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Miniconda on Heroku Example App

This repository contains two things:

  • A Dockerfile, which installs scikit-learn with miniconda, and a few pip dependencies.
  • A Flask webapp, which utilizes basic functionality of scikit-learn.

All Anaconda packages are supported—scikit-learn is just being used here as an example.

☤ Advantages over Conda Buildpack:

  • No slug size limit (Anaconda packages can be very large).
  • Exact Miniconda environment, from Continuum Analytics.

☤ Deploy this Application:

Deploy with the Container Registry and Runtime: $ sudo usermod -a -G docker $USER ($ heroku plugins:install heroku-container-registry) not working anymore... $ heroku plugins:install @heroku-cli/plugin-container-registry $ heroku container:login

 $ git clone https://github.com/heroku-examples/python-miniconda
 $ cd python-miniconda
 
 $ heroku create
 $ heroku container:push web
 ($ heroku:release web) also not working for me
 $ heroku container:release web
 $ heroku open

When you're running out of disk: Docker provides a single command that will clean up any resources — images, containers, volumes, and networks — that are dangling (not associated with a container):

docker system prune

To additionally remove any stopped containers and all unused images (not just dangling images), add the -a flag to the command:

docker system prune -a

docker images -a | grep "pattern" | awk '{print $3}' | xargs docker rmi

All the Docker images on a system can be listed by adding -a to the docker images command. Once you're sure you want to delete them all, you can add the -q flag to pass the Image ID to docker rmi:

List:

docker images -a

Remove:

docker rmi $(docker images -a -q)

✨🍰✨