Simple shareable local Data Science environments

A simple user interface allowing you to easily run Jupyter or Streamlit through virtual environments on your Windows or Mac computer

You don’t need to learn or use any Docker commands at all

Select a standard Jupyter/Streamlit starting point, or specify a Binder-ready git repo

Choose a workspace folder on your computer’s hard drive

This is to store your project notebook files and data

Launch straight into Jupyter Lab or Notebook in your browser

No need for tokens or passwords

Export the project and share with clients or colleagues

Clone as a pre-built Conda environment to be reused whenever and wherever it is needed, or send to a client as a standalone file so they can run your work exactly as you last saw it without any command line instructions

Since environments used by ContainDS can run Linux, it can often be easier to build and maintain these isolated virtual environments than building and installing packages natively in Windows or MacOS.Getting StartedDownload ContainDS