This is a starter data science docker dev environment.
The Dev environment comes with R, Python 3.8, and many of the standard data science python packages pre-installed (see the requirements.txt file). You can fork this repository or copy/paste the files into your repo and then modify them for your needs!
You can open the dev environment in GitPod by clicking the "Open in GitPod Button at the top of this README, or open on your system with VSCode by cloning this repository, opening it with VSCode, and then using the Remote Development extension to "Reopen in Container".
There are two sets of config files in this repo: one for local development and the other for development on Gitpod. Both use the same dockerfile to specify the dev environment, but since each executes on a different platform (the first via VSCode and Docker installed on your machine and the second on Gitpod's cloud servers) their settings are specified through seperate configuration files.
All config files for local development can be found in the .devcontainer directory. There are two files: devcontainer.json and Dockerfile. The devcontainer.json file contains information like the name of the dev container, its context, the dockerfile its based on, settings, VSCode extensions to install in the container, commands to run once the container has been created, etc. There are many settings you can change here to customize your environment. See the documentation here for a comprehensive list of all settings.
We've setup the Gitpod environment to use the same Dockerfile as is used in the local dev environment to make things as consistent as possible. Gitpod, however, uses the .gitpod.yml file rather than the devcontainer.json file to configure settings, extenstions, commands, etc. Visit the docs here for a comprehesive list of all configuration options! Also, checkout our internal gitpod docs/tips/tricks repo here for tips on customization.