multi-session crawls with pause/resume and automatic proxy rotation - all in a few lines of Python. One library, zero compromises. Blazing fast crawls with real-time stats and streaming. Built by Web Scrapers for Web Scrapers and regular users, there's something for everyone. ```python from scrapling.fetchers import Fetcher, AsyncFetcher, StealthyFetcher, DynamicFetcher StealthyFetcher.adaptive = True p = StealthyFetcher.fetch('https://example.com', headless=True, network_idle=True) # Fetch website under the radar! products = p.css('.product', auto_save=True) # Scrape data that survives website design changes! products = p.css('.product', adaptive=True) # Later, if the website structure changes, pass `adaptive=True` to find them! ``` Or scale up to full crawls ```python from scrapling.spiders import Spider, Response class MySpider(Spider): name = "demo" start_urls = ["https://example.com/"] async def parse(self, response: Response): for item in response.css('.product'): yield {"title": item.css('h2::text').get()} MySpider().start() ```

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_{Do you want to show your ad here? Click [here](https://github.com/sponsors/D4Vinci) and choose the tier that suites you!} --- ## Key Features ### Spiders - A Full Crawling Framework - 🕷️ **Scrapy-like Spider API**: Define spiders with `start_urls`, async `parse` callbacks, and `Request`/`Response` objects. - ⚡ **Concurrent Crawling**: Configurable concurrency limits, per-domain throttling, and download delays. - 🔄 **Multi-Session Support**: Unified interface for HTTP requests, and stealthy headless browsers in a single spider - route requests to different sessions by ID. - 💾 **Pause & Resume**: Checkpoint-based crawl persistence. Press Ctrl+C for a graceful shutdown; restart to resume from where you left off. - 📡 **Streaming Mode**: Stream scraped items as they arrive via `async for item in spider.stream()` with real-time stats - ideal for UI, pipelines, and long-running crawls. - 🛡️ **Blocked Request Detection**: Automatic detection and retry of blocked requests with customizable logic. - 📦 **Built-in Export**: Export results through hooks and your own pipeline or the built-in JSON/JSONL with `result.items.to_json()` / `result.items.to_jsonl()` respectively. ### Advanced Websites Fetching with Session Support - **HTTP Requests**: Fast and stealthy HTTP requests with the `Fetcher` class. Can impersonate browsers' TLS fingerprint, headers, and use HTTP/3. - **Dynamic Loading**: Fetch dynamic websites with full browser automation through the `DynamicFetcher` class supporting Playwright's Chromium and Google's Chrome. - **Anti-bot Bypass**: Advanced stealth capabilities with `StealthyFetcher` and fingerprint spoofing. Can easily bypass all types of Cloudflare's Turnstile/Interstitial with automation. - **Session Management**: Persistent session support with `FetcherSession`, `StealthySession`, and `DynamicSession` classes for cookie and state management across requests. - **Proxy Rotation**: Built-in `ProxyRotator` with cyclic or custom rotation strategies across all session types, plus per-request proxy overrides. - **Domain Blocking**: Block requests to specific domains (and their subdomains) in browser-based fetchers. - **Async Support**: Complete async support across all fetchers and dedicated async session classes. ### Adaptive Scraping & AI Integration - 🔄 **Smart Element Tracking**: Relocate elements after website changes using intelligent similarity algorithms. - 🎯 **Smart Flexible Selection**: CSS selectors, XPath selectors, filter-based search, text search, regex search, and more. - 🔍 **Find Similar Elements**: Automatically locate elements similar to found elements. - 🤖 **MCP Server to be used with AI**: Built-in MCP server for AI-assisted Web Scraping and data extraction. The MCP server features powerful, custom capabilities that leverage Scrapling to extract targeted content before passing it to the AI (Claude/Cursor/etc), thereby speeding up operations and reducing costs by minimizing token usage. ([demo video](https://www.youtube.com/watch?v=qyFk3ZNwOxE)) ### High-Performance & battle-tested Architecture - 🚀 **Lightning Fast**: Optimized performance outperforming most Python scraping libraries. - 🔋 **Memory Efficient**: Optimized data structures and lazy loading for a minimal memory footprint. - ⚡ **Fast JSON Serialization**: 10x faster than the standard library. - 🏗️ **Battle tested**: Not only does Scrapling have 92% test coverage and full type hints coverage, but it has been used daily by hundreds of Web Scrapers over the past year. ### Developer/Web Scraper Friendly Experience - 🎯 **Interactive Web Scraping Shell**: Optional built-in IPython shell with Scrapling integration, shortcuts, and new tools to speed up Web Scraping scripts development, like converting curl requests to Scrapling requests and viewing requests results in your browser. - 🚀 **Use it directly from the Terminal**: Optionally, you can use Scrapling to scrape a URL without writing a single line of code! - 🛠️ **Rich Navigation API**: Advanced DOM traversal with parent, sibling, and child navigation methods. - 🧬 **Enhanced Text Processing**: Built-in regex, cleaning methods, and optimized string operations. - 📝 **Auto Selector Generation**: Generate robust CSS/XPath selectors for any element. - 🔌 **Familiar API**: Similar to Scrapy/BeautifulSoup with the same pseudo-elements used in Scrapy/Parsel. - 📘 **Complete Type Coverage**: Full type hints for excellent IDE support and code completion. The entire codebase is automatically scanned with **PyRight** and **MyPy** with each change. - 🔋 **Ready Docker image**: With each release, a Docker image containing all browsers is automatically built and pushed. ## Getting Started Let's give you a quick glimpse of what Scrapling can do without deep diving. ### Basic Usage HTTP requests with session support ```python from scrapling.fetchers import Fetcher, FetcherSession with FetcherSession(impersonate='chrome') as session: # Use latest version of Chrome's TLS fingerprint page = session.get('https://quotes.toscrape.com/', stealthy_headers=True) quotes = page.css('.quote .text::text').getall() # Or use one-off requests page = Fetcher.get('https://quotes.toscrape.com/') quotes = page.css('.quote .text::text').getall() ``` Advanced stealth mode ```python from scrapling.fetchers import StealthyFetcher, StealthySession with StealthySession(headless=True, solve_cloudflare=True) as session: # Keep the browser open until you finish page = session.fetch('https://nopecha.com/demo/cloudflare', google_search=False) data = page.css('#padded_content a').getall() # Or use one-off request style, it opens the browser for this request, then closes it after finishing page = StealthyFetcher.fetch('https://nopecha.com/demo/cloudflare') data = page.css('#padded_content a').getall() ``` Full browser automation ```python from scrapling.fetchers import DynamicFetcher, DynamicSession with DynamicSession(headless=True, disable_resources=False, network_idle=True) as session: # Keep the browser open until you finish page = session.fetch('https://quotes.toscrape.com/', load_dom=False) data = page.xpath('//span[@class="text"]/text()').getall() # XPath selector if you prefer it # Or use one-off request style, it opens the browser for this request, then closes it after finishing page = DynamicFetcher.fetch('https://quotes.toscrape.com/') data = page.css('.quote .text::text').getall() ``` ### Spiders Build full crawlers with concurrent requests, multiple session types, and pause/resume: ```python from scrapling.spiders import Spider, Request, Response class QuotesSpider(Spider): name = "quotes" start_urls = ["https://quotes.toscrape.com/"] concurrent_requests = 10 async def parse(self, response: Response): for quote in response.css('.quote'): yield { "text": quote.css('.text::text').get(), "author": quote.css('.author::text').get(), } next_page = response.css('.next a') if next_page: yield response.follow(next_page[0].attrib['href']) result = QuotesSpider().start() print(f"Scraped {len(result.items)} quotes") result.items.to_json("quotes.json") ``` Use multiple session types in a single spider: ```python from scrapling.spiders import