Tarpaulin API

Tarpaulin is a lightweight course management tool designed as an alternative to Canvas. This project involves developing a complete RESTful API for Tarpaulin, allowing users (instructors and students) to manage courses, assignments, and submissions.

Table of Contents

• Project Overview
• Features
• Technologies Used
• Getting Started
• Running the Application
• API Endpoints
• Deployment
• Testing
• Contributing
• License

Project Overview

The Tarpaulin API supports various operations for managing courses, assignments, and submissions. The API is designed to be modular and scalable, using modern development practices such as containerization and cloud deployment.

Features

• User authentication and authorization (Admin, Instructor, Student roles)
• CRUD operations for courses, assignments, and submissions
• File upload and download for assignment submissions
• Course roster download in CSV format
• Pagination for large datasets
• Rate limiting to prevent abuse
• Docker containerization for all services

Technologies Used

• Node.js: Server-side JavaScript runtime
• Express.js: Web framework for Node.js
• MySQL: Relational database management system
• Redis: In-memory data structure store for caching
• RabbitMQ: Message broker for asynchronous task handling
• AWS S3: Object storage service for file uploads
• JWT: JSON Web Tokens for authentication
• Docker: Containerization platform
• Google Cloud Platform: Cloud hosting and deployment

Getting Started

Prerequisites

• Node.js (>= 14.x)
• Docker
• AWS account for S3
• Google Cloud account

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/tarpaulin-api.git
   cd tarpaulin-api

2. Install dependencies:

   npm install

3. Set up environment variables: Create a .env file in the root directory with the following content:

   NODE_ENV=development
   DB_HOST=db
   DB_USER=root
   DB_PASSWORD=example
   DB_NAME=tarpaulin
   JWT_SECRET=your_jwt_secret
   AWS_ACCESS_KEY_ID=your_aws_access_key_id
   AWS_SECRET_ACCESS_KEY=your_aws_secret_access_key
   AWS_S3_BUCKET_NAME=your_s3_bucket_name

Running the Application

Using Docker

1. Start the services using Docker Compose:

   docker-compose up

2. The API should now be running at http://localhost:3000.

Without Docker

1. Start the MySQL and Redis servers locally.
2. Run the application:

   npm start

API Endpoints

The API endpoints are defined in the OpenAPI specification and can be viewed in the Swagger editor. Below are some key endpoints:

• User Authentication
  • POST /auth/register
  • POST /auth/login
• Courses
  • GET /courses
  • GET /courses/{id}
  • POST /courses
  • PUT /courses/{id}
  • DELETE /courses/{id}
  • GET /courses/{id}/roster
• Assignments
  • GET /assignments
  • GET /assignments/{id}
  • POST /assignments
  • PUT /assignments/{id}
  • DELETE /assignments/{id}
• Submissions
  • GET /submissions
  • GET /submissions/{id}
  • POST /assignments/{id}/submissions
  • PUT /submissions/{id}
  • DELETE /submissions/{id}

Deployment

Google Cloud Platform

1. Deploy using Google Cloud Run:

   • Build and push the Docker image to Google Container Registry:

     gcloud builds submit --tag gcr.io/your-project-id/tarpaulin-api

   • Deploy the image to Cloud Run:

     gcloud run deploy tarpaulin-api --image gcr.io/your-project-id/tarpaulin-api --platform managed --region us-central1

2. Deploy using Google Kubernetes Engine (GKE):

   • Create a cluster:

     gcloud container clusters create tarpaulin-cluster --num-nodes=3

   • Deploy the application:

     kubectl apply -f k8s-deployment.yaml