The documentation in this repository describes the FullStack webscrapping platform for use in Machine learning.
We first break the architecture into four distictive components namely Front-End, API, Scrapers and Database. The user sends information from the front-end to the API, the fron-end connects the API through a form. Inputs like the youtube URL are sent through front-end. Later the scrapers through the API pulls the necessary data and is saved to the database. Afterwhich the data is served to the front-end.
The Tech Stack are as below
- Front-End - javascript
- API - express
- scraper - puppeteer
- db - mysql (typeorm)
Also we need nodejs, npm and mysql.
The Architecture consists of several components:
For the Front-end we will have a header, an input box and a button. Below which we will have render boxes which renders relevant info from json. This will send data to the API.
We will have to create a single route with two methods GET and POST. We use nodejs and simple backed framework express.
This function takes in URL and reaches out to YouTube, fetch the relevant data and then store it into the database.
We use mySQL here. Here we add id, name, avatar and channelURL
To run the program
First go into server
$ npm install init
Install all the necessary packages
$ npm install express
$ npm install body-parser
Run the index.js script
$ node index.js
Thanks to Aron from Uber