https://github.com/manangandhi1810/online-ide

Leetcode like platform to practice coding
https://github.com/manangandhi1810/online-ide

docker express leetcode postgresql prisma react redis shadcn-ui

Last synced: 1 day ago
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Leetcode like platform to practice coding

• Host: GitHub
• URL: https://github.com/manangandhi1810/online-ide
• Owner: MananGandhi1810
• License: mit
• Created: 2024-09-18T03:21:24.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-12T10:23:07.000Z (6 days ago)
• Last Synced: 2024-11-12T11:22:45.099Z (6 days ago)
• Topics: docker, express, leetcode, postgresql, prisma, react, redis, shadcn-ui
• Language: JavaScript
• Homepage: https://code.manangandhi.tech
• Size: 990 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Online IDE

Leetcode like platform to practice logic based coding problems. Built using Express.js, React.js, Postgres, and Docker

## Table of Contents

-   [Features](#features)

-   [Tech Stack](#tech-stack)

-   [How It Works](#how-it-works)

-   [Setup](#setup)

    -   [Using Docker Compose](#using-docker-compose)

    -   [Running Backend and Frontend Separately](#running-backend-and-frontend-separately)

-   [Contributing](#contributing)

## Features

-   JWT Based User Authentication

    -   Register

    -   Login

    -   Email token verification

    -   Forgot password with OTP

-   Code Editor

    -   Syntax Highlighting (with Shiki.js)

    -   4 Languages Supported (Python, C, C++, Java)

    -   Problem Statements rendered as Markdown, with support for code blocks

    -   Sample Test Cases for each problem with expected output

    -   Custom testcases can be set by the user

-   Sandboxed Code Execution

    -   Docker container for each code execution

    -   Limit time used by code

-   Test code against sample test cases before submission

-   Verify output against hidden test cases

-   Persist code to local storage

-   AI Assistant

    -   LLaMA will provide hints for the problem statement, with access to the code written by the user as context

    -   Streaming response from the AI Assistant, for a more interactive experience

-   Points

    -   +10 if the user solves a problem statement in the first submission

    -   +5 if the user solves a problem statement in more than one submission

    -   no points awarded if user solves a problem statement correctly more than once

-   Leaderboard ranking based on points

-   User Profile

    -   GitHub-like submission graph

    -   Total submissions

    -   Points earned

    -   Problems solved

-   Editorials for each problem statement

    -   Markdown rendered editorials

    -   Code blocks in editorials

    -   User can submit editorials after solving the problem statement

-   Critical endpoints are rate limited to prevent abuse

## Tech Stack

-   Express.js (Backend + Execution Worker)

-   Python (for code execution on the container)

-   React.js (Frontend)

-   Redis (for internal messaging, storing OTPs, saving code execution results)

-   PostgreSQL (with Prisma ORM)

-   Docker (with docker-compose)

-   Dockerode (for managing docker containers)

-   Resend (for sending emails)

-   Shadcn/UI (for frontend components)

-   Shiki.js with Monaco Editor (for code editing with syntax highlighting)

-   Meta LLaMA 3.1 8B (CloudFlare Workers AI)

## How it works

![Diagram](assets/flow-diagram.png)

## Setup

You can either use the docker-compose file to run the project or run the backend and frontend separately.

### Using Docker Compose

-   Clone the repository

-   Copy the `.env.example` file to `.env` and fill in the required values in both `frontend` and `backend` directories.

-   Run `docker compose up` in the root directory

-   The project will be running on `localhost:8000`

### Running Backend and Frontend Separately

> [!NOTE]

> You will still need to have Docker installed on your system.

-   Clone the repository

-   Copy the `.env.example` file to `.env` and fill in the required values in both `frontend` and `backend` directories.

-   Run the backend server

    -   Navigate to the `backend` directory

    -   Run `npm install`

    -   Run `npm run dev`

-   The backend server will be running on `localhost:3000`

-   Run the frontend server

    -   Navigate to the `frontend` directory

    -   Run `npm install`

    -   Run `npm start`

-   The project will be running on `localhost:5173`

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.