Memora Backend

A robust Node.js backend API for the Memora flashcard application - a web-based memory training tool that helps users create, manage, and study flashcards.

🌐 Live at: memora.tiberiusgh.com

🚀 Features

• User Management: Firebase Authentication integration with MongoDB for persistent user profiles
• Flashcard Collections: Create, update, delete, and manage flashcard collections
• Individual Flashcards: Full CRUD operations for flashcards within collections
• Public Collections: Share collections publicly and browse community content
• Access Control: Role-based permissions for collections and flashcards
• Comprehensive Logging: Winston-based logging with multiple transports
• Request Tracking: UUID-based request tracking and HTTP context management
• Security: Helmet.js security headers, XSS protection, and input sanitization

Architecture

Core Components

• Express.js: Web framework
• MongoDB: Database with Mongoose ODM
• Firebase Admin SDK: Authentication and user management
• Winston: Structured logging
• Morgan: HTTP request logging

Installation

Prerequisites

• Node.js
• MongoDB
• Firebase project with Admin SDK credentials

Development Setup

1. Clone the repository

   git clone https://github.com/Memora-Tiberiusgh/backend
   cd backend

2. Install dependencies

   npm install

3. Environment Configuration

   Copy the provided example.env file to .env and configure with your values:

   cp example.env .env

   Then edit the .env file with your specific configuration values.

4. Start the development server

   npm run dev

Docker Development & Production

The application can be containerized for both development and production environments. The easiest way to run the complete Memora stack (backend, frontend, and database) is through the docker-compose file provided in the orchestrator repository:

Using Docker Compose (Recommended):

# Clone the orchestrator repository
git clone https://github.com/Memora-Tiberiusgh/orchestrator
cd orchestrator
# Follow the setup instructions in the orchestrator README
# This will start the entire Memora application stack

Manual Docker Build (if needed):

Development Environment:

docker build -f Dockerfile.dev -t memora-backend:dev .
docker run -p 8186:8186 memora-backend:dev

Production Environment:

docker build -f Dockerfile -t memora-backend:prod .
docker run -p 8186:8186 memora-backend:prod

API Documentation

Authentication

All protected routes require Firebase ID token in the Authorization header:

Authorization: Bearer <firebase-id-token>

User Endpoints

Method	Endpoint	Description	Auth Required
POST	/users	Create/retrieve user profile	No
PUT	/users/collections/:collectionId	Toggle collection in user library	Yes

Collection Endpoints

Method	Endpoint	Description	Auth Required
GET	/collections	Get user's collections	Yes
POST	/collections	Create new collection	Yes
GET	/collections/public	Get public collections	Yes
GET	/collections/:collectionId	Get specific collection	Yes
PATCH	/collections/:collectionId	Update collection	Yes
DELETE	/collections/:collectionId	Delete collection	Yes
POST	/collections/:collectionId/submit	Submit for public review	Yes

Flashcard Endpoints

Method	Endpoint	Description	Auth Required
POST	/flashcards	Create new flashcard	Yes
GET	/flashcards/:flashcardId	Get specific flashcard	Yes
PATCH	/flashcards/:flashcardId	Update flashcard	Yes
DELETE	/flashcards/:flashcardId	Delete flashcard	Yes
GET	/flashcards/collections/:collectionId	Get collection's flashcards	Yes

Request/Response Examples

Create Collection:

POST /collections
{
  "name": "Spanish Vocabulary",
  "description": "Basic Spanish words and phrases"
}

Create Flashcard:

POST /flashcards
{
  "question": "¿Cómo estás?",
  "answer": "How are you?",
  "collectionId": "64f7b1234567890abcdef123"
}

Security Features

• Input Sanitization: XSS protection using the xss library
• Authentication: Firebase ID token verification
• Authorization: Role-based access control for collections and flashcards
• Security Headers: Helmet.js for security headers
• Error Handling: Sanitized error responses in production
• Request Tracking: UUID-based request correlation

Logging

The application uses Winston for comprehensive logging with multiple transports:

• Console: Formated logs for development
• File Logging: Separate files for combined, error, and exception logs
• MongoDB: Optional database logging for warnings and errors
• Submission Tracking: Dedicated logging for collection submissions

Database Schema

User Model

{
  firebaseUid: String,      // Firebase UID (unique)
  displayName: String,      // User display name
  email: String,           // User email
  userAddedCollections: [ObjectId]  // References to added collections
}

Collection Model

{
  name: String,            // Collection name (1-50 characters)
  description: String,     // Optional description (max 500 characters)
  isPublic: Boolean,       // Public visibility flag
  creator: ObjectId,       // Reference to User
  submitted: Boolean       // Submission status for review
}

Flashcard Model

{
  question: String,        // Question text (1-500 characters)
  answer: String,         // Answer text (1-1000 characters)
  collectionId: ObjectId, // Reference to Collection
  creator: ObjectId       // Reference to User
}

Development

Code Style

This project uses ESLint with LNU configuration for consistent code formatting.

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/new-feature
3. Make your changes
4. Run tests and linting: npm run lint
5. Commit your changes: git commit -am 'Add new feature'
6. Push to the branch: git push origin feature/new-feature
7. Submit a pull request

License

This project is licensed under the MIT License.

Support

For issues and feature requests, please visit our GitHub Discussions or contribute to the project at GitHub organization.

Author

Tiberius Gherac - tiberius.gherac@gmail.com
First-year Web Development Student @ Linnaeus University
GitHub: @TiberiusGh

---