# 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](https://www.docker.com/products/docker-desktop))
- 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:
```powershell
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):

```env
# 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**
```powershell
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:
```json
{
  "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:
```powershell
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":
```powershell
# 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
```powershell
# Clean up Docker
docker system prune -a
```

## Image Upload

Once running, you can upload product images:

```bash
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:
```powershell
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):
```javascript
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! 🚀