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Snippets Application

This is a full stack web application I worked during Fall'23 semester as part of Advanced Web Programming course at CalState LA.

  • The app allows users to write code snippets that can be viewed and bookmarked by other users.
  • Login/Register functionality is implemented for users to access personalized dashboard and feed.
  • Users can select their topics (programming languages) for the personalized feed.
  • Based on the user roles, users can/cannot perform some actions.

Technologies & Frameworks Used

Backend: Node.js, Express.js, Mongoose, bcrypt

Frontend: Vue.js, axios, tailwindcss

Database: Mongo DB

Features

Building a Node.js RESTful Server Application

  • Implements a Express.js s
  • Building a Node.js Server Application.
  • Implement RESTful routes to manage resources.
  • Development of the backend logic for handling HTTP requests and responses.

Adding JWT to the Node.js Server Application and Connecting to MongoDB

  • Incorporate the MVC design pattern
  • Implement schemas and data models
  • Connect to MongoDB to store application data

Creating a Vue.js Frontend for the Node.js Server Application

  • Enhance Snippet Application by using JWTs for user management
  • Develop a dynamic and interactive user interface using Vue.js.
  • Establish communication between the Vue.js frontend and the Node.js backend

Installation

Clone the repository

Backend

Install the dependencies

cd snippet-server
npm install # Installs the backend dependencies

Running the application

To run the application mongo atlas account is required

Go to config.json in snippet-server to replace the values of username and password with your mongo atlas credentials.

npm run start # Nodemon Automatically restarts based on file changes

The application is served at http://localhost:8080

Frontend

Install the dependencies

cd snippet-client
npm install # Installs the frontend dependencies

Running the application

npm run dev

The frontend is served at http://localhost:5173

Improvements

  • UI is pretty basic at best and needs to be revamped.
  • An ML model/suggestion algorithm can be used to give more personalized feed.
  • The feed doesn't show the bookmarks of the current snippet.

Shout out to Cydney Auman for teaching this class.

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Full stack web application for Snippets

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