Scrapling

Scrapling is a web scraping framework with anti-bot bypass, stealth browser automation, and a spider framework. It provides three fetching strategies (HTTP, dynamic JS, stealth/Cloudflare) and a full CLI.

This skill is for educational and research purposes only. Users must comply with local/international data scraping laws and respect website Terms of Service.

When to Use

• Scraping static HTML pages (faster than browser tools)
• Scraping JS-rendered pages that need a real browser
• Bypassing Cloudflare Turnstile or bot detection
• Crawling multiple pages with a spider
• When the built-in web_extract tool does not return the data you need

Installation

pip install "scrapling[all]"
scrapling install

Minimal install (HTTP only, no browser):

pip install scrapling

With browser automation only:

pip install "scrapling[fetchers]"
scrapling install

Quick Reference

Approach	Class	Use When
HTTP	Fetcher / FetcherSession	Static pages, APIs, fast bulk requests
Dynamic	DynamicFetcher / DynamicSession	JS-rendered content, SPAs
Stealth	StealthyFetcher / StealthySession	Cloudflare, anti-bot protected sites
Spider	Spider	Multi-page crawling with link following

CLI Usage

Extract Static Page

scrapling extract get 'https://example.com' output.md

With CSS selector and browser impersonation:

scrapling extract get 'https://example.com' output.md \
  --css-selector '.content' \
  --impersonate 'chrome'

Extract JS-Rendered Page

scrapling extract fetch 'https://example.com' output.md \
  --css-selector '.dynamic-content' \
  --disable-resources \
  --network-idle

Extract Cloudflare-Protected Page

scrapling extract stealthy-fetch 'https://protected-site.com' output.html \
  --solve-cloudflare \
  --block-webrtc \
  --hide-canvas

POST Request

scrapling extract post 'https://example.com/api' output.json \
  --json '{"query": "search term"}'

Output Formats

The output format is determined by the file extension:

• .html -- raw HTML
• .md -- converted to Markdown
• .txt -- plain text
• .json / .jsonl -- JSON

Python: HTTP Scraping

Single Request

from scrapling.fetchers import Fetcher

page = Fetcher.get('https://quotes.toscrape.com/')
quotes = page.css('.quote .text::text').getall()
for q in quotes:
    print(q)

Session (Persistent Cookies)

from scrapling.fetchers import FetcherSession

with FetcherSession(impersonate='chrome') as session:
    page = session.get('https://example.com/', stealthy_headers=True)
    links = page.css('a::attr(href)').getall()
    for link in links[:5]:
        sub = session.get(link)
        print(sub.css('h1::text').get())

POST / PUT / DELETE

page = Fetcher.post('https://api.example.com/data', json={"key": "value"})
page = Fetcher.put('https://api.example.com/item/1', data={"name": "updated"})
page = Fetcher.delete('https://api.example.com/item/1')

With Proxy

page = Fetcher.get('https://example.com', proxy='http://user:pass@proxy:8080')

Python: Dynamic Pages (JS-Rendered)

For pages that require JavaScript execution (SPAs, lazy-loaded content):

from scrapling.fetchers import DynamicFetcher

page = DynamicFetcher.fetch('https://example.com', headless=True)
data = page.css('.js-loaded-content::text').getall()

Wait for Specific Element

page = DynamicFetcher.fetch(
    'https://example.com',
    wait_selector=('.results', 'visible'),
    network_idle=True,
)

Disable Resources for Speed

Blocks fonts, images, media, stylesheets (~25% faster):

from scrapling.fetchers import DynamicSession

with DynamicSession(headless=True, disable_resources=True, network_idle=True) as session:
    page = session.fetch('https://example.com')
    items = page.css('.item::text').getall()

Custom Page Automation

from playwright.sync_api import Page
from scrapling.fetchers import DynamicFetcher

def scroll_and_click(page: Page):
    page.mouse.wheel(0, 3000)
    page.wait_for_timeout(1000)
    page.click('button.load-more')
    page.wait_for_selector('.extra-results')

page = DynamicFetcher.fetch('https://example.com', page_action=scroll_and_click)
results = page.css('.extra-results .item::text').getall()

Python: Stealth Mode (Anti-Bot Bypass)

For Cloudflare-protected or heavily fingerprinted sites:

from scrapling.fetchers import StealthyFetcher

page = StealthyFetcher.fetch(
    'https://protected-site.com',
    headless=True,
    solve_cloudflare=True,
    block_webrtc=True,
    hide_canvas=True,
)
content = page.css('.protected-content::text').getall()

Stealth Session

from scrapling.fetchers import StealthySession

with StealthySession(headless=True, solve_cloudflare=True) as session:
    page1 = session.fetch('https://protected-site.com/page1')
    page2 = session.fetch('https://protected-site.com/page2')

Element Selection

All fetchers return a Selector object with these methods:

CSS Selectors

page.css('h1::text').get()              # First h1 text
page.css('a::attr(href)').getall()      # All link hrefs
page.css('.quote .text::text').getall() # Nested selection

XPath

page.xpath('//div[@class="content"]/text()').getall()
page.xpath('//a/@href').getall()

Find Methods

page.find_all('div', class_='quote')       # By tag + attribute
page.find_by_text('Read more', tag='a')    # By text content
page.find_by_regex(r'\$\d+\.\d{2}')       # By regex pattern

Similar Elements

Find elements with similar structure (useful for product listings, etc.):

first_product = page.css('.product')[0]
all_similar = first_product.find_similar()

Navigation

el = page.css('.target')[0]
el.parent                # Parent element
el.children              # Child elements
el.next_sibling          # Next sibling
el.prev_sibling          # Previous sibling

Python: Spider Framework

For multi-page crawling with link following:

from scrapling.spiders import Spider, Request, Response

class QuotesSpider(Spider):
    name = "quotes"
    start_urls = ["https://quotes.toscrape.com/"]
    concurrent_requests = 10
    download_delay = 1

    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)

result = QuotesSpider().start()
print(f"Scraped {len(result.items)} quotes")
result.items.to_json("quotes.json")

Multi-Session Spider

Route requests to different fetcher types:

from scrapling.fetchers import FetcherSession, AsyncStealthySession

class SmartSpider(Spider):
    name = "smart"
    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():
            if "protected" in link:
                yield Request(link, sid="stealth")
            else:
                yield Request(link, sid="fast", callback=self.parse)

Pause/Resume Crawling

spider = QuotesSpider(crawldir="./crawl_checkpoint")
spider.start()  # Ctrl+C to pause, re-run to resume from checkpoint

Pitfalls

• Browser install required: run scrapling install after pip install -- without it, DynamicFetcher and StealthyFetcher will fail
• Timeouts: DynamicFetcher/StealthyFetcher timeout is in milliseconds (default 30000), Fetcher timeout is in seconds
• Cloudflare bypass: solve_cloudflare=True adds 5-15 seconds to fetch time -- only enable when needed
• Resource usage: StealthyFetcher runs a real browser -- limit concurrent usage
• Legal: always check robots.txt and website ToS before scraping. This library is for educational and research purposes
• Python version: requires Python 3.10+