IRKernel to support R code in Jupyter notebooks Jupyter/r-notebook includes popular packages from the R ecosystem listed below:Įverything in jupyter/minimal-notebook and its ancestor images Nano (actually nano-tiny), tzdata, and unzip TeX Live for notebook document conversion Jupyter/minimal-notebook adds command-line tools useful when working in Jupyter applications. Options for a self-signed HTTPS certificate and passwordless sudo ipython, jupyter kernelgateway, jupyter lab) Tini as the container entrypoint and a start-notebook.sh script as the default commandĪ start-singleuser.sh script useful for launching containers in JupyterHubĪ start.sh script useful for running alternative commands in the container (e.g. With ownership over the /home/jovyan and /opt/conda paths Unprivileged user jovyan ( uid=1000, configurable, see options in the common features section of this documentation) in group users ( gid=100) No preinstalled scientific computing packages Notebook, jupyterhub and jupyterlab packages We use this package manager by default when installing packages. Mamba: “reimplementation of the conda package manager in C++”. Miniforge Python 3.x in /opt/conda with two package managersĬonda: “cross-platform, language-agnostic binary package manager”. Minimally-functional Jupyter Notebook server (e.g., no LaTeX support for saving notebooks as PDFs) It is the basis for all other stacks and contains: Jupyter/base-notebook is a small image supporting the options common across all core stacks. The following sections describe these images, including their contents, relationships, and versioning strategy. The Jupyter team maintains a set of Docker image definitions in the GitHub repository. This section provides details about the first. How you wish to start Docker containers from that image
Using one of the Jupyter Docker Stacks requires two choices:
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