Building a simple book library application can be a rewarding experience, especially when you incorporate technologies like Flask and SQLite. This guide will walk you through the steps to set up your very own Book Library application!

Features Overview

This application will include the following features:

  • User login, logout, registration, password change, and updating personal information.
  • Users can borrow and return books, as well as write and delete comments.
  • Administrators can add, delete, and update book information.
  • Administrators can delete comments as needed.

Screenshots of the Application

Here’s a sneak peek into various pages of your application:

  • Index Page: index page
  • User Detail Page: user detail page
  • Book List Page: book list page
  • Book Detail Page: book detail page

Installation Guide

Follow these straightforward steps to clone and set up your application:

git clone https://github.com/magic-akari/BookLibrary.git
cd BookLibrary
python3 -m venv venv
source .venv/bin/activate
pip install -r requirements.txt
python3 run.py

Don’t forget to press CTRL+C to terminate the server and use `deactivate` to exit the virtual environment.

While Python 3 is recommended, this project is also compatible with Python 2.

Running the Application with Docker

If you prefer to use Docker for a simplified setup, here’s how you can do it:

sh
docker build -t booklibrary:latest .
docker run -ti -v pwd:app -p 4000:4000 booklibrary:latest

Add the `-v` option to ensure that your changes in local files are reflected within the Docker container. To run in production mode, you can skip this `-v` flag.

Dependencies

Your project will require several dependencies, which you can find at these links:

Troubleshooting Tips

If you encounter any issues while setting up or running your application, here are some troubleshooting tips:

  • If the server doesn’t start, double-check your Python version and ensure that all dependencies are properly installed.
  • Ensure that your virtual environment is activated before running the application.
  • If using Docker, make sure that the Docker daemon is running and that you’re using the correct commands.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

About the Author

Hemen Ashodia

Hemen Ashodia

Hemen has over 14+ years in data science, contributing to hundreds of ML projects. Hemen is founder of haveto.com and fxis.ai, which has been doing data science since 2015. He has worked with notable companies like Bitcoin.com, Tala, Johnson & Johnson, and AB InBev. He possesses hard-to-find expertise in artificial neural networks, deep learning, reinforcement learning, and generative adversarial networks. Proven track record of leading projects and teams for Fortune 500 companies and startups, delivering innovative and scalable solutions. Hemen has also worked for cruxbot that was later acquired by Intel, mainly for their machine learning development.

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