Library Management System

About the Project

This is a Library Management System project developed with Django. The platform allows comprehensive management of books, authors, categories, patrons, and loan control, all with a robust authentication and permissions system.

The goal was to build a complete and functional web application, applying concepts learned in my journey with Python and Django, while exploring modern tools to optimize the development cycle.

Main Features

• Catalog Management: Complete CRUD for Books, Authors, and Categories.
• Patron Control: Registration and management of patron information.
• Loan System:
  • New loan registration with automatic book inventory updates.
  • Return registration.
  • Separate listings for active and returned loans.
  • Smart search by book, patron name, or CPF (Brazilian ID).
• Authentication and Permissions: The system uses Django's authentication and permissions system to control access to different functionalities, ensuring only authorized users can perform certain actions.

Technologies Used

• Backend: Python, Django
• Frontend: HTML, CSS, Bootstrap 5
• Database: PostgreSQL (configured to run with Docker)
• Testing: Pytest, Pytest-Django
• Containerization: Docker, Docker Compose

▶️ Click here to watch the video demonstration

How to Run the Project Locally

The project is containerized with Docker, making environment setup easier.

1. Clone the repository:

   git clone https://github.com/CFBruna/library_management.git
   cd library_management

2. Configure environment variables:

   • Rename the .env.example file to .env.
   • If desired, modify the values inside the .env file (not strictly necessary to run locally, but it's a good practice).

3. Start the containers with Docker Compose:

   docker-compose up --build

4. Access the application:

   • Open your browser and navigate to http://localhost:8000.

My Development Process and the Role of AI

From the beginning, my goal was not just to build a project, but also to optimize the process. I was responsible for the entire application architecture: I designed the models, structured the views with business logic, and defined permission rules.

In this process, I used Artificial Intelligence tools as a development assistant. Instead of spending time on repetitive tasks, I directed the AI to:

• Generate automated tests: With my knowledge of what needed to be tested, I guided the AI to create unit and integration tests with Pytest, which accelerated code quality assurance.
• Structure the frontend: The base.html template and other templates were generated with AI assistance, following the design guidelines I established.
• Configure the deployment environment: I used AI to help write the Dockerfile and docker-compose.yml, based on my project requirements.

I believe that the most important skill of a modern developer is knowing how to translate a business need into a functional technical solution, using the best and most efficient tools available. This project is a reflection of that philosophy.