diff --git a/docs/01_introduction/quick-start.mdx b/docs/01_introduction/quick-start.mdx
index da166da9..c0f8bec3 100644
--- a/docs/01_introduction/quick-start.mdx
+++ b/docs/01_introduction/quick-start.mdx
@@ -105,4 +105,5 @@ To see how you can integrate the Apify SDK with popular web scraping libraries,
 - [Selenium](../guides/selenium)
 - [Crawlee](../guides/crawlee)
 - [Scrapy](../guides/scrapy)
+- [Scrapling](../guides/scrapling)
 - [Running webserver](../guides/running-webserver)
diff --git a/docs/03_guides/07_scrapling.mdx b/docs/03_guides/07_scrapling.mdx
new file mode 100644
index 00000000..63e948e5
--- /dev/null
+++ b/docs/03_guides/07_scrapling.mdx
@@ -0,0 +1,96 @@
+---
+id: scrapling
+title: Adaptive scraping with Scrapling
+description: Build an Apify Actor that scrapes web pages using the Scrapling adaptive web scraping library.
+---
+
+import CodeBlock from '@theme/CodeBlock';
+import RunnableCodeBlock from '@site/src/components/RunnableCodeBlock';
+
+import ScraplingExample from '!!raw-loader!roa-loader!./code/07_scrapling.py';
+import ScraplingBrowserScraper from '!!raw-loader!./code/07_scrapling_browser.py';
+
+In this guide, you'll learn how to use the [Scrapling](https://scrapling.readthedocs.io/) library for adaptive web scraping in your Apify Actors.
+
+## Introduction
+
+[Scrapling](https://scrapling.readthedocs.io/) is an adaptive web scraping library for Python that combines fetching and parsing behind a single, high-level API. It can fetch a page with fast HTTP requests or with a real browser, parse the result with familiar CSS selectors and XPath, and even relocate your selectors automatically when a website's structure changes.
+
+Some of the features that make Scrapling a good fit for Apify Actors:
+
+- **Multiple fetchers** - A single API exposes a fast HTTP client with browser TLS-fingerprint impersonation, as well as full browser automation for JavaScript-heavy or protected pages.
+- **Adaptive selectors** - Scrapling can remember the elements you scraped and find them again after a website redesign, so your scrapers keep working with fewer manual fixes.
+- **Anti-bot evasion** - Built-in stealth features (browser impersonation, realistic headers, and automatic Cloudflare Turnstile solving with the browser fetchers) help you avoid being blocked.
+- **Familiar parsing API** - Elements are selected with CSS selectors (including the `::text` and `::attr()` pseudo-elements) or XPath, with a Scrapy/Parsel-like `.get()` and `.getall()` interface.
+- **First-class async support** - Every fetcher has an asynchronous variant, which integrates naturally with the asyncio-based Apify SDK.
+
+Scrapling's parser works on its own, while the fetchers are an optional extra. Install Scrapling with the `fetchers` extra to get the HTTP and browser fetchers:
+
+```bash
+pip install "scrapling[fetchers]"
+```
+
+## Choosing a fetcher
+
+All of Scrapling's fetchers are importable from `scrapling.fetchers`. Pick the one that matches the website you're scraping:
+
+- **`Fetcher` / `AsyncFetcher`** - Plain HTTP requests via `.get()`, `.post()`, `.put()`, and `.delete()`. Fast and lightweight, with optional browser TLS-fingerprint impersonation (`impersonate`) and realistic headers (`stealthy_headers`). This is the best choice for static pages and APIs, and it needs no browser binaries.
+- **`DynamicFetcher` / `DynamicSession`** - Full browser automation based on [Playwright](https://playwright.dev/), for pages that require JavaScript rendering or interaction. Fetch a page with `.fetch()` or its async variant `.async_fetch()`.
+- **`StealthyFetcher` / `StealthySession`** - A stealth-hardened browser fetcher that can automatically solve Cloudflare Turnstile challenges (`solve_cloudflare=True`). Use it for the most heavily protected websites.
+
+The returned `Response` object is also a Scrapling selector, so you can call `.css()`, `.xpath()`, `.find_all()`, and the other parsing methods on it directly.
+
+The HTTP fetchers work with just the `scrapling[fetchers]` extra. The browser-based fetchers (`DynamicFetcher` and `StealthyFetcher`) additionally need browser binaries, which you download with the `scrapling install` command - see [Running browser-based fetchers](#running-browser-based-fetchers) below.
+
+The example Actor in this guide uses the HTTP `AsyncFetcher`, which is the simplest to deploy and pairs well with Apify Proxy.
+
+## Example Actor
+
+The following Actor recursively scrapes data from linked pages on the same site, up to a user-defined maximum depth, starting from the URLs in the Actor input. It uses Scrapling's `AsyncFetcher` to fetch each page through [Apify Proxy](https://docs.apify.com/platform/proxy), and CSS selectors to extract the title, headings, and links.