Spider, Request, Response from scrapling.fetchers import FetcherSession, AsyncStealthySession class MultiSessionSpider(Spider): name = "multi" start_urls = ["https://example.com/"] def configure_sessions(self, manager): manager.add("fast", FetcherSession(impersonate="chrome")) manager.add("stealth", AsyncStealthySession(headless=True), lazy=True) async def parse(self, response: Response): for link in response.css('a::attr(href)').getall(): # Route protected pages through the stealth session if "protected" in link: yield Request(link, sid="stealth") else: yield Request(link, sid="fast", callback=self.parse) # explicit callback ``` Pause and resume long crawls with checkpoints by running the spider like this: ```python QuotesSpider(crawldir="./crawl_data").start() ``` Press Ctrl+C to pause gracefully - progress is saved automatically. Later, when you start the spider again, pass the same `crawldir`, and it will resume from where it stopped. ### Advanced Parsing & Navigation ```python from scrapling.fetchers import Fetcher # Rich element selection and navigation page = Fetcher.get('https://quotes.toscrape.com/') # Get quotes with multiple selection methods quotes = page.css('.quote') # CSS selector quotes = page.xpath('//div[@class="quote"]') # XPath quotes = page.find_all('div', {'class': 'quote'}) # BeautifulSoup-style # Same as quotes = page.find_all('div', class_='quote') quotes = page.find_all(['div'], class_='quote') quotes = page.find_all(class_='quote') # and so on... # Find element by text content quotes = page.find_by_text('quote', tag='div') # Advanced navigation quote_text = page.css('.quote')[0].css('.text::text').get() quote_text = page.css('.quote').css('.text::text').getall() # Chained selectors first_quote = page.css('.quote')[0] author = first_quote.next_sibling.css('.author::text') parent_container = first_quote.parent # Element relationships and similarity similar_elements = first_quote.find_similar() below_elements = first_quote.below_elements() ``` You can use the parser right away if you don't want to fetch websites like below: ```python from scrapling.parser import Selector page = Selector("...") ``` And it works precisely the same way! ### Async Session Management Examples ```python import asyncio from scrapling.fetchers import FetcherSession, AsyncStealthySession, AsyncDynamicSession async with FetcherSession(http3=True) as session: # `FetcherSession` is context-aware and can work in both sync/async patterns page1 = session.get('https://quotes.toscrape.com/') page2 = session.get('https://quotes.toscrape.com/', impersonate='firefox135') # Async session usage async with AsyncStealthySession(max_pages=2) as session: tasks = [] urls = ['https://example.com/page1', 'https://example.com/page2'] for url in urls: task = session.fetch(url) tasks.append(task) print(session.get_pool_stats()) # Optional - The status of the browser tabs pool (busy/free/error) results = await asyncio.gather(*tasks) print(session.get_pool_stats()) ``` ## CLI & Interactive Shell Scrapling includes a powerful command-line interface: [![asciicast](https://asciinema.org/a/736339.svg)](https://asciinema.org/a/736339) Launch the interactive Web Scraping shell ```bash scrapling shell ``` Extract pages to a file directly without programming (Extracts the content inside the `body` tag by default). If the output file ends with `.txt`, then the text content of the target will be extracted. If it ends in `.md`, it will be a Markdown representation of the HTML content; if it ends in `.html`, it will be the HTML content itself. ```bash scrapling extract get 'https://example.com' content.md scrapling extract get 'https://example.com' content.txt --css-selector '#fromSkipToProducts' --impersonate 'chrome' # All elements matching the CSS selector '#fromSkipToProducts' scrapling extract fetch 'https://example.com' content.md --css-selector '#fromSkipToProducts' --no-headless scrapling extract stealthy-fetch 'https://nopecha.com/demo/cloudflare' captchas.html --css-selector '#padded_content a' --solve-cloudflare ``` > [!NOTE] > There are many additional features, but we want to keep this