GKNB_MSTM071/Frontend/1 het/backend/STUDENT_SETUP.md

Student Production Setup Guide

This guide explains how to set up and run the webstore backend in production mode.

What You'll Receive

Your instructor will provide you with:

1. webstore-production-images.tar - Docker images archive (API + database)
2. production.compose.yml - Docker Compose configuration
3. .production.env - Environment variables template
4. run-student-production.bat - Easy start script
5. Product images - 17 placeholder product images

Prerequisites

• Docker Desktop installed (Download here)
• Windows 10 or later (for Docker)
• Minimum 2GB free disk space
• ~5 minutes for initial setup

Step-by-Step Setup

Step 1: Extract Docker Images

Right-click on webstore-production-images.tar
→ Select "Extract All"
→ Choose destination folder

Or use PowerShell/terminal:

docker load -i webstore-production-images.tar

Step 2: Configure Environment Variables

1. Open .production.env in a text editor
2. Update these values (if different from defaults):

# Database Configuration
POSTGRES_DB=webstore_db
POSTGRES_USER=webstore_user
POSTGRES_PASSWORD=webstore_password
DB_PORT=5432

# API Configuration
PORT=3000
API_PORT=3000

# JWT Configuration
JWT_SECRET=your-secret-key-change-for-production
JWT_EXPIRES_IN=7d

# Security
COOKIE_NAME=webstore_token
COOKIE_SECURE=false  # Set to true if using HTTPS

# Database URL (usually don't change this)
DATABASE_URL=postgresql://webstore_user:webstore_password@db:5432/webstore_db?schema=public

Step 3: Start the Application

Option A: Using the provided script (recommended)

Double-click: run-student-production.bat

Option B: Using Docker Compose directly

docker-compose -f production.compose.yml up

Step 4: Verify Setup

Wait for logs to show:

webstore_api_prod | npm notice
webstore_api_prod | > webstore-backend@1.0.0 start
webstore_api_prod | > node src/Api/server.js
webstore_api_prod | Server running on port 3000

Step 5: Test the API

Open in your browser:

http://localhost:3000/api/health

Expected response:

{
  "status": "ok",
  "message": "CQRS backend running"
}

Accessing the API

The API is available at: http://localhost:3000

Key Endpoints

• GET /api/health - Health check
• GET /api/shop/categories - List all product categories
• GET /api/shop/products - List all products
• GET /api/shop/products/:id - Get product by ID
• POST /api/shop/products - Create product (with image upload)
• POST /api/shop/products/:id/image - Update product image

Built-in Data

The database automatically seeds with:

Test Users:

Email: admin@test.com
Password: admin123

Email: john@test.com
Password: password123

Email: jane@test.com
Password: password123

Products:

• 16 sample products across 5 categories
• Each product has a placeholder image
• Sample prices range from 4,990 to 29,990 HUF

Categories:

• Shoes (4 products)
• Bags (4 products)
• Accessories (4 products)
• Clothing (3 products)
• Electronics (2 products)

Stopping the Application

Using Docker Compose:

docker-compose -f production.compose.yml down

Or simply close the terminal window

Troubleshooting

Port Already in Use

If you get "port 3000 already in use":

# Change port in .production.env
API_PORT=3001

Database Connection Failed

• Verify database container is running: docker ps
• Check DATABASE_URL in .production.env
• Ensure PostgreSQL image is loaded: docker images | grep postgres

Docker Not Running

• Start Docker Desktop application
• Wait for Docker daemon to be ready (check system tray)

Out of Disk Space

# Clean up Docker
docker system prune -a

Image Upload

Once running, you can upload product images:

curl -X POST http://localhost:3000/api/shop/products/1/image \
  -F "image=@path/to/image.jpg"

Images are stored in the images/uploads/ directory and served automatically.

Database Persistence

Product data is stored in PostgreSQL. Data persists between application restarts unless you:

docker-compose -f production.compose.yml down -v

The -v flag removes data volumes (use carefully!).

Connecting Frontend

Configure your frontend to use:

API Base URL: http://localhost:3000/api

Example (fetch):

const response = await fetch('http://localhost:3000/api/shop/products');
const data = await response.json();
console.log(data);

Questions or Issues?

Consult your instructor or check the main README.md for more information about the backend architecture and CQRS pattern.

Happy coding! 🚀