Node Parser Code for Web Scraping
Web scraping is a powerful method of capturing and using valuable data for business, research, or other purposes. If done well, it can help you have more data intelligence about critical details to help you make better decisions.
One popular way of doing this is with Node.js, which is why you need to learn a bit about a Node parser, including what it is and how it works. We’ve provided lots of web scraping tutorials, but let’s break down one of the fundamental components of the process.
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The term “Node parser” refers to a tool or library used in Node.js to process data. Node.js is an open-source JavaScript runtime environment that executes JavaScript code without the need for a separate web browser. Because of its asynchronous nature and rich ecosystem, Node.js is a valuable platform for building efficient scraping solutions. It will enable you to effectively and efficiently extract and analyze data from the website.
Nodejs-HTML-parser: The Details to Get Started
You will need to have some fundamental experience with Node parser code to use this guide. If you have not done so yet, we recommend reading “The Ultimate Guide to Node.js Web Scraping for Enterprise.”
What you will find is that JavaScript is very different than any other dynamic language. Its model is vastly different because it is event-based, which makes it more efficient for some projects. However, to use JavaScript to the fullest level, you need to use a server like Node.js to guide you.
What makes it so different is that it does not deal with PHP, .NET, or Java. With it, you can execute language on the server side without a web browser, but it maintains a lightweight tool that is ideal for just about anyone to use. It is also beneficial for data-intensive applications, including real-time data extraction or streaming.
Keep in mind that Node.js is not a framework itself, but rather a method for reducing the complexity of building code. Also notable, it is built on the Chrome V8 JavaScript engine. This will take the code you create and turn it into a readable form. There are over 350,000 packages within the Node package manager that can help you build applications and strategies for your project. With all that said, why are we creating a Node parser solution?
It is an excellent tool for processing and interpreting data in various formats. That includes HTML, JSON, and XML. It can also be used for custom file types, which allows you to better understand its functionality, no matter what your objectives are. As a server-side JavaScript environment, it is essential to have an efficient parsing mechanism that will handle the incoming data and manipulate the content, like all parsers do. Your Node parser will also need to interact with external resources.
The Tools You Need for Node Parser Success
As a web scraping tutorial will tell you, the parser you use must be designed to provide specific features to deal with the type of data you have. Popular Node parsers include several libraries designed to parse and manipulate data based on the format it is in. In that frame, we will look at several of those Node parser options here so you can choose those most appropriate for your needs.
Cheerio: Perhaps one of the most important and powerful libraries to use to create a Node parser is Cheerio. Specifically, this library is ideal for parsing and manipulating HTML content. We talked a bit about this in our recent piece called “Cheerio Web Scraping: How This Node.js Parsing Tool Stacks Against Puppeteer.” It is a lightweight library that offers jQuery-like API to explore HTML and XML documents. IT is ideal for using Cheerio to parse HTML documents, select HTML elements, or extract data from those documents. It is an advanced web scraping API for this reason.
Here is an example snippet to give you an idea of Cheerio:
import * as Cheerio from 'cheerio';
const $ = cheerio.load('<h2 class="title">Hello world</h2>');
$('h2.title').text('Hello there!');
$('h2').addClass('welcome');
$.html();
//=> <html><head></head><body><h2 class="title welcome">Hello there!</h2></body></html>
JSON.parse(): Choosing the most appropriate library for JSON data often means using the JSON.parse() method. With JSON.parse(), you have the simplest of methods to parse JSON data, as it is a built-in method. It takes a JSON string as your input and will return it as a JavaScript object. Here is an example of what it may look like:
const jsonString = '{"name": "Joe", "age": 20}';
const jsonObject = JSON.parse(jsonString);
console.log(jsonObject.name);
console.log(jsonObject.age);
This would produce the output of
Joe
20
XML2js: When it comes to parsing XML, as noted previously, Cheerio can offer some help, but XML2js is the better option for XML for numerous reasons. It allows for the conversation of simple XML into JavaScript objects. It works the other way around as well. It offers powerful features and while that may mean it takes a bit longer to learn to use, it is certainly the better route to take when it comes to more precise outcomes.
Here is an example of what this may look like:
var parseString = require('xml2js').parseString;
var xml = "<root>Hello xml2js!</root>"
parseString(xml, function (err, result) {
console.dir(result);
});
The Steps to Setting Up a JavaScript Web Scraper in Node.js
When it comes to node-HTML-parser or any other Node parser format, you need to know a few specific steps to help you complete the project. Here is a simple way to build a JavaScript web scraper in Node.js that will automatically extract data from a website. Let’s focus on the Rayobyte homepage as our target. The goal is to process HTML elements from the page, retrieve that data, and then convert it into a useful format.
This process is a skeleton of what you can expect from a Node parser, meaning there is much more you can do with these tools.
