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Scrapling

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Tommy-yw
scrapling

Web scraping with Scrapling - HTTP fetching, stealth browser automation, Cloudflare bypass, and spider crawling via CLI and Python.

Overview

PublisherTommy-yw
RepositoryRunbookHermes
Skill namescrapling
Stars
546
Forks
41
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Tommy-yw on GitHub. Read the source before you install it.

Installation

Install the Scrapling AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Tommy-yw/RunbookHermes/tree/main/optional-skills/research/scrapling
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Tommy-yw/RunbookHermes.git /tmp/RunbookHermes
mkdir -p .claude/skills
cp -r /tmp/RunbookHermes/optional-skills/research/scrapling .claude/skills/scrapling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scrapling in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Scrapling on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Scrapling is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

bash
pip install "scrapling[all]"
scrapling install

Minimal install (HTTP only, no browser):

bash
pip install scrapling

With browser automation only:

bash
pip install "scrapling[fetchers]"
scrapling install

Quick Reference

ApproachClassUse When
HTTPFetcher / FetcherSessionStatic pages, APIs, fast bulk requests
DynamicDynamicFetcher / DynamicSessionJS-rendered content, SPAs
StealthStealthyFetcher / StealthySessionCloudflare, anti-bot protected sites
SpiderSpiderMulti-page crawling with link following

CLI Usage

Extract Static Page

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

With CSS selector and browser impersonation:

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

Extract JS-Rendered Page

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

Extract Cloudflare-Protected Page

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

POST Request

bash
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

python
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)

python
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

python
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

python
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):

python
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

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

Disable Resources for Speed

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

python
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

python
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:

python
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

python
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

python
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

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

Find Methods

python
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.):

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

Navigation

python
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:

python
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:

python
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

python
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+

Frequently asked questions

What does the Scrapling AI skill do?

Web scraping with Scrapling - HTTP fetching, stealth browser automation, Cloudflare bypass, and spider crawling via CLI and Python.

Why use Scrapling on TypingMind?

Because you install it once and use it with any model. Scrapling is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Scrapling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Tommy-yw/RunbookHermes/tree/main/optional-skills/research/scrapling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Scrapling?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Scrapling?

As many as you like. As long as a model supports skills, you can use Scrapling with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Scrapling AI skill free?

Yes. It is published on GitHub by Tommy-yw under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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