jupyter-devbox

A Docker development box for Jupyter Notebook's with a focus on Computer Vision, Machine Learning, Statistics and Visualization.

What is this?

This is a Docker container based on Debian Linux (see Dockerfile). It sets up a Python/Jupyter Notebook development environment for Visual Studio Code. The pre-installed libraries include OpenCV, Tensorflow, Keras, Numpy, Pandas, Sklearn, Scipy, Matplotlib, Seaborn, Imutils, SqlAlchemy.

What is pre-installed?

Base: Debian 11 - Bullseye

On top of the base image the following tools are installed:

zsh, git, cmake
curl, wget
imagemagick, gnuplot, graphviz

These programming languages are included:

Python 3 (including wheel, setuptools, pip)
C & C++ (g++)

The installed Python libraries are:

jupyter ipykernel docutils pyyaml pylint h5py
tensorflow keras
numpy pandas sklearn scipy
matplotlib seaborn
opencv-python
imutils
sqlalchemy
pyautogui
yfinance alpha_vantage quandl
pandas-datareader requests_cache

Prerequisites

You need the following things to run this:

Docker
Visual Studio Code

How to run this?

There are two ways of setting the container up.

Either by building the container image locally or by fetching the prebuild container image from the Github container registry.

Building the Container Image locally using VSCode

Get the source: clone this repository using git or download the zip
In VSCode open the folder in a container (Remote Containers: Open Folder in Container):

This will build the container image (Starting Dev Container (show log): Building image..)

Which takes a while...

Then, finally...
Open the file notebooks\test.ipynb
You might get a warning message for "untrusted" Notebook content.

Click Trust to allow executing the content of the Notebook.
You are now able to edit cells and run their content interactively.

You might also run your scripts inside your browser at http://localhost:8888/

And you can also read and run your scripts via the Github website: notebooks/test.ipynb.
Enjoy! 😎

Fetching the prebuild container image

This container image is published to the Github Container Registry (GHCR).

You may find the package here: https://github.com/jakoch/jupyter-devbox/pkgs/container/jupyter-devbox.

You can install the container image from the command line:

docker pull ghcr.io/jakoch/jupyter-devbox:latest

You might also use this container image as a base image in your own Dockerfile:

FROM ghcr.io/