A complete docker package for django which is easy to understand and can be deployed anywhere(supports Data Science related libraries like numpy, scipy etc).
A boilerplate to deploy Django with cool stuff. Also serves as an example project from these tutorial:
Where it is described how this boilerplate was created from scratch so that you can build your own.
Dockerfile.In the Dockerfile, there are detailed instructions on how to install data science dependencies.
PS: Here is a gist which is more useful for Numpy, Pandas, Scipy etc. And it is usable with this project’s docker-compose.yml file. Just you need to replace the Dockerfile from ./compose directory with the one in the gist.
make build inside root directory.make up to start up the project for first time..envs folder.Checkout the commands section for more usage.
A default Django project resides in src directory. So, when you start the project, you will see the following screen in 8000 port:

Also when you access the django container log via make log-web, you will see the following:

To use this project, run this commands:
make up to build the project and starting containers.make build to build the project.make start to start containers if project has been up already.make stop to stop containers.make shell-web to shell access web container.make shell-db to shell access db container.make shell-nginx to shell access nginx container.make logs-web to log access web container.make logs-db to log access db container.make logs-nginx to log access nginx container.make collectstatic to put static files in static directory.make log-web to log access web container.make log-db to log access db container.make log-nginx to log access nginx container.make restart to restart containers.MIT.
Feel free to fork and create PR.