2.1.0-base-python-3.9.18

workspace-python-ds-pack-2.1.0-base-python-3.9.18

This is the Python Data Science pack image made for Workspaces. The image runs a Jupyterhub server that has PyCharm and VSCode pre-installed with all of the essential and most used packages. The images also comes pre installed with peak-sdk.

Image details

Base image

This image uses python:3.9.18-slim-bookworm as its base which is maintained by the Docker Community.

OS and other details

Debian         GNU/Linux 12 (bookworm)
Linux Kernel   5.10.186-179.751.amzn2.x86_64
Python         3.9.18

Important Linux packages installed

aws-cli        2.7.4
curl           7.88.1
git            2.39.2
jq             1.6
nano           7.2
vim            9.0
fish           3.6.0
zsh            5.9
R              4.3.1
node           18.17.1
docker         24.0.6
htop           3.2.0
pandoc         2.17.1.1
less           590
latex          3.141592653-2.6-1.40.24
vscode-cli     1.82.2

Python libraries installed

ipywidgets                        8.1.0
jupyter-server-proxy              4.0.0
jupyterhub                        4.0.2
jupyterlab-git                    0.42.0
jupyterlab-lsp                    4.2.0
jupyterlab                        3.6.5
jupyterlab_widgets                3.0.8
jupytext                          1.15.1
lckr-jupyterlab-variableinspector 3.0.9
mypy-ls                           0.5.1
nbconvert                         7.8.0
notebook                          6.5.5
pyls-black                        0.4.7
pyls-flake                        80.4.0
pyls-isort                        0.2.2
pyls-mypy                         0.1.8
python-lsp-black                  1.3.0
python-lsp-server[all]            1.4.1
virtualenv                        20.24.5
peak-sdk                          1.0.0
jupysql                           0.10.1

VS Code extensions installed

cweijan.vscode-database-client2   6.6.3    

VS Code Tunneling

The image supports creating remote tunnels. For simplicity the image comes in handy with some node/bash scripts which can be used to initialise, start, stop, and restart the remote tunnels. More info can be found here.

Building the image

To build the image locally, run the docker build command and pass in the required build arguments:

docker build . -t workflow-python-ds-pack-2.1.0-base-python-3.9.18

Using the image

To use the image, select it when configuring the Workspace. If you need to install additional dependencies or add some use case specific environment variables, it can be easily extended.