page concise, including the MCP server and the interactive Web Scraping Shell. Check out the full documentation [here](https://scrapling.readthedocs.io/en/latest/) ## Performance Benchmarks Scrapling isn't just powerful-it's also blazing fast. The following benchmarks compare Scrapling's parser with the latest versions of other popular libraries. ### Text Extraction Speed Test (5000 nested elements) | # | Library | Time (ms) | vs Scrapling | |---|:-----------------:|:---------:|:------------:| | 1 | Scrapling | 2.02 | 1.0x | | 2 | Parsel/Scrapy | 2.04 | 1.01 | | 3 | Raw Lxml | 2.54 | 1.257 | | 4 | PyQuery | 24.17 | ~12x | | 5 | Selectolax | 82.63 | ~41x | | 6 | MechanicalSoup | 1549.71 | ~767.1x | | 7 | BS4 with Lxml | 1584.31 | ~784.3x | | 8 | BS4 with html5lib | 3391.91 | ~1679.1x | ### Element Similarity & Text Search Performance Scrapling's adaptive element finding capabilities significantly outperform alternatives: | Library | Time (ms) | vs Scrapling | |-------------|:---------:|:------------:| | Scrapling | 2.39 | 1.0x | | AutoScraper | 12.45 | 5.209x | > All benchmarks represent averages of 100+ runs. See [benchmarks.py](https://github.com/D4Vinci/Scrapling/blob/main/benchmarks.py) for methodology. ## Installation Scrapling requires Python 3.10 or higher: ```bash pip install scrapling ``` This installation only includes the parser engine and its dependencies, without any fetchers or commandline dependencies. ### Optional Dependencies 1. If you are going to use any of the extra features below, the fetchers, or their classes, you will need to install fetchers' dependencies and their browser dependencies as follows: ```bash pip install "scrapling[fetchers]" scrapling install # normal install scrapling install --force # force reinstall ``` This downloads all browsers, along with their system dependencies and fingerprint manipulation dependencies. Or you can install them from the code instead of running a command like this: ```python from scrapling.cli import install install([], standalone_mode=False) # normal install install(["--force"], standalone_mode=False) # force reinstall ``` 2. Extra features: - Install the MCP server feature: ```bash pip install "scrapling[ai]" ``` - Install shell features (Web Scraping shell and the `extract` command): ```bash pip install "scrapling[shell]" ``` - Install everything: ```bash pip install "scrapling[all]" ``` Remember that you need to install the browser dependencies with `scrapling install` after any of these extras (if you didn't already) ### Docker You can also install a Docker image with all extras and browsers with the following command from DockerHub: ```bash docker pull pyd4vinci/scrapling ``` Or download it from the GitHub registry: ```bash docker pull ghcr.io/d4vinci/scrapling:latest ``` This image is automatically built and pushed using GitHub Actions and the repository's main branch. ## Contributing We welcome contributions! Please read our [contributing guidelines](https://github.com/D4Vinci/Scrapling/blob/main/CONTRIBUTING.md) before getting started. ## Disclaimer > [!CAUTION] > This library is provided for educational and research purposes only. By using this library, you agree to comply with local and international data scraping and privacy laws. The authors and contributors are not responsible for any misuse of this software. Always respect the terms of service of websites and robots.txt files. ## 🎓 Citations If you have used our library for research purposes please quote us with the following reference: ```text @misc{scrapling, author = {Karim Shoair}, title = {Scrapling}, year = {2024}, url = {https://github.com/D4Vinci/Scrapling}, note = {An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!} } ``` ## License This work is licensed under the BSD-3-Clause License. ## Acknowledgments This project includes code adapted from: - Parsel (BSD License)-Used for [translator](https://github.com/D4Vinci/Scrapling/blob/main/scrapling/core/translator.py) submodule ---

Designed & crafted with ❤️ by Karim Shoair.

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Effortless Web Scraping for the Modern Web