+
+The whole Actor fits in a single file. A `scrape_page` helper holds the Scrapling-specific fetching and parsing, while the `main` coroutine handles the [Actor](https://docs.apify.com/platform/actors) lifecycle, reads the input, sets up [Apify Proxy](https://docs.apify.com/platform/proxy) and the [request queue](https://docs.apify.com/platform/storage/request-queue), and drives the crawl:
+
+<RunnableCodeBlock className="language-python" language="python">
+    {ScraplingExample}
+</RunnableCodeBlock>
+
+A few things worth pointing out:
+
+- Keeping the fetching and parsing in `scrape_page` separates the Scrapling-specific code from the Actor's orchestration logic. The function returns the extracted data together with the discovered links, so `main` decides what to store and what to enqueue.
+- The response of `AsyncFetcher.get` is a Scrapling selector, so `response.css('title::text').get()` reads the page title and `response.css('a::attr(href)').getall()` returns every link's `href` in one call.
+- `response.urljoin(link_href)` resolves relative links against the page URL, so you can enqueue them directly.
+- The `impersonate='chrome'` and `stealthy_headers=True` options make the request look like it comes from a real Chrome browser, which - combined with Apify Proxy - reduces the chance of being blocked.
+
+## Using Apify Proxy
+
+Running on the Apify platform gives your scraper access to [Apify Proxy](https://docs.apify.com/platform/proxy), which rotates IP addresses to avoid rate limiting and blocking. In the example above, `main` creates a proxy configuration with `Actor.create_proxy_configuration` and passes a fresh proxy URL to `scrape_page` for every request, which forwards it to Scrapling's `proxy` argument.
+
+Scrapling accepts the proxy as a URL string (for example `http://user:pass@proxy.apify.com:8000`), which is exactly what `ProxyConfiguration.new_url` returns. To select specific proxy groups or a country, pass the relevant arguments to `Actor.create_proxy_configuration`. For more details, see the [Proxy management](../concepts/proxy-management) guide. The browser-based fetchers accept the same `proxy` argument.
+
+## Running browser-based fetchers
+
+`DynamicFetcher` and `StealthyFetcher` drive a real browser, so they need the browser binaries installed with the `scrapling install` command. Locally, run it once after installing the `scrapling[fetchers]` extra:
+
+```bash
+scrapling install
+```
+
+Switching the example Actor from HTTP to a real browser takes only one code change - swap the `AsyncFetcher.get` call in `scrape_page` for `DynamicFetcher.async_fetch`. The parsing API is identical, so the rest of the Actor stays exactly the same:
+
+<CodeBlock className="language-python">
+    {ScraplingBrowserScraper}
+</CodeBlock>
+
+To run this on the Apify platform, build on top of the [Apify Playwright base image](https://hub.docker.com/r/apify/actor-python-playwright), which already ships a browser together with all of its system-level dependencies, and run `scrapling install` during the Docker build to download the browser binaries that Scrapling expects.
+
+## Conclusion
+
+In this guide, you learned how to use Scrapling in your Apify Actors. You can now fetch pages with Scrapling's HTTP or browser-based fetchers, extract data with its CSS and XPath selectors, route requests through Apify Proxy, and run the whole thing on the Apify platform. See the [Actor templates](https://apify.com/templates/categories/python) to get started with your own scraping tasks. If you have questions or need assistance, feel free to reach out on our [GitHub](https://github.com/apify/apify-sdk-python) or join our [Discord community](https://discord.com/invite/jyEM2PRvMU). Happy scraping!
+
+## Additional resources
+
+- [Scrapling: Official documentation](https://scrapling.readthedocs.io/)
+- [Scrapling: Fetchers](https://scrapling.readthedocs.io/en/latest/fetching/choosing/)
+- [Scrapling: Parsing and selecting elements](https://scrapling.readthedocs.io/en/latest/parsing/selection/)
+- [Scrapling: GitHub repository](https://github.com/D4Vinci/Scrapling)
+- [Apify: Proxy management](https://docs.apify.com/platform/proxy)
diff --git a/docs/03_guides/code/07_scrapling.py b/docs/03_guides/code/07_scrapling.py
new file mode 100644
index 00000000..49aab31b
--- /dev/null
+++ b/docs/03_guides/code/07_scrapling.py
@@ -0,0 +1,122 @@
+import asyncio
+from typing import Any
+from urllib.parse import urlsplit
+
+from scrapling.fetchers import AsyncFetcher
+
+from apify import Actor, Request
+from apify.storages import RequestQueue
+
+
+async def scrape_page(
+    url: str,
+    *,
+    proxy_url: str | None = None,
+) -> tuple[dict[str, Any], list[str]]:
+    """Fetch a page with Scrapling's HTTP fetcher and return data and links."""
