Product Management System

This is a backend application for a Product Management System with asynchronous image processing. The application is built using Go and features RabbitMQ for message queuing, PostgreSQL for data storage, and local storage for compressed images.

Features

Product Management API:

• Add, retrieve, and filter products.
• Supports price range and product name filtering.

Asynchronous Image Processing:

• Upload product images and process them asynchronously.
• Compress and store images locally.
• Update the database with paths to compressed images.

Scalable Architecture:

• Uses RabbitMQ for message queuing.
• Modular design with separate packages for database and queue handling.

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Project Structure

product-management/
├── cmd/
│   └── main.go            # Entry point for the application
├── pkg/
│   ├── api/
│   │   ├── handlers.go    # HTTP API handlers
│   ├── database/
│   │   ├── db.go          # PostgreSQL connection setup
│   ├── queue/
│       ├── queue.go       # RabbitMQ connection and publishing logic
├── README.md              # Project documentation
├── go.mod                 # Go module dependencies
└── go.sum                 # Checksums for module dependencies

Installation

Prerequisites

• Go 1.18 or later
• PostgreSQL installed and running
• RabbitMQ installed and running (or use Docker)
• curl or Postman for API testing

Setup Instructions

1. Clone the Repository

git clone https://github.com/your-repo/product-management.git
cd product-management

2. Install Dependencies

go mod tidy

3. Set Up PostgreSQL

Create a new database:
postgres

CREATE DATABASE productdb;
Create tables:
sql
Copy code
CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    email VARCHAR(255) UNIQUE NOT NULL
);

CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    user_id INT REFERENCES users(id),
    product_name VARCHAR(255) NOT NULL,
    product_description TEXT,
    product_images TEXT[], -- Array of image URLs
    compressed_product_images TEXT[], -- Array of compressed URLs
    product_price DECIMAL(10, 2)
);

4. Start RabbitMQ

Start RabbitMQ using Docker or your local installation:

docker run -d --name rabbitmq -p 5672:5672 rabbitmq:management

Running the Application

Start the Application

go run cmd/main.go

API Endpoints

| Method | Endpoint         | Description                                |
|--------|------------------|--------------------------------------------|
| POST   | `/products`      | Create a new product                       |
| GET    | `/products`      | Retrieve all products with optional filters|
| GET    | `/products/{id}` | Retrieve a product by ID                   |
| POST   | `/process-images`| Process images asynchronously              |

Testing the Endpoints

1. Create a Product

curl -X POST http://localhost:8080/products \
-H "Content-Type: application/json" \
-d '{
    "user_id": 1,
    "product_name": "Test Product",
    "product_description": "A sample product.",
    "product_images": ["http://example.com/image1.jpg", "http://example.com/image2.jpg"],
    "product_price": 49.99
}'

2. Retrieve All Products

curl "http://localhost:8080/products?user_id=1&min_price=10&max_price=50&product_name=Sample"

3. Retrieve a Product by ID

curl "http://localhost:8080/products/1"

Asynchronous Image Processing

How It Works:

• Images are added to a RabbitMQ queue (image_processing) upon product creation.
• A microservice listens for messages, downloads images, compresses them, and stores the compressed versions locally.
• The compressed_product_images field in the database is updated with the paths of the compressed images.

Project Details

Technologies Used

• Language: Go
• Database: PostgreSQL
• Message Queue: RabbitMQ
• Local Storage: File system for image compression

Future Enhancements

• Add authentication and authorization for the API.
• Implement retry mechanisms for failed image processing tasks.
• Use cloud storage (e.g., S3) for compressed images.
• Implement a dead-letter queue for unprocessed messages.

Developer

• Full Name - Dhruv Kalra
• College - SRM Institute of Science & Technology
• Reg No - RA2111003030194
• Course - B.Tech
• Branch - Computer Science & Engineering