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Web scraping is rarely seen as an easy activity, so you might assume the same for node.js web scraping, yet that is not entirely true.
To provide evidence for such a claim, we’ve made a quick tutorial that essentially covers all the basics you would need to know for a successful node.js web scraping start. Our step-by-step guide takes you through the entire process, starting with the required software and which libraries should be downloaded.
Follow how packages like Cheerio provide additional benefits when used with Node.js. Learn how it converts the raw HTML captured by Axios into something that can be queried using a jQuery-like syntax. When one considers the popularity of jQuerry, quite a few developers are likely to feel familiar with some of the steps.
Examine the practical tutorial provided and learn without fear through the use of books-to-scrape, a website dedicated to testing out your scraping projects. The availability of a step-by-step tutorial gives you the unique opportunity to analyze each of the web scraping steps and see what might be the most relevant for you. Have you chosen a valid selector, or perhaps there were difficulties while scraping the genre. All is answered, and even if your scraping project was all smooth sailing, there are still valuable tips and package suggestions provided in the video, such as Axios, Cheerio, and Json2scv.
Watch these related videos:
Scraping tutorials with Python:
🎥 https://www.youtube.com/playlist?list=PL635Vr00fwj-1JL4GsY7ox5JRKRoaX4lg
Key information on web scraping:
🎥 https://www.youtube.com/playlist?list=PL635Vr00fwj_9W0e28fXXNuMkRmO8JnLq
Scraping tips and tricks:
🎥 https://www.youtube.com/playlist?list=PL635Vr00fwj_J5rR-CyLbQQl78VOiT-Rk
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The following parts are examined:
0:00 Introduction
0:20 What is Node.js?
1:27 Required software
1:58 Setting up Node.js
2:53 Basic steps of web scraping with JavaScript
3:58 Parsing the response
4:20 Web scraping, a practical example
5:57 Scraping the genre
7:56 Scraping book listings
9:24 Pagination
10:24 Saving scraped data to CSV
12:00 Summary
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