Parsel crawler

This example shows how to use ParselCrawler to crawl a website or a list of URLs. Each URL is loaded using a plain HTTP request and the response is parsed using Parsel library which supports CSS and XPath selectors for HTML responses and JMESPath for JSON responses. We can extract data from all kinds of complex HTML structures using XPath. In this example, we will use Parsel to crawl github.com and extract page title, URL and emails found in the webpage. The default handler will scrape data from the current webpage and enqueue all the links found in the webpage for continuous scraping.

import asyncio

from crawlee.parsel_crawler import ParselCrawler, ParselCrawlingContext

# Regex for identifying email addresses on a webpage.
EMAIL_REGEX = r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'


async def main() -> None:
    crawler = ParselCrawler(
        # 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: ParselCrawlingContext) -> None:
        context.log.info(f'Processing {context.request.url} ...')

        # Extract data from the page.
        data = {
            'url': context.request.url,
            'title': context.selector.xpath('//title/text()').get(),
            'email_address_list': context.selector.re(EMAIL_REGEX),
        }

        # 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://github.com'])

    # Export the entire dataset to a JSON file.
    await crawler.export_data('results.json')


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