Your first step is to set up a Node.js project or create a folder that will hold your Node.js web scraping project.
mkdir web-scraper-nodejs
This will create an empty web-scraper-nodejs directory. Next, move into the folder using:
cd web-scraper-nodejs
and then initiate your NPM project using:
npm init -y
You should see a package.json that looks like this:
{rn u0022nameu0022: u0022web-scraper-nodejsu0022,rn u0022versionu0022: u00221.0.0u0022,rn u0022descriptionu0022: u0022u0022,rn u0022mainu0022: u0022index.jsu0022,rn u0022scriptsu0022: {rn u0022testu0022: u0022echo "Error: no test specified" u0026u0026 exit 1u0022rn },rn u0022keywordsu0022: [],rn u0022authoru0022: u0022u0022,rn u0022licenseu0022: u0022ISCu0022rn}
The next line to add is the root folder that you want your project to go to and initialize it.
// index.js
console.log("Hello, World!")
Your file has the web scraping logic you need to use. You will then open the package.json file and use the following script within the scripts section:
"start": "node index.js"
So far, it’s pretty straightforward, right? Now, we want to run the command below in the terminal. This will ultimately launch the script:
npm run start
All of that should result in
Hello, World!
If you get to that point, your Node.js app will work properly.
For this next part of the project, we will use Cheerio and Axios, which will help provide the functionality for the next process component. However, you can use whatever web scraping libraries are appropriate for your project. If you are unsure which to use, take a peek at the details on the target website you plan to use. Go to that site, right-click on a blank section of the site, and then click “inspect.” This will open the DevTools window, where you can then take a look at the Fetch/XHR section. This is where you will find valuable information in the source code.
Our next step is to install Cheerio with Axios, which will reduce the load times and make the process less complex. If you don’t have these libraries on board, you’ll need to install both.
npm install cheerio axios
Add the following lines of code to index.js:
// index.js
const cheerio = require("cheerio")
const axios = require("axios")
Then, download the content from your target website. Alter this bit of code to choose the site that you want to target:
// downloading the target web page
// by performing an HTTP GET request in Axios
const axiosResponse = await axios.request({
method: "GET",
url: "https://rayobyte.com",
})
Axios will use the following user-agent setup:
axios <axios_version>
Set a valid user-agent header in Axios by adding the following attribute to the object passed to request ():
headers: {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36"
}
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Now, at this point, you should have the content you need and can inspect the HTML page. It looks pretty impressive, right?
When you analyze the HTML code on the selected node, you will see <a> HTML elements. This element will contain a <figure> HTML element that includes the image associated with the industry field and a <div> HTML element that contains the name of the industry field.
Cheerio will give you numerous ways to select HTML elements that you want from a page. To get started, first initialize Cheerio:
// parsing the HTML source of the target web page with Cheerio
const $ = cheerio.load(axiosResponse.data)
It will accept HTML in string form. You can select the HTML element with Cheerio by using its class. Do this with:
const htmlElement = $(“.elementClass”)
You can select HTML elements by passing to $ any valid CSS selector. This is the same as you would do with jQuery. You can use the concatenate selection logic along with the find () method. To do that, try this:
// retrieving the list of industry cards
const industryCards = $(".elementor-element-7a85e3a8").find(".e-container")
You can iterate on a list of nodes with Cheerio. To do that, use the each() method. Here is an example:
// iterating over the list of industry cards
$(".elementor-element-7a85e3a8")
.find(".e-container")
.each((index, element) => {
// scraping logic...
})
Now you need to scrape the target data for web scraping and then convert he extract date to JSON. Since JSON derives from JavaScript, it tends to be the ideal choice when you are returning data. This will make converting your JavaScript scraping data to JSON easier to navigate.
To do that, use the following code as an example:
// transforming the scraped data into a general object
const scrapedData = {
industries: industries,
marketLeader: marketLeaderReasons,
customerExperience: customerExperienceReasons,
}
// converting the scraped data object to JSON
const scrapedDataJSON = JSON.stringify(scrapedData)
At this point, you have connected to the site, and you can now scrape the data and convert it to JSON. Once you put all of this together and run your script, you gain the data you need. With Nodejs’ parse HTML and other strategies, you can build a strong parser for your project.
This is one example of how to build a node parser, and it really does not take a lot of code to make it happen (there are more challenging projects out there, of course!). What makes these tools so important is what they do for you. These parsers enable you to process structured data, automate tasks, including web scraping, and handle API responses efficiently.
With the help of Node parsers, you can then work to build your scalable and dynamic server-side application.
Let Rayobyte Help You
To get started with Rayobyte, you can check out our web scraping API. You can also use our proxy services to help you build a stronger parser without any damage to your privacy. Learn more about what your options are and get started with Rayobyte. Make sure you learn more about why proxies for web scraping are so important.
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