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LICENSE (1082, 2023-04-09)
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Rpkg_install.R (312, 2023-04-09)
conda-env-minimal.yml (848, 2023-04-09)
conda-env-no-version.yml (1481, 2023-04-09)
conda-env.yml (12328, 2023-04-09)
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fonts.zip (9916391, 2023-04-09)
pip.conf (102, 2023-04-09)
rpkgs.csv (212, 2023-04-09)
start-notebook.sh (664, 2023-04-09)
start-singleuser.sh (1196, 2023-04-09)
start.sh (5675, 2023-04-09)

# SciPython-Docker This repo contains a `Dockerfile` to build a foundational scientific Python [Docker](https://www.docker.com) image. It is intended to be the foundation of a development environment in a context where installing a bespoke set of required packages from the internet may be cumbersome or discouraged. Built images are hosted on [Docker Hub](https://hub.docker.com/blueogive/scipython-docker). The foundation of the image is the [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge) environment management system developed by the Conda-Forge community. Core packages included in the image include: * CPython (3.10) * Numpy * Pandas * Matplotlib * Seaborn * Jupyter (Notebook, Lab) Additional packages are included for: * Documentation (Sphinx) * Testing (pytest, coverage) * Linting (flake8, pylint) * Environment management (python-dotenv) * Database connectivity (sqlalchemy, pyodbc, pymssql) * Literate programming ([Quarto](https://quarto.org)) In addition, it includes: * R (4.2.3); * RStudio-Server (1.4.x); * [jupyter-rsession-proxy](https://github.com/jupyterhub/jupyter-rsession-proxy), so you can launch an RStudio session from within Jupyter Notebook/Lab, and a collection of R packages centered around the [tidyverse](https://tidyverse.org), and literate programming; * [Golang](https://go.dev) (1.20.x) and [Hugo](https://gohugo.io) (0.111.x); and * [Rust](https://www.rust-lang.org) (1.66.x) ## Usage To instantiate an ephemeral container from the image, mount the current directory within the container, and open a bash prompt within the `base` conda Python environment: ```bash docker run -it --rm -v $(pwd):/home/docker/work blueogive/scipython-docker:latest ``` By default, you will be running as the (unprivileged) `docker` user within the container. The image includes the [gosu](https://github.com/tianon/gosu) utility, which allows you to conveniently execute commands as a less privileged user: ```bash gosu 1000:1000 python myscript.py ``` I borrowed much of the apparatus for enabling the launch of Jupyter Notebook/Lab server processes from the [Jupyter Docker Stacks](https://github.com/jupyter/docker-stacks/), so the commands to start a Jupyter server are similar to those they suggest. ## Jupyter Notebook ```bash docker run -it --init --rm -v $(pwd):/home/docker/work -p 8888:8888 blueogive/scipython-docker:latest start-notebook.sh ``` Note that the `--init` argument is necessary for the Jupyter process to start correctly within the container. ## Jupyter Lab ```bash docker run -it --init --rm -v $(pwd):/home/docker/work -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes blueogive/scipython-docker:latest start-notebook.sh ``` As the container starts, it will echo a bit of output to the console ending with statement similar to: ``` Or copy and paste one of these URLs: http://( or 127.0.0.1):8888/?token= ``` where `` and `` are hexadecimal strings unique to your instance. If the host name of the machine on which you executed the `docker run` command is ``, open a web browser and put the following in the location bar: `http://:8888/?token=` to connect to the Jupyter Lab instance. If you want a shell prompt as a non-root user inside the container without starting a Jupyter server, use the command below, noting that above to start the notebook server but change the command at the end and remove the `--init` argument: ```bash docker run -it --rm -v $(pwd):/home/docker/work -p 8888:8888 blueogive/scipython-docker:latest ``` Pressing `CTRL-d` within the container will cause it to terminate. ## RStudio Server To launch RStudio Server, start the container using either the Jupyter Lab or Jupyter Notebook commands above. Then, connect to the Jupyter server using your browser. If you started Jupyter Lab, use the menu to 'Launch Classic Notebook'. If you started a Jupyter Notebook, skip that step. Within the classic Notebook, click `New`, and select `RStudio`. In recent versions of Jupyter Lab, there is and RStudio launcher on the main/home page. Contributions are welcome.

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