Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/D4Vinci/Scrapling/llms.txt

Use this file to discover all available pages before exploring further.

​
Prerequisites

Make sure you have Scrapling installed. If not, see the Installation guide. For the examples below, you’ll need: 
pip install "scrapling[fetchers]"
scrapling install

​
Your First Scrape

Let’s scrape a simple website using HTTP requests:
1

Import the Fetcher

from scrapling.fetchers import Fetcher
2

Fetch the page

page = Fetcher.get('https://quotes.toscrape.com/')
3

Extract data with CSS selectors

# Get all quotes
quotes = page.css('.quote .text::text').getall()
print(quotes)

# Get all authors
authors = page.css('.quote .author::text').getall()
print(authors)
The ::text pseudo-element extracts text content, similar to Scrapy/Parsel syntax.

​
Using Sessions

For multiple requests to the same domain, use sessions to maintain cookies and state: 
from scrapling.fetchers import FetcherSession

with FetcherSession(impersonate='chrome') as session:
    # First request
    page1 = session.get('https://quotes.toscrape.com/')
    quotes = page1.css('.quote .text::text').getall()
    
    # Follow pagination - cookies maintained
    page2 = session.get('https://quotes.toscrape.com/page/2/')
    more_quotes = page2.css('.quote .text::text').getall()

​
Stealthy Scraping

For websites with anti-bot protection, use the StealthyFetcher:
1

Import StealthyFetcher

from scrapling.fetchers import StealthyFetcher
2

Fetch protected pages

# Bypass Cloudflare automatically
page = StealthyFetcher.fetch(
    'https://nopecha.com/demo/cloudflare',
    solve_cloudflare=True,
    headless=True
)
3

Extract data

data = page.css('#padded_content a').getall()
print(page.status)  # 200

from scrapling.fetchers import StealthyFetcher

page = StealthyFetcher.fetch(
    'https://www.browserscan.net/bot-detection',
    headless=True,
    network_idle=True
)
print(f"Status: {page.status}")  # 200

​
Building a Spider

For larger scraping projects, use Scrapling’s spider framework:
1

Create a spider class

from scrapling.spiders import Spider, Response

class QuotesSpider(Spider):
    name = "quotes"
    start_urls = ["https://quotes.toscrape.com/"]
    concurrent_requests = 10
2

Define the parse method

    async def parse(self, response: Response):
        # Extract quotes from current page
        for quote in response.css('.quote'):
            yield {
                "text": quote.css('.text::text').get(),
                "author": quote.css('.author::text').get(),
                "tags": quote.css('.tag::text').getall(),
            }
        
        # Follow pagination
        next_page = response.css('.next a::attr(href)').get()
        if next_page:
            yield response.follow(next_page)
3

Run the spider

# Run and get results
result = QuotesSpider().start()

print(f"Scraped {len(result.items)} quotes")

# Export to JSON
result.items.to_json("quotes.json")

# Or JSONL
result.items.to_jsonl("quotes.jsonl")

​
Complete Spider Example

from scrapling.spiders import Spider, 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(),
                "tags": quote.css('.tag::text').getall(),
            }
        
        next_page = response.css('.next a::attr(href)').get()
        if next_page:
            yield response.follow(next_page)

# Run the spider
result = QuotesSpider().start()
print(f"Scraped {len(result.items)} quotes")
result.items.to_json("quotes.json")
Spiders support pause/resume, multiple session types, proxy rotation, and streaming mode. See Spider Documentation for advanced features.

​
Multi-Session Spider

Use different session types in a single spider for optimal performance: 
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):
        # Fast HTTP session for most pages
        manager.add("fast", FetcherSession(impersonate="chrome"))
        # Stealth session for protected pages
        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 stealth session
            if "protected" in link:
                yield Request(link, sid="stealth", callback=self.parse_protected)
            else:
                yield Request(link, sid="fast")
    
    async def parse_protected(self, response: Response):
        # Handle protected pages
        data = response.css('.content::text').get()
        yield {"protected_data": data}

MultiSessionSpider().start()

​
Adaptive Scraping

Scrapling can automatically relocate elements when website structure changes:
1

Enable adaptive mode

from scrapling.fetchers import StealthyFetcher

StealthyFetcher.adaptive = True
2

Save element locations

page = StealthyFetcher.fetch('https://example.com', headless=True)

# Save element signatures for future use
products = page.css('.product', auto_save=True)
3

Relocate after changes

# Later, if website structure changes
page = StealthyFetcher.fetch('https://example.com', headless=True)

# Automatically find elements using saved signatures
products = page.css('.product', adaptive=True)
Scrapling offers powerful element navigation: 
from scrapling.fetchers import Fetcher

page = Fetcher.get('https://quotes.toscrape.com/')

# 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
quotes = page.find_by_text('quote', tag='div')          # Text search

# Element navigation
first_quote = quotes[0]
author = first_quote.css('.author::text').get()
parent = first_quote.parent
children = first_quote.children
siblings = first_quote.siblings

# Find similar elements
similar = first_quote.find_similar()
See Selection Methods for comprehensive selector documentation.

​
Command Line Usage

Scrape without writing code: 
scrapling shell
  • .txt extension extracts text content
  • .md extension extracts Markdown representation
  • .html extension extracts raw HTML

​
Next Steps

You’re now ready to explore Scrapling’s advanced features:

Selection Methods

Master CSS, XPath, regex, and text search

Choose Your Fetcher

Learn when to use each fetcher type

Build Advanced Spiders

Concurrent crawls with pause/resume

Proxy Rotation

Built-in proxy rotation strategies

Interactive Shell

Speed up development with IPython

MCP Server

AI-assisted web scraping

​
Common Patterns

from scrapling.fetchers import Fetcher

page = Fetcher.get('https://quotes.toscrape.com/')

while True:
    # Extract data from current page
    quotes = page.css('.quote .text::text').getall()
    print(quotes)
    
    # Check for next page
    next_link = page.css('.next a::attr(href)').get()
    if not next_link:
        break
    
    # Fetch next page
    page = Fetcher.get(f'https://quotes.toscrape.com{next_link}')

# Get href attributes
links = page.css('a::attr(href)').getall()

# Get data attributes
product_ids = page.css('.product::attr(data-id)').getall()

# Get multiple attributes
for link in page.css('a'):
    url = link.attrib.get('href')
    title = link.attrib.get('title')

# Extract JSON from script tags
json_data = page.css('script#data::text').get()

# Parse JSON attributes
schema = page.css('[schema]').attrib['schema'].json()

# Extract all text as JSON-ready
data = {
    "title": page.css('h1::text').get(),
    "price": page.css('.price::text').get(),
    "description": page.css('.description::text').get(),
}

from scrapling.fetchers import Fetcher

try:
    page = Fetcher.get('https://example.com', timeout=10)
    
    if page.status != 200:
        print(f"Error: Status {page.status}")
    else:
        data = page.css('.content::text').get()
        
except Exception as e:
    print(f"Failed to fetch: {e}")

Build docs developers (and LLMs) love

Get started for freeTalk to us