Deploy deepgalaxy project with Django

This project is a Django web applicationn for DeepGalaxy project, consists of several main components:

• Image uplolad and display djangoimageupload

• Machine learning model deployment deploymachinelearning.com

• Polished frontend user interaction

• It contains tests for both ML code and server code

This application is (going to be) hosted in one of the main cloud provider, in order to provide public access.

The code structure

In the research directory there are:

• code for training machine learning models (TBD).

In the backend directory there is Django application. Under /apps there are:

• endpoints: Django Rest application

• ml: deepgalaxy model code and training dataset

In the docker directory there are dockerfiles for running the service in the container.

How to use

• Install dependencies from requirements.txt

• To clean historic data, you can

  >>> rm db.sqlite3
  >>> python manage.py makemigrations
  >>> python manage.py migrate
  

• To run the server, you can

  python manage.py runserver

  Open your browser and go to 0.0.0.0:8000/post/ to start, have fun! ;)

• To test the code and endpoint (TBD)

  >>> python manage.py test apps.ml.tests
  >>> python manage.py test apps.endpoints.tests
  >>> python manage.py test apps
  

Containerization

The docker compose file consists of two services:

• Nginx: our web server and reverse proxy. Where requests from the internet arrive first and get handled quickly.
• WSGI server: uses Gunicorn, a production-grade WSGI server. Worker that actually calls Python code when a request comes in.

>>> docker-compose down -v
>>> docker-compose up --build