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This project forked from b08x/docker-stacks-jupyter-ruby-nlp

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Ready-to-run Docker images containing IRuby Notebook applications

Ruby 19.24% Jupyter Notebook 58.04% Dockerfile 22.71%

docker-stacks's Introduction

Docker Stacks: Jupyter Python Ruby

CI

The RubyData Jupyter Notebook Docker Stack is designed to provide a seamless environment for data processing and analysis using Ruby and Jupyter notebooks. This stack includes a curated selection of essential Ruby gems to facilitate efficient data extraction, transformation, and loading (ETL) processes.

RubyData Docker stacks are a set of ready-to-run Docker images containing Jupyter and data tools for Rubyists.

This repository is based on rubydata/docker-stacks.

Quick Start

Minimal Image

Data Science Image

NLP Image

Building Images

Using the Rakefile

The Rakefile defines the following key tasks:

  • pull/base_image/{image} - Pulls the base image for each supported image (minimal, datascience, etc.)
  • build/{image} - Builds the Docker image, depends on pulling the base image
  • tag/{image} - Tags the built image with the Git commit sha
  • push/{image} - Pushes the image to the Docker registry

It also defines composite tasks:

  • build-all - Builds all images in parallel
  • tag-all - Tags all images
  • push-all - Pushes all images

These tasks leverage variables defined at the top like ALL_IMAGES, BASE_IMAGES, OWNER to programmatically handle building, tagging and pushing multiple images.

Individual tasks are invoked for each image, while the composite tasks iterate over ALL_IMAGES to perform the action for all of them.

This Rakefile automation handles common repetitive Docker image operations and allows building, tagging and pushing multiple images with simple rake commands.

License

MIT License

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