Backend E-commerce Django API

This project is the result of completing The Ultimate Django Series by Mosh Hamedani.
It demonstrates a backend architecture for an e-commerce system and reflects the practical skills and best practices learned throughout all three parts of the course.

🧱 Project Structure

The project is organized into multiple Django apps, each responsible for a specific domain of the system. This structure improves separation of concerns, maintainability, and scalability as the project grows.

• core – Project-specific shared logic such as base configurations, signals, and utilities
• store – Core e-commerce domain: products, collections, carts, orders, pricing, and validations
• likes – Handling user likes and related interactions
• tags – Tagging system for categorizing and filtering entities
• mailer – Email-related logic and background email tasks
• storefront – Project configuration layer (settings, URLs, ASGI/WSGI, Celery setup)

🧠 Key Concepts & Features

🌐 REST API & Architecture

• RESTful API built with Django REST Framework
• Pagination, filtering, searching, and ordering
• Clean separation between domain logic and API layer

🗄 Database & ORM

• Relational database design for an e-commerce system
• Optimized queries using select_related and prefetch_related

🛒 E-commerce Core

• Product catalog and collections
• Shopping cart and order workflow
• Price validation and business rules

🔐 Authentication & Authorization

• Django authentication system
• Custom user model
• Token-based authentication and permission handling (JWT)

📦 Media & File Handling

• Product image uploads
• File and image validation using Django and custom validators

🔔 Signals & Business Logic

• Custom Django signals
• Automatic creation and synchronization of related objects

🧩 Admin Customization

• Customized Django admin interface
• Advanced list views, filters, search, and inline models

🧪 Testing & Code Quality

• Automated testing with pytest
• Test data generation using model_bakery
• Reusable fixtures for consistent and maintainable tests

⚡ Performance & Background Tasks

• Redis used for caching and as a message broker
• Background task processing with Celery
• Task monitoring with Flower
• Performance and load testing using Locust

📬 Email & Background Services

• Local email testing using a Dockerized SMTP server (smtp4dev)
• No real SMTP provider required during development
• Web-based admin panel available for inspecting sent emails

🐳 Docker & Development Environment

• Docker-based development setup
• Reproducible and isolated environment for services and dependencies

🗂 ER Model (Database Design)

🛠 Prerequisites

Make sure you have the following installed:

• Python 3.10+
• pip
• Virtual environment tool (venv or virtualenv)
• MySQL (or PostgreSQL)
• Docker

📦 Installation

1. Clone the repository

2. Create and activate a virtual environment

3. Install dependencies

pip install -r requirements.txt

4. Set environment variables

Create a .env file and configure sensitive settings such as SECRET_KEY and database credentials.

5. Run migrations

python manage.py migrate

6. Start the development server

python manage.py runserver

🧪 Running Tests

pytest

📄 API Documentation

The project includes OpenAPI documentation and an interactive Swagger UI generated from the API schema. The documentation focuses on happy path scenarios, demonstrating the intended and correct usage of the API endpoints rather than edge cases or failure states.

• Swagger schema file
• Swagger documentation page