Skip to main content

Crawlee for Python

Project description

Crawlee
A web scraping and browser automation library

Crawlee covers your crawling and scraping end-to-end and helps you build reliable scrapers. Fast.

🚀 Crawlee for Python is open to early adopters!

Your crawlers will appear almost human-like and fly under the radar of modern bot protections even with the default configuration. Crawlee gives you the tools to crawl the web for links, scrape data and persistently store it in machine-readable formats, without having to worry about the technical details. And thanks to rich configuration options, you can tweak almost any aspect of Crawlee to suit your project's needs if the default settings don't cut it.

👉 View full documentation, guides and examples on the Crawlee project website 👈

We also have a TypeScript implementation of the Crawlee, which you can explore and utilize for your projects. Visit our GitHub repository for more information Crawlee for JS/TS on GitHub.

Installation

We recommend visiting the Introduction tutorial in Crawlee documentation for more information.

Crawlee is available as the crawlee PyPI package.

pip install crawlee

Additional, optional dependencies unlocking more features are shipped as package extras.

If you plan to parse HTML and use CSS selectors, install crawlee with beautifulsoup extra:

pip install 'crawlee[beautifulsoup]'

If you plan to use a (headless) browser, install crawlee with the playwright extra:

pip install 'crawlee[playwright]'

Then, install the Playwright dependencies:

playwright install

You can install multiple extras at once by using a comma as a separator:

pip install 'crawlee[beautifulsoup,playwright]'

Verify that Crawlee is successfully installed:

python -c 'import crawlee; print(crawlee.__version__)'

With Crawlee CLI

The quickest way to get started with Crawlee is by using the Crawlee CLI and selecting one of the prepared templates. First, ensure you have Pipx installed:

pipx --help

Then, run the CLI and choose from the available templates:

pipx run crawlee create my-crawler

If you already have crawlee installed, you can spin it up by running:

crawlee create my-crawler

Examples

Here are some practical examples to help you get started with different types of crawlers in Crawlee. Each example demonstrates how to set up and run a crawler for specific use cases, whether you need to handle simple HTML pages or interact with JavaScript-heavy sites. A crawler run will create a storage/ directory in your current working directory.

BeautifulSoupCrawler

The BeautifulSoupCrawler downloads web pages using an HTTP library and provides HTML-parsed content to the user. It uses HTTPX for HTTP communication and BeautifulSoup for parsing HTML. It is ideal for projects that require efficient extraction of data from HTML content. This crawler has very good performance since it does not use a browser. However, if you need to execute client-side JavaScript, to get your content, this is not going to be enough and you will need to use PlaywrightCrawler. Also if you want to use this crawler, make sure you install crawlee with beautifulsoup extra.

import asyncio

from crawlee.beautifulsoup_crawler import BeautifulSoupCrawler, BeautifulSoupCrawlingContext


async def main() -> None:
    crawler = BeautifulSoupCrawler(
        # Limit the crawl to max requests. Remove or increase it for crawling all links.
        max_requests_per_crawl=10,
    )

    # Define the default request handler, which will be called for every request.
    @crawler.router.default_handler
    async def request_handler(context: BeautifulSoupCrawlingContext) -> None:
        context.log.info(f'Processing {context.request.url} ...')

        # Extract data from the page.
        data = {
            'url': context.request.url,
            'title': context.soup.title.string if context.soup.title else None,
        }

        # Push the extracted data to the default dataset.
        await context.push_data(data)

        # Enqueue all links found on the page.
        await context.enqueue_links()

    # Run the crawler with the initial list of URLs.
    await crawler.run(['https://crawlee.dev'])

if __name__ == '__main__':
    asyncio.run(main())

PlaywrightCrawler

The PlaywrightCrawler uses a headless browser to download web pages and provides an API for data extraction. It is built on Playwright, an automation library designed for managing headless browsers. It excels at retrieving web pages that rely on client-side JavaScript for content generation, or tasks requiring interaction with JavaScript-driven content. For scenarios where JavaScript execution is unnecessary or higher performance is required, consider using the BeautifulSoupCrawler. Also if you want to use this crawler, make sure you install crawlee with playwright extra.

import asyncio

from crawlee.playwright_crawler import PlaywrightCrawler, PlaywrightCrawlingContext


async def main() -> None:
    crawler = PlaywrightCrawler(
        # Limit the crawl to max requests. Remove or increase it for crawling all links.
        max_requests_per_crawl=10,
    )

    # Define the default request handler, which will be called for every request.
    @crawler.router.default_handler
    async def request_handler(context: PlaywrightCrawlingContext) -> None:
        context.log.info(f'Processing {context.request.url} ...')

        # Extract data from the page.
        data = {
            'url': context.request.url,
            'title': await context.page.title(),
        }

        # Push the extracted data to the default dataset.
        await context.push_data(data)

        # Enqueue all links found on the page.
        await context.enqueue_links()

    # Run the crawler with the initial list of requests.
    await crawler.run(['https://crawlee.dev'])


if __name__ == '__main__':
    asyncio.run(main())

More examples

Explore our Examples page in the Crawlee documentation for a wide range of additional use cases and demonstrations.

Features

Why Crawlee is the preferred choice for web scraping and crawling?

Why use Crawlee instead of just a random HTTP library with an HTML parser?

  • Unified interface for HTTP & headless browser crawling.
  • Automatic parallel crawling based on available system resources.
  • Written in Python with type hints - enhances DX (IDE autocompletion) and reduces bugs (static type checking).
  • Automatic retries on errors or when you’re getting blocked.
  • Integrated proxy rotation and session management.
  • Configurable request routing - direct URLs to the appropriate handlers.
  • Persistent queue for URLs to crawl.
  • Pluggable storage of both tabular data and files.
  • Robust error handling.

Why to use Crawlee rather than Scrapy?

  • Crawlee has out-of-the-box support for headless browser crawling (Playwright).
  • Crawlee has a minimalistic & elegant interface - Set up your scraper with fewer than 10 lines of code.
  • Complete type hint coverage.
  • Based on standard Asyncio.

Running on the Apify platform

Crawlee is open-source and runs anywhere, but since it's developed by Apify, it's easy to set up on the Apify platform and run in the cloud. Visit the Apify SDK website to learn more about deploying Crawlee to the Apify platform.

Support

If you find any bug or issue with Crawlee, please submit an issue on GitHub. For questions, you can ask on Stack Overflow, in GitHub Discussions or you can join our Discord server.

Contributing

Your code contributions are welcome, and you'll be praised for eternity! If you have any ideas for improvements, either submit an issue or create a pull request. For contribution guidelines and the code of conduct, see CONTRIBUTING.md.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

crawlee-0.1.1.tar.gz (111.9 kB view hashes)

Uploaded Source

Built Distribution

crawlee-0.1.1-py3-none-any.whl (150.7 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page