PADDEL

Repository for PADDEL (PArkinson's Disease DEtection Library).

Author: Catalin Andrei, Cacuci

This site can be accessed at paddel.catalin.sh also, the API documentation can be found at api.paddel.catalin.sh/docs.

There is a default user that cannot be deleted with the following credentials:

Username: test

Password: secret

Video guides for the application deployment and model generation can be found on the Paddel YouTube channel.

Project structure

This project has the following components:

PADDEL library

Located in the paddel directory, this is an installable Python package that contains the core of the application.

Notebooks

The notebooks directory contains multiple Jupyter notebooks that were used during the research and development of the PADDEL library.

Web application

Located in the app directory, it is comprized of the following Docker containers:

• proxy: Caddy web server based container that implements a reverse proxy to forward api requests to the api container and web requests to the web container. This container also serves as an SSL certifiate management tool to automate the creation and renewal of these certificates, redirect http requests to https and thus allow for a secure connection across the Internet.

• web: NodeJS-lts based container implementing the SvelteKit JavaScript library. It interacts with the API to fetch the data it needs.

• api: Python 3.9 based container with a FastAPI instance that depends on the PADDEL library. It's main purpose is to serve as an interface between the website and the library. Swagger documentation for the API can be accessed in the /api/docs path of a deployment of the containers.

• database: PostgreSQL 15.2 based container. It is used by the API to persist information.

This folder also containes a sample.env file which contains environment variables used by the containers and some base values. It should be edited to match the running environment both in production and development and saved as .env in the same directory.

Once the .env file is setup launching the containers is as simple as executing make prod or make dev accordingly while having the Docker Engine running. In development mode the web and api containers scan the source code and reload automatically when a change is detected, this will work most of the time, but some changes may still require a restart of the containers.

Restarting the containers is done by re-running the make prod or make dev command.

Stopping the containers is done by running make down, this will also remove the container images, but not image cache, so build time will still be fast after the first build.

Documentation

The docs folder contains the LaTeX documentation for this project, it is written in Spanish.