cheerio VS TypeScript

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.

Nice. I've used Cheerio for this in the past: https://github.com/cheeriojs/cheerio?tab=readme-ov-file#sele...

For this article, I will be using the TypeScript Starter template as shown in the screenshot above. This comes with Nodejs, Cheerio, Axios

> I'm not sure why Python web scraping is so popular compared to Node.js web scraping

Take this with a grain of salt, since I am fully cognizant that I'm the outlier in most of these conversations, but Scrapy is A++ the no-kidding best framework for this activity that has been created thus far. So, if there was scrapyjs maybe I'd look into it, but there's not (that I'm aware of) so here we are. This conversation often comes up in any such "well, I just use requests & ..." conversation and if one is happy with main.py and a bunch of requests invocations, I'm glad for you, but I don't want to try and cobble together all the side-band stuff that Scrapy and its ecosystem provide for me in a reusable and predictable way

Also, often those conversations conflate the server side language with the "scrape using headed browser" language which happens to be the same one. So, if one is using cheerio <https://github.com/cheeriojs/cheerio> then sure node can be a fine thing - if the blog post is all "fire up puppeteer, what can go wrong?!" then there is the road to ruin of doing battle with all kinds of detection problems since it's kind of a browser but kind of not

I, under no circumstances, want the target site running their JS during my crawl runs. I fully accept responsibility for reproducing any XHR or auth or whatever to find the 3 URLs that I care about, without downloading every thumbnail and marketing JS and beacon and and and. I'm also cognizant that my traffic will thus stand out since it uniquely does not make the beacon and marketing calls, but my experience has been that I get the ban hammer less often with my target fetches than trying to pretend to be a browser with a human on the keyboard/mouse but is not

Web scraping is a powerful technique used to extract data from websites. In this tutorial, we'll explore how to perform web scraping using Node.js, Axios for making HTTP requests,Cheerio for parsing HTML content and also json2csv for converting json data to csv. We'll scrape product data from a sample website, "https://scrapeme.live/shop/".

Web scraping, while immensely useful, often requires developers to navigate a sea of tools and libraries, each with its own quirks and intricacies. Whether it's JSDOM, Cheerio, Playwright, or even just plain old vanilla JS in the DevTools console, moving between these platforms can be a challenge.

While looking for a way to implement capo.js in BigQuery to understand how pages in HTTP Archive are ordered, I came across the Cheerio library, which is a jQuery-like interface over an HTML parser.

Cheerio is a JavaScript tool for parsing HTML and XML in Node.js. It provides APIs for traversing and manipulating the DOM of a webpage.

Regular expressions are part of the language, so it's not so unreasonable that TypeScript should parse them and take their semantics into account. Indeed, TypeScript 5.5 will include [new support for syntax checking of regular expressions](https://github.com/microsoft/TypeScript/pull/55600), and presumably they'll eventually be able to solve the problem the GP highlighted on top of those foundations.

Dedicated syntax for creating unique subsets of a type that denote a particular refinement is a longstanding ask[2] - and very useful, we've experimented with implementations.[3]

I don't think it has any relation to runtime type checking at all. It's refinement types, [4] or newtypes[5] depending on the details and how you shape it.

[1] https://github.com/microsoft/TypeScript/blob/main/src/compil...

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Learning Curve and Developer Tooling sCrypt is an embedded Domain Specific Language (eDSL) based on TypeScript. It is strictly a subset of TypeScript, so all sCrypt code is valid TypeScript. TypeScript is chosen as the host language because it provides an easy, familiar language (JavaScript), but with type safety. There’s an abundance of learning materials available for TypeScript and thus sCrypt, including online tutorials, courses, documentation, and community support. This makes it relatively easy for beginners to start learning. It also has a vast ecosystem with numerous libraries and frameworks (e.g., React, Angular, Vue) that can simplify development and integration with Web2 applications.

As a JavaScript or TypeScript developer, you might have come across the terms type and interface when working with complex data structures or defining custom types. While both serve similar purposes, they have distinct characteristics that influence when to use them. In this blog post, we'll delve into the differences between types and interfaces in TypeScript, providing examples to aid your understanding.

TypeScript helps you in many ways in the context of a JavaScript app. It makes it easier to consume interfaces of any type.

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.

TypeScript

Familiarity with TypeScript, React and Next.js