Video Summary

Here's a summarized version of the article in 300 words:

To scrape dynamic web sites with Scraper API, you'll need to use JavaScript and send text-based responses. When you're dealing with web sites that use a lot of JavaScript, you'll often run into walls when trying to scrape them. One such example is a sports betting site, which requires a lot of dynamic information. This article will show you how to scrape such sites using Scraper API and the Scrapy framework.

The key is to render the JavaScript code and get the HTML response. Scraper API allows you to set additional parameters in your requests, such as rendering the JavaScript code. There's also a Python SDK available, which you can install using pip. Once you have the SDK, you can import the Scraper API client and use it to send requests.

The article then goes on to show how to use Scrapy to scrape a sports betting site. It demonstrates how to use the scrapy.Request object to send a request to the site, and then use the scrapy.get method to get the HTML response. The article also shows how to use the render parameter to render the JavaScript code and get the dynamic content.

The resulting HTML file can then be exported to a file, allowing you to view the content in a browser. The article concludes by stating that Scraper API makes it easy to scrape dynamic web sites, and that you can use it to extract the text and data you need.