wallace-apple-dictionary VS cheerio

Scraping the Academy Award winners listed on Wikipedia with cheerio and saving them to a CSV file.

To get the best data for RAG, we need to remove irrelevant content. When you’re working within one site, you can use tools like cheerio to parse the HTML yourself based on your knowledge of the site's structure. But if you're scraping pages across different layouts and designs, you need a good way to return just the relevant content and avoid the rest.

Another thing! Imagine a user adds such a helper in the comments section under a post and adds malicious content in the parameter. Be mindful of security. For example, if you render every HTML completely, you could be vulnerable to XSS attacks. It’s recommended to compile and render Handlebars.js in specific, closed areas. You can use the cheerio (https://cheerio.js.org/) library for parsing HTML and rendering Handlebars where necessary. Here’s an example of how you can secure yourself by modifying the previous rendering code:

Cheerio: For parsing HTML

Cheerio

I opted to use cheerio, a nifty HTML parsing library to clean-up the HTML before returning it from the function. Using cheerio I:

We're going to use cheerio to parse the content from websites ("web scraping").

Cheerio is your ticket to the world of server-side magic, allowing you to manipulate HTML and XML documents with jQuery-like syntax. It’s perfect for web scraping, data extraction, or just making sense of the mess that is web content. With Cheerio, you get to play around with the DOM, use CSS selectors, and basically do all the cool things you'd do in the browser, but server-side.

In this guide, we'll be extracting information from Amazon product pages using the power of TypeScript in combination with the Cheerio and Crawlee libraries. We'll explore how to retrieve and extract detailed product data such as titles, prices, image URLs, and more from Amazon's vast marketplace. We'll also discuss handling potential blocking issues that may arise during the scraping process.

Used libraries Axios - it is a promise HTTP clients to make requests to the specified URL. Cheerio- it is a library for parsing and manipulating HTML that is commonly used here for extracting data from downloaded HTML content. Apify SDK- it is for building Apify Actors, that is utilized for initializing actor environments, getting input data, and pushing extracted data to the dataset.