Microblog Python Project Using ChatGPT as a Co-Pilot

Overview

I documented my experience building a microblog service in Python while using ChatGPT as a development assistant. Rather than a finalized blog post, I preserved this as a working note for future reference, with the complete project available on GitHub.

Project Goals

As someone who writes Java professionally, I wanted to explore Python ORMs through a practical test project. I leveraged ChatGPT to research technologies and generate code throughout development.

Key Components

Architecture:

• SQLite database for persistence
• Flask web framework
• Single admin user with authentication
• Public and admin API endpoints with different access levels

Data Model: Posts contain: ID, content, created timestamp, visibility flag, deleted timestamp, and edited timestamp.

Endpoints:

• Public client controller (unauthenticated, visible posts only)
• Admin controller (JWT-authenticated, all posts accessible)

Technology Selection

After prompting ChatGPT about Python ORMs, I selected Peewee, which I found to be simple compared to SQLAlchemy and Django ORM alternatives.

Development Process

ChatGPT maintained conversation context, allowing me to reference previously discussed models when requesting new features. I iteratively asked the AI to:

• Generate database models
• Build service and controller classes
• Add JWT authentication
• Create user management endpoints

I validated API functionality using Postman, then copied responses into ChatGPT to generate documentation.

Conclusion

AI-assisted development significantly accelerates coding velocity. While ChatGPT’s output requires refinement, it provides a strong foundation for rapid prototyping.