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 โ 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.
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
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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Key Features
Spiders โ A Full Crawling Framework
๐ท๏ธ Scrapy-like Spider API: Define spiders with start_urls, async parse callbacks, and Request/Response objects.
๐ Multi-Session Support: Unified interface for HTTP requests, and stealthy headless browsers in a single spider โ route requests to different sessions by ID.
๐พ Pause & Resume: Checkpoint-based crawl persistence. Press Ctrl+C for a graceful shutdown; restart to resume from where you left off.
๐ก Streaming Mode: Stream scraped items as they arrive via async for item in spider.stream() with real-time stats โ ideal for UI, pipelines, and long-running crawls.
๐ก๏ธ Blocked Request Detection: Automatic detection and retry of blocked requests with customizable logic.
๐ฆ 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
๐ Smart Element Tracking: Relocate elements after website changes using intelligent similarity algorithms.
๐ฏ Smart Flexible Selection: CSS selectors, XPath selectors, filter-based search, text search, regex search, and more.
๐ Find Similar Elements: Automatically locate elements similar to found elements.
๐ค 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)
High-Performance & battle-tested Architecture
๐ Lightning Fast: Optimized performance outperforming most Python scraping libraries.
๐ Memory Efficient: Optimized data structures and lazy loading for a minimal memory footprint.
โก Fast JSON Serialization: 10x faster than the standard library.
๐๏ธ 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
๐ฏ 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.
๐ Use it directly from the Terminal: Optionally, you can use Scrapling to scrape a URL without writing a single line of code!
๐ ๏ธ Rich Navigation API: Advanced DOM traversal with parent, sibling, and child navigation methods.
๐งฌ Enhanced Text Processing: Built-in regex, cleaning methods, and optimized string operations.
๐ Auto Selector Generation: Generate robust CSS/XPath selectors for any element.
๐ Familiar API: Similar to Scrapy/BeautifulSoup with the same pseudo-elements used in Scrapy/Parsel.
๐ 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.
๐ 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
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
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
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:
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:
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:
QuotesSpider(crawldir="./crawl_data").start()
Press Ctrl+C to pause gracefully โ 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
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:
from scrapling.parser import Selector
page = Selector("<html>...</html>")
And it works precisely the same way!
Async Session Management Examples
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:
Launch the interactive Web Scraping shell
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.
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
Performance Benchmarks
Scrapling isn't just powerfulโit'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 for methodology.
Installation
Scrapling requires Python 3.10 or higher:
pip install scrapling
This installation only includes the parser engine and its dependencies, without any fetchers or commandline dependencies.
Optional Dependencies
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:
[!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.
License
This work is licensed under the BSD-3-Clause License.
Acknowledgments
This project includes code adapted from:
Parsel (BSD License)โUsed for translator submodule
Designed & crafted with โค๏ธ by Karim Shoair.
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