Docker Deployment Guide

This guide explains how to deploy the project using Docker and Docker Compose.

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Project Overview

This is a Django learning project that supports user registration, blog posts, and threaded comments. The project includes:

• A custom user model with a unique email address and homepage
• Secure storage and rendering of user-generated content (HTML sanitization and XSS protection)
• Nested comments (parent/replies)
• CAPTCHA protection against spam
• Clean and maintainable code structure with docstrings, help_text, reusable forms, and class-based views

Features

• Modern Django project structure (users, posts apps)
• Class-based views and reusable mixins
• Pagination and sorting for posts and comments
• Docker environment for quick setup
• Examples of custom validators and extending Django's built-in models

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Requirements

• Docker and Docker Compose must be installed on your system.
• The project repository should contain all required files, including:
  • docker-compose.yml
  • Dockerfile
  • .env
  • and any other files required to run the application.

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Deployment Steps

1. Clone the repository

git clone https://github.com/AlexTkDev/spa.git
cd spa

2. Configure environment variables

Rename the .env.example file in the project root to .env and fill in your environment variables:

SECRET_KEY=""

# Database
DATABASE_NAME=***
DATABASE_USER=***
DATABASE_PASSWORD=***
DATABASE_PORT=5432

These variables are used to configure the database connection.

Generate a Django secret key using the following command (Linux/macOS), then paste it into your .env file:

python -c 'from django.core.management.utils import get_random_secret_key; print(get_random_secret_key())'

3. Build and start the containers

From the project root (where docker-compose.yml and Dockerfile are located), run:

docker-compose up -d

4. Verify the deployment

Once the containers are running, the application will be available at:

http://localhost:9000

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Using the Pre-built Docker Image

Instead of building the project locally, you can download the pre-built image from Docker Hub and run it on your machine:

docker pull alextkdev/spa:prod