Apify SDK for Python

The official Python SDK for building Apify Actors.

apify is the official SDK for building Apify Actors in Python. It handles the Actor lifecycle, storage access, platform events, Apify Proxy, pay-per-event charging, and more.

If you only need to consume the Apify API from Python (running Actors, reading datasets, managing storages) rather than building Actors, use the Apify API client for Python instead. It comes bundled with this SDK.

Table of contents

• Installation
• Quick start
• What are Actors?
• Features
• What you can build
• Usage examples
• Documentation
• Related projects
• Support and community
• Contributing
• License

Installation

The Apify SDK for Python requires Python 3.11 or higher. It is published on PyPI as the apify package and can be installed with pip:

pip install apify

or with uv:

uv add apify

To use the Scrapy integration, install the scrapy extra:

pip install 'apify[scrapy]'

Quick start

An Actor is a Python program that runs inside the async with Actor: context. The context initializes the Actor when it starts and tears it down when it finishes. Here's a minimal Actor that reads its input and stores a result:

from apify import Actor


async def main() -> None:
    async with Actor:
        actor_input = await Actor.get_input()
        Actor.log.info('Actor input: %s', actor_input)
        await Actor.set_value('OUTPUT', 'Hello, world!')

The quickest way to scaffold a full Actor project, with the .actor configuration, input schema, and Dockerfile already in place, is the Apify CLI:

1. Install the CLI:

   npm install -g apify-cli
   

2. Create a new Actor from the Python "getting started" template:

   apify create my-actor --template python-start
   

3. Run it locally:

   cd my-actor
   apify run
   

To create, run, and deploy your first Actor step by step, see the Quick start guide.

What are Actors?

Actors are serverless programs that can do almost anything. From simple scripts and web scrapers to complex automation workflows, AI agents, or even always-on services that expose HTTP endpoints.

They can run either locally or on the Apify platform, where you can scale their execution, monitor runs, schedule tasks, integrate them with other services, or even publish and monetize them. If you're new to Apify, learn more about the platform in the Apify documentation.

For more context, read the Actor whitepaper.

Features

• Run the full Actor lifecycle inside async with Actor:, covering init, exit, failures, status messages, and reboots (Actor lifecycle).
• Read Actor input validated against your input schema with Actor.get_input() (Actor input).
• Read and write datasets, key-value stores, and request queues, locally or on the platform (Working with storages).
• React to platform events such as system info, migration, and abort (Actor events).
• Route requests through Apify Proxy with group selection, country targeting, and rotation (Proxy management).
• Start, call, abort, and metamorph other Actors and tasks, and attach webhooks to run events (Interacting with other Actors, Webhooks).
• Monetize your Actor with pay-per-event charging (Pay-per-event).
• Reach the full Apify API through a preconfigured ApifyClient (Accessing the Apify API).

What you can build

Almost any Python project can become an Actor, including projects for:

• Web scraping and crawling — The SDK is fully compatible with Crawlee, which makes Apify a natural place to deploy and scale your crawlers (see the Crawlee guide). It also works with other popular scraping libraries, such as Scrapy, Scrapling, or Crawl4AI.
• Browser automation — Drive a real browser with Playwright or Selenium, or with higher-level tools such as Browser Use.
• Web servers and APIs — Run a web server inside an Actor to serve HTTP requests, for example to expose your scraper as a live API.
• AI agents — Host agents built with your framework of choice (see the AI agents guide). Ready-made Actor templates cover LangGraph, CrewAI, PydanticAI, LlamaIndex, and Smolagents.
• MCP servers — Deploy a Python MCP server as an Actor and make its tools available to any MCP client (see the MCP servers guide). Ready-made Actor templates cover the MCP server and MCP proxy.

Whatever you build, the Apify SDK doesn't lock you into a particular framework. Bring the libraries you already use, and let Apify run your project in the cloud.

Usage examples

The examples below show two common setups, but the same async with Actor: pattern works with any stack. For more, see the guides.

HTTPX2 with BeautifulSoup

Scrape pages with HTTPX2 and BeautifulSoup, using the Actor's request queue to track URLs:

from bs4 import BeautifulSoup
from httpx2 import AsyncClient

from apify import Actor


async def main() -> None:
    async with Actor:
        actor_input = await Actor.get_input() or {}
        start_urls = actor_input.get('start_urls', [{'url': 'https://apify.com'}])

        # Enqueue the start URLs into the default request queue.
        request_queue = await Actor.open_request_queue()
        for start_url in start_urls:
            await request_queue.add_request(start_url['url'])

        # Process the queue until it's empty.
        while request := await request_queue.fetch_next_request():
            Actor.log.info(f'Scraping {request.url} ...')
            async with AsyncClient() as client:
                response = await client.get(request.url)
            soup = BeautifulSoup(response.content, 'html.parser')

            # Push the extracted data to the default dataset.
            await Actor.push_data(
                {
                    'url': request.url,
                    'title': soup.title.string if soup.title else None,
                }
            )

            # Mark the request as handled so it is not processed again.
            await request_queue.mark_request_as_handled(request)

Crawlee with Playwright

Scrape pages with Crawlee's PlaywrightCrawler, which handles queueing, concurrency, and the browser for you:

from crawlee.crawlers import PlaywrightCrawler, PlaywrightCrawlingContext

from apify import Actor


async def main() -> None:
    async with Actor:
        actor_input = await Actor.get_input() or {}
        start_urls = [url['url'] for url in actor_input.get('start_urls', [{'url': 'https://apify.com'}])]

        crawler = PlaywrightCrawler(max_requests_per_crawl=50, headless=True)

        @crawler.router.default_handler
        async def handler(context: PlaywrightCrawlingContext) -> None:
            Actor.log.info(f'Scraping {context.request.url} ...')
            await context.push_data(
                {
                    'url': context.request.url,
                    'title': await context.page.title(),
                }
            )
            # Follow links found on the page.
            await context.enqueue_links()

        await crawler.run(start_urls)

Documentation

The full SDK documentation lives at docs.apify.com/sdk/python. For the Apify platform itself, see the Apify documentation.

Related projects

• Apify API client for Python — talk to the Apify API directly from Python (bundled with this SDK).
• Crawlee for Python — web scraping and browser automation framework; fully compatible with this SDK.
• Apify SDK for JavaScript / TypeScript — the equivalent SDK for Node.js.
• Apify API client for JavaScript / TypeScript — the equivalent API client for Node.js.
• Crawlee for JavaScript / TypeScript — the original Node.js implementation of Crawlee.
• Apify CLI — command-line tool for creating, running, and deploying Actors locally and on the platform.

Support and community

• Discord — chat with the team and other users on the Apify Discord server.
• GitHub issues — report a bug or request a feature in the issue tracker.

Contributing

Bug reports, fixes, and improvements are welcome! See CONTRIBUTING.md for the development setup, coding standards, testing, and release process.

License

Released under the Apache License 2.0.