BMI Tracker

BMI Calculator Web Application

Video Demo

youtube video

Description

A full-stack web application designed to track Body Mass Index (BMI) over time. Unlike simple static calculators, this project leverages FastAPI for a high-performance backend and SQLite for data persistence, allowing users to store and analyze their history log.

Key Technologies: Python, FastAPI, SQLite, HTML/Bootstrap.

• Persistent History Tracking:
  • Utilizes a SQLite database to store user records permanently.
  • Performs backend calculations to analyze weight trends and percentage changes compared to previous entries.

The application features:

• BMI Calculation: Users input their weight and height, and the app calculates their BMI and categorizes it.
• History: Users can view their BMI calculation history, including the percentage change in BMI from previous records.
• CORS-enabled: The app allows communication between the frontend and backend even when hosted on different origins, thanks to FastAPI’s CORS middleware.

Files

• app.py: This is the FastAPI backend. It handles the POST request to calculate BMI and the GET request to retrieve the BMI history.
• index.html: This HTML file contains the frontend interface for the user to input their weight and height, see BMI calculations, and view the history.
• requirements.txt: Lists the Python dependencies required for the project.

Features

• BMI Calculation:

  • The app calculates BMI using the formula:
    [ \text{BMI} = \frac{\text{weight (kg)}}{\text{height (m)}^2} ]
  • It classifies BMI into categories (Underweight, Normal, Overweight, Obese).

• History Feature:

  • Users can track their previous BMI calculations along with the percentage change between them.
  • The app saves BMI history in an SQLite database.

• Responsive Design:

  • The app uses Bootstrap to make the frontend responsive and user-friendly across different devices.

Setup and Installation

1. Clone the repository:

   git clone https://github.com/A-Najjar/FastAPI-BMI-App.git
   cd bmi_calculator
   

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies:

pip install -r requirements.txt

4. Run the FastAPI application:

uvicorn app:app --reload

you can add /docs to the url to get to the swaggar ui

5. Access the frontend:

   • Open the index.html file in your browser, or serve it using a local HTTP server (e.g., python -m http.server).

6. Test the application:

   • Enter your weight and height on the frontend.
   • Click "Calculate BMI" to get your BMI result.
   • Click "Load History" to view your previous BMI records.