dataVisualizer

version alpha

DataVisualizer is a proof of concpet for Flask-based application for data visualization. This application is containerized using Docker and can be run in a local environment. This README will guide you through setting up and running the application in a Docker container.

Prerequisites

Make sure you have the following installed on your machine:

• Docker
• Docker Compose
• Python 3.9 (for testing outside of Docker if needed)
• pip (Python package manager)

Environment Variables

Before running the application, ensure to create an .env file in the root directory that contains the required infos

.env file:

DB_PATH="sqlDB.db"
OPENAI_API_KEY="Your_openai_apikey"
OPENAI_ORGA_ID="Your organization ID"
OPENAI_PROJECT_ID="Your project ID"

How to get openai api key ?

• Create an openAI account
• Get my API_KEY

to get your organization ID and Project ID go to your settings page once you're done creating your profile.

Running the Application

Using Docker Compose

The easiest way to run the application is by using Docker Compose. This will build the Docker image and start the application in a container.

1. Clone the repository:

   git clone https://github.com/your-repo/data-visualizer.git
   cd data-visualizer

2. Build and run the container:

   docker-compose up -d

   This will:

   • Build the Docker image from the provided Dockerfile.
   • Start a container for the application.
   • The application will be available locally on port 8000.

3. Access the application: Open your web browser and go to:

   http://localhost:8000
   

Stopping the Application

To stop the running containers, use:

docker-compose down

This will stop and remove the running containers but leave the built image intact.

Project Structure

/app
│   ├── dataVisualizer.py   # Main Flask application
│   ├── init_data.py        # Script to initialize database
│   ├── Dockerfile          # Dockerfile for building the container
│   ├── entrypoint.sh       # Entrypoint script for the container
│   ├── requirements.txt    # Python dependencies
│   ├── .env                # Environment variables
│   └── templates/          # HTML templates for the Flask app
│
└── docker-compose.yml      # Docker Compose configuration

Dockerfile

The Dockerfile performs the following tasks:

• Sets up a Python environment with required dependencies.
• Copies the application code into the container.
• Installs the necessary Python packages.
• Runs the Flask application using Gunicorn in production mode.

Running Without Docker (Optional)

If you wish to run the application outside of Docker, you can do so using Python and pip.

1. Create a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate   # On Linux/Mac
   venv\Scriptsctivate      # On Windows

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the Flask application:

   export FLASK_ENV=production
   python dataVisualizer.py

4. Access the application: Open your browser and navigate to:

   http://localhost:8000
   

Troubleshooting

• Connection Refused Error: Ensure that Docker Compose is mapping the correct port (8000:8000). Check for any firewall settings that may block access to port 8000.
• Permission Errors: Make sure the entrypoint.sh script has the correct execution permissions. Run:

  chmod +x entrypoint.sh

License

This project is licensed under the MIT License.