+    # `impersonate` and `stealthy_headers` make the request look like Chrome.
+    response = await AsyncFetcher.get(
+        url,
+        proxy=proxy_url,
+        impersonate='chrome',
+        stealthy_headers=True,
+        timeout=60,
+    )
+
+    data = {
+        'url': url,
+        'title': response.css('title::text').get(),
+        'h1s': response.css('h1::text').getall(),
+        'h2s': response.css('h2::text').getall(),
+        'h3s': response.css('h3::text').getall(),
+    }
+
+    # Keep only absolute links on the same host.
+    links: list[str] = []
+    host = urlsplit(url).netloc
+    for href in response.css('a::attr(href)').getall():
+        link_url = response.urljoin(href)
+        if not link_url.startswith(('http://', 'https://')):
+            continue
+        if urlsplit(link_url).netloc == host:
+            links.append(link_url)
+
+    return data, links
+
+
+async def enqueue_links(
+    request_queue: RequestQueue,
+    links: list[str],
+    *,
+    depth: int,
+    max_depth: int,
+) -> None:
+    """Enqueue the links one level deeper, unless max_depth was reached."""
+    if depth >= max_depth:
+        return
+
+    for link_url in links:
+        Actor.log.info(f'Enqueuing {link_url} ...')
+        request = Request.from_url(link_url)
+        request.crawl_depth = depth + 1
+        await request_queue.add_request(request)
+
+
+async def main() -> None:
+    async with Actor:
+        # Read the Actor input.
+        actor_input = await Actor.get_input() or {}
+        start_urls = actor_input.get('startUrls', [{'url': 'https://crawlee.dev'}])
+        max_depth = actor_input.get('maxDepth', 1)
+
+        if not start_urls:
+            Actor.log.info('No start URLs specified in Actor input, exiting...')
+            await Actor.exit()
+
+        # Set up Apify Proxy and the request queue.
+        proxy_configuration = await Actor.create_proxy_configuration()
+        request_queue = await Actor.open_request_queue()
+
+        # Enqueue the start URLs (crawl depth defaults to 0).
+        for start_url in start_urls:
+            url = start_url.get('url')
+            Actor.log.info(f'Enqueuing start URL: {url}')
+            await request_queue.add_request(Request.from_url(url))
+
+        # Cap the crawl; raise or remove to follow more pages.
+        max_requests = 50
+        handled_requests = 0
+
+        while handled_requests < max_requests and (
+            request := await request_queue.fetch_next_request()
+        ):
+            handled_requests += 1
+            url = request.url
+            depth = request.crawl_depth
+            Actor.log.info(f'Scraping {url} (depth={depth}) ...')
+
+            try:
+                # Fresh proxy URL per request (None if no proxy).
+                proxy_url = None
+                if proxy_configuration:
+                    proxy_url = await proxy_configuration.new_url()
+
+                data, links = await scrape_page(url, proxy_url=proxy_url)
+                await Actor.push_data(data)
+                Actor.log.info(
+                    f'Stored data from {url} '
+                    f'(title={data["title"]!r}, {len(links)} links found).'
+                )
+                await enqueue_links(
+                    request_queue, links, depth=depth, max_depth=max_depth
+                )
+
+            except Exception:
+                Actor.log.exception(f'Cannot extract data from {url}.')
+
+            finally:
+                await request_queue.mark_request_as_handled(request)
+
+
+if __name__ == '__main__':
+    asyncio.run(main())
diff --git a/docs/03_guides/code/07_scrapling_browser.py b/docs/03_guides/code/07_scrapling_browser.py
new file mode 100644
index 00000000..3eb50e24
--- /dev/null
+++ b/docs/03_guides/code/07_scrapling_browser.py
@@ -0,0 +1,35 @@
+from typing import Any
+
+from scrapling.fetchers import DynamicFetcher
+
+
+async def scrape_page(
+    url: str,
+    *,
+    proxy_url: str | None = None,
+) -> tuple[dict[str, Any], list[str]]:
+    """Fetch a page in a real browser with Scrapling and return data and links."""
+    # `network_idle` waits until the page stops making network requests.
+    response = await DynamicFetcher.async_fetch(
+        url,
+        proxy=proxy_url,
+        headless=True,
+        network_idle=True,
+    )
+
+    data = {
+        'url': url,
+        'title': response.css('title::text').get(),
+        'h1s': response.css('h1::text').getall(),
+        'h2s': response.css('h2::text').getall(),
+        'h3s': response.css('h3::text').getall(),
+    }
+
+    # Collect absolute links from the page.
+    links: list[str] = []
+    for href in response.css('a::attr(href)').getall():
+        link_url = response.urljoin(href)
+        if link_url.startswith(('http://', 'https://')):
+            links.append(link_url)
+
+    return data, links