AI4Devs - Backend Demo

This project showcases the process of translating a Python-based backend application into Node.js and enhancing it with Redis for improved performance. It serves as a comprehensive demonstration for the backend session of the AI4Devs Master program.

Table of Contents

• AI4Devs - Backend Demo
  • Table of Contents
  • Project Overview
    • Objectives
  • Technologies Used
  • Project Structure
    • 1. /starter
    • 2. checkpoints/starter-to-node-working
    • 3. checkpoints/starter-to-node-redis
  • Getting Started
    • Prerequisites
    • Installation and Usage

Project Overview

This repository demonstrates the step-by-step translation of a Python Flask backend application into a Node.js application using TypeScript and Sequelize. Additionally, it integrates Redis to implement a distributed caching system, enhancing the application's performance and scalability.

Objectives

1. Language Translation: Convert the backend from Python to Node.js while maintaining functionality and structure.
2. Performance Enhancement: Integrate Redis to implement caching mechanisms, reducing database load and improving response times.
3. Best Practices: Apply software development best practices throughout the migration and enhancement process.

Technologies Used

• Backend Frameworks:
  • Python: Flask
  • Node.js: Express.js with TypeScript
• Database:
  • PostgreSQL
  • ORM: Sequelize (for Node.js), SQLAlchemy (for Python)
• Caching:
  • Redis
• Containerization:
  • Docker & Docker Compose
• Others:
  • TypeScript, Sequelize-Typescript, dotenv

Project Structure

1. /starter

The initial Python-based backend application using Flask. It includes:

• Flask Application: Handles HTTP requests and interacts with the PostgreSQL database.
• SQLAlchemy ORM: Manages database models and migrations.
• Docker Setup: Contains Dockerfile and docker-compose.yml for containerization.

2. checkpoints/starter-to-node-working

This branch/project focuses on translating the Python Flask application to a Node.js application. Key features include:

• TypeScript Integration: Ensures strong typing and better code maintainability.
• Sequelize ORM: Manages database interactions with PostgreSQL.
• Express.js: Serves as the web framework for handling routes and middleware.
• Docker Configuration: Updated to accommodate Node.js environment.

A fully functional version of this translation is available in the starter-to-node-working directory.

3. checkpoints/starter-to-node-redis

Building upon the Node.js translation, this phase integrates Redis to implement a distributed caching system. Enhancements include:

• Redis Integration: Implements caching for product data to enhance performance.
• Cache Management: Ensures cache invalidation upon creating, updating, or deleting products.
• Docker Update: Adds Redis service to the docker-compose.yml for seamless integration.

The enhanced version with Redis is available in the starter-to-node-redis directory.

Getting Started

Follow these instructions to set up and run the project locally.

Prerequisites

• Docker & Docker Compose

Installation and Usage

1. Clone the Repository

   git clone https://github.com/your-username/ai4devs-backend-demo.git
   cd ai4devs-backend-demo

2. Navigate to the First Project Phase

   • Python Starter: starter/

3. Set Up the Starter Project

   You have the readme.md of this project with the instructions to run it.

4. Testing prompts: Python to Node.js

   To accompplish the first goal you have all the prompts used to guide the AI along the way. Also, all the most frequet errors faced during the process.

   • Python to Node.js

   If you're facing any issue with the starter-to-node-working project, you can find the solution here.

5. Testing prompts: Adding Redis

   To accompplish the second goal you have all the prompts used to guide the AI along the way. Also, all the most frequet errors faced during the process.

   • Adding Redis

   If you're facing any issue with the starter-to-node-redis project, you can find the solution here.