Web scraping refers to the process of gather information from a website through automated scripts. With web scraping, one can gather large amounts of data from websites where no official API exists.
Web scraping can be broken down into two simple steps:
- Fetching the HTML source code of a website via an HTTP request or a headless browser
- Parsing the raw HMTL data to get the information that matters
We'll look at both of these steps during this tutorial and writing our web scraper in TypeScript.
Why Typescript?
We'll be writing this in Typescript because the typed nature of TypeScript makes it easier to catch bugs and write cleaner code.
Prerequisites
To complete this tutorial, you need to have Node.js (version 8.x or later) and npm installed on your computer.
Getting Started
Let's create a new scraper directory for this project and initialize it as an NPM package by running npm init -y in the project root.
Setting up TypeScript
Lets setup TypeScript:
npm i -D typescript # Typescript compiles to plain JS
npm i -D ts-node # ts-node to run typescript code without compiling to JS
npm i -D nodemon # Automatically restarts the application whenever file changes are detected
Setting up TSConfig
Now lets setup the Typescript config file. Create a new file tsconfig.json and add the following code:
{
"compilerOptions": {
"target": "es6",
"module": "commonjs",
"rootDir": "src",
"outDir": "dist",
"sourceMap": true,
"resolveJsonModule": true,
"lib": ["es6", "dom"],
"esModuleInterop": true
},
"include": [
"src/**/*.ts"
],
"exclude": [
"node_modules"
]
}
We won't go into depth about what all these options do, but you can read the typescript documentation to learn more.
Adding a Start Script
Now, lets add some scripts to make it easier to run our code. Add the following to the package.json file.
{
...
"scripts": {
"start": "tsc && node dist/index.js",
"dev": "nodemon --watch 'src/**/*.ts' --exec 'ts-node' src/index.ts"
},
...
}
The start script compiles and runs our code, while the dev script will run the code and then rerun it every time you change it.
Installing other dependencies
Let's install the dependencies we'll be using to build the web scraper:
npm i -s axio cheerio
npm i -D @types/axios @types/cheerio
Setup the folder structure
Create a new folder src in your root directory, and a file called index.ts in the src folder. Your folder structure should now look like this:
scraper
│ package.json
│ tsconfig.json
└───src
│ │ index.ts
└───node_modules
Test Everything
Lets make sure everything was setup properly.
Open index.ts and add the following.
// index.ts
console.log('Project setup correctly!')
Then run npm run dev, and you should see Project setup correctly! appear in the console!
Scrape a website with Axios and Cheerio
we're going to set up a script to scrape the Premier League website for some player stats.
Specifically, we'll scrape the website for the top 20 goalscorers in Premier League history and organize the data as JSON.
Open up index.ts again and add the following code:
// index.ts
import axios from 'axios';
const url = 'https://www.premierleague.com/stats/top/players/goals?se=-1&cl=-1&iso=-1&po=-1?se=-1'; // URL we're scraping
const AxiosInstance = axios.create(); // Create a new Axios Instance
// Send an async HTTP Get request to the url
AxiosInstance.get(url)
.then( // Once we have data returned ...
response => {
const html = response.data; // Get the HTML from the HTTP request
console.log(html);
}
)
.catch(console.error); // Error handling
If you don't have the npm run dev command running already, make sure it's running, and you should see a bunch of HTML output.
You'll see this HTML contains a lot of stuff we don't need, like scripts and links to CSS, so how do we parse the HTML to get information we need?
This is where cheerio comes in. Cheerio allows us to use jQuery methods to parse an HTML string to extract information.
Open this link in your browser, and open the dev tools on that page. Use the inspector tool to highlight the body of the table listing the top goalscorers in Premier League history.
As you an see, the table body that holds the players has a class of .statsTableContainer. We can select all the rows using cheerio like this: $('.statsTableContainer > tr'). Go ahead and update the index.ts file to look like this:
import axios from 'axios';
import cheerio from 'cheerio';
const url = 'https://www.premierleague.com/stats/top/players/goals?se=-1&cl=-1&iso=-1&po=-1?se=-1'; // URL we're scraping
const AxiosInstance = axios.create(); // Create a new Axios Instance
// Send an async HTTP Get request to the url
AxiosInstance.get(url)
.then( // Once we have data returned ...
response => {
const html = response.data; // Get the HTML from the HTTP request
const $ = cheerio.load(html); // Load the HTML string into cheerio
const statsTable: Cheerio = $('.statsTableContainer > tr'); // Parse the HTML and extract just whatever code contains .statsTableContainer and has tr inside
console.log(statsTable); // Log the number of captured elements
}
)
.catch(console.error); // Error handling
You should see the number of players, 20, logged in your console.
The next step is to extract the rank, player name, nationality, and number of goals from each row. We can do that with the following script:
import axios from 'axios';
import cheerio from 'cheerio';
const url = 'https://www.premierleague.com/stats/top/players/goals?se=-1&cl=-1&iso=-1&po=-1?se=-1'; // URL we're scraping
const AxiosInstance = axios.create(); // Create a new Axios Instance
// This is the structure of the player data we recieve
interface PlayerData {
rank: number; // 1 - 20 rank
name: string;
nationality: string;
goals: number;
}
// Send an async HTTP Get request to the url
AxiosInstance.get(url)
.then( // Once we have data returned ...
response => {
const html = response.data; // Get the HTML from the HTTP request
const $ = cheerio.load(html); // Load the HTML string into cheerio
const statsTable: Cheerio = $('.statsTableContainer > tr'); // Parse the HTML and extract just whatever code contains .statsTableContainer and has tr inside
const topScorers: PlayerData[] = [];
statsTable.each((i, elem) => {
const rank: number = parseInt($(elem).find('.rank > strong').text()); // Parse the rank
const name: string = $(elem).find('.playerName > strong').text(); // Parse the name
const nationality: string = $(elem).find('.playerCountry').text(); // Parse the country
const goals: number = parseInt($(elem).find('.mainStat').text()); // Parse the number of goals
topScorers.push({
rank,
name,
nationality,
goals
})
})
console.log(topScorers);
}
)
.catch(console.error); // Error handling
We created an interface, PlayerData that represents the structure of the data we're parsing. We then parse this information from the HTML we recieve from the webpage, and create an array of objects with that data.
After saving your code, you should see an array being printed in your console with the information on each player. Pretty awesome, right! Plus, all the code is typesafe!
You can find the source code for this tutorial here.
Top comments (3)
Hi, there is an error with Cherio - (... const statsTable: Cheerio ...),
[Cannot find name 'Cheerio'.ts(2304)], do you know if something was changed?
If it is still needed, replace:
const statsTable: Cheerio = $('.statsTableContainer > tr');with
const statsTable: cheerio.Cheerio = $('.statsTableContainer > tr');Hi there I am a beginner and i am interested in scraping and making API, so the way you described above I want to know how can I store the scraped json in mongodb to create an api