DiseaseDx: Disease Diagnosis

DiseaseDx is a disease diagnosis system developed as part of my final project in Computer Science.

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Table of Contents

1. About the Project
2. Setting Up the Local Environment
3. Running the Project
4. Configuring VS Code Debugging
5. Diagrams
6. Technologies Used

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About the Project

DiseaseDx is a system designed to assist in diagnosing diseases by evaluating symptoms and test results using an evaluation tree. It leverages SQLAlchemy for database interactions and Streamlit for front-end with caching and performance optimization.

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Setting Up the Local Environment

Follow these steps to set up the project locally:

Prerequisites

• Python 3.13
• pipenv for dependency management
• If running on Windows it also needs protobuf==5.27.0

Installation

# Check if pipenv is installed
$ pip show pipenv

# Install pipenv if not installed
$ pip install pipenv

# Install dependencies from Pipfile
$ pipenv install

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Running the Project

You can run the project in three ways:

1. Using a MySQL Database:

   • Create a MySQL database called diseasedx_test.
   • Set the environment variables MYSQL_USER and MYSQL_PASS with your MySQL credentials.

2. Using a SQLite Database in Memory:

   • Modify the connection string in db_config.py to use SQLite in-memory mode.

3. Using a Local SQLite Database:

   • Modify the connection string in db_config.py to use a local SQLite database (e.g., sqlite:///mylocaldb.db).
   • Install the SQLite extension for VS Code to interact with the database.

Tip: For the local SQLite database, after running the project and creating mylocaldb.db, you can open it in VS Code:

• Press CTRL + SHIFT + P, type SQLite: Open Database, and select mylocaldb.db.
• A blade will open in the bottom-left corner where you can interact with the database.

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Configuring VS Code Debugging

To debug the project in VS Code, you can use the following launch.json configuration:

{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python Debugger: Current File",
            "type": "debugpy",
            "request": "launch",
            "program": "${file}",
            "console": "integratedTerminal",
            "justMyCode": false
        },
        {
            "name": "Python:Streamlit",
            "type": "debugpy",
            "request": "launch",
            "module": "streamlit",
            "args": [
                "run",
                "main.py"
            ],
            "console": "integratedTerminal",
            "justMyCode": false,
            "cwd": "${workspaceFolder}/src"
        }
    ]
}

Steps to Configure:

1. Open the .vscode folder in your project directory.
2. Create or edit the launch.json file with the above configuration.
3. To debug the Streamlit app:
   • Open the Debug panel in VS Code (CTRL + SHIFT + D).
   • Select the Python:Streamlit configuration.
   • Click the green "Start Debugging" button.

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Diagrams

Class Diagram

Object Diagram

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Technologies Used

• Python: Core programming language for the project.
• SQLAlchemy: ORM for database interactions.
• Streamlit: Used as front-end for caching and performance optimization.
• MySQL: Primary database for production.
• SQLite: Alternative database for local development and testing.

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Feel free to contribute or reach out with any questions!