We check to make sure there are exactly 45 elements returned (the number of U.S. Let’s use Cheerio.js to parse the HTML we received earlier to return a list of links to the individual Wikipedia pages of U.S.
#Node.js webscraper code#
Parsing HTML with Cheerio.jsĪwesome, Chrome DevTools is now showing us the exact pattern we should be looking for in the code (a “big” tag with a hyperlink inside of it). Now, simply click inspect, and Chrome will bring up its DevTools pane, allowing you to easily inspect the page’s source HTML. Using Chrome DevTools is easy: simply open Google Chrome, and right click on the element you would like to scrape (in this case I am right clicking on George Washington, because we want to get links to all of the individual presidents’ Wikipedia pages): To do that, we’ll need to use Chrome DevTools to allow us to easily search through the HTML of a web page. Next, let’s open a new text file (name the file potusScraper.js), and write a quick function to get the HTML of the Wikipedia “List of Presidents” page.Ĭool, we got the raw HTML from the web page! But now we need to make sense of this giant blob of text.
#Node.js webscraper install#
presidents from Wikipedia and the titles of all the posts on the front page of Reddit.įirst things first: Let’s install the libraries we’ll be using in this guide (Puppeteer will take a while to install as it needs to download Chromium as well). We will be gathering a list of all the names and birthdays of U.S.
#Node.js webscraper pro#
Working through the examples in this guide, you will learn all the tips and tricks you need to become a pro at gathering any data you need with Node.js! This guide will walk you through the process with the popular Node.js request-promise module, CheerioJS, and Puppeteer. and parsing the data to get the exact information you want.acquiring the data using an HTML request library or a headless browser,.Getting started with web scraping is easy, and the process can be broken down into two main parts:
Or you could even be wanting to build a search engine like Google! Maybe you want to collect emails from various directories for sales leads, or use data from the internet to train machine learning/AI models. Or perhaps you need flight times and hotel/AirBNB listings for a travel site. There are a lot of use cases for web scraping: you might want to collect prices from various e-commerce sites for a price comparison site.
Retrieving the HTML is easy, but there are no browser APIs in NodeJS, so we need a tool like cheerio to process DOM elements and find the necessary metatags. The first strategy makes an HTTP request to a URL and expects an HTML document string as the response.
Npm run serve Strategy A - Basic HTTP Request
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