jupyter-repo2docker

jupyter-repo2docker is a tool to build, run, and push Docker images from source code repositories.

repo2docker fetches a repository (from GitHub, GitLab, Zenodo, a Git repository or a local directory) and builds a container image in which the code can be executed. The image build process is based on the configuration files found in the repository.

repo2docker can be used to explore a repository locally by building and executing the constructed image of the repository, or as a means of building images that are pushed to a Docker registry.

repo2docker is the tool used by BinderHub to build images on demand.

Please report Bugs, ask questions or contribute to the project.

Getting started with repo2docker

• Installing repo2docker
  • Prerequisite: Docker
  • Installing with pip
  • Installing from source code
  • Windows support
• Using repo2docker
  • Calling repo2docker
  • Building a specific branch, commit or tag
  • Where to put configuration files
  • Debugging repo2docker with --debug and --no-build
  • Command line API
• Frequently Asked Questions (FAQ)
  • How should I specify another version of Python?
  • What versions of Python (or R or Julia…) are supported?
  • Why is my repository is failing to build with ResolvePackageNotFound ?
  • Can I add executable files to the user’s PATH?
  • How do I set environment variables?
  • Can I use repo2docker to bootstrap my own Dockerfile?
  • Can I use repo2docker to edit a local host repository within a Docker environment?
  • Why is my R shiny app not launching?
  • Why does repo2docker need to exist? Why not use tool like source2image?

How-To guides

• Configure the user interface
  • JupyterLab
  • nteract
  • RStudio
  • Shiny
  • Stencila
• Choose languages for your environment
  • Python
  • The R Language
  • Julia
  • Languages not covered here
  • Using multiple languages at once
• How to automatically create a environment.yml that works with repo2docker
  • The challenge
  • The solution
• Share JupyterLab Workspaces with a repository
• Build JupyterHub-ready images
• Using repo2docker as part of your Continuous Integration
  • Getting Started

Complete list of configuration files

• Configuration Files
  • environment.yml - Install a Python environment
  • Pipfile and/or Pipfile.lock - Install a Python environment
  • requirements.txt - Install a Python environment
  • setup.py - Install Python packages
  • Project.toml - Install a Julia environment
  • REQUIRE - Install a Julia environment (legacy)
  • install.R - Install an R/RStudio environment
  • apt.txt - Install packages with apt-get
  • DESCRIPTION - Install an R package
  • manifest.xml - Install Stencila
  • postBuild - Run code after installing the environment
  • start - Run code before the user sessions starts
  • runtime.txt - Specifying runtimes
  • default.nix - the nix package manager
  • Dockerfile - Advanced environments
• The Reproducible Execution Environment Specification

Contribute to repo2docker

• Contributing to repo2docker development
  • Types of contribution
  • Process for making a contribution
  • Guidelines to getting a Pull Request merged
  • Setting up for Local Development
• The repo2docker roadmap
  • Using the roadmap
  • The roadmap proper
• Architecture of repo2docker
  • Buildpacks
  • ContentProviders
• Design of repo2docker
  • Deterministic output
  • Reproducibility and version stability
  • Unix principles “do one thing well”
  • Composability
  • Pareto principle (The 80-20 Rule)
• Common tasks
  • Running tests
  • Update and Freeze BuildPack Dependencies
  • Creating a Release
  • Update the change log
  • Keeping the Pipfile and requirements files up to date
• Adding a new buildpack to repo2docker
  • Criteria to balance and consider
  • Adding libraries or UI to existing buildpacks

Changelog

• Changelog
  • Version x.x.x
  • Version 0.10.0
  • Version 0.9.0
  • Version 0.8.0
  • Version 0.7.0
  • Version 0.6
  • Version 0.5
  • Version 0.4.1
  • Version 0.2
  • Version 0.1.1
  • Version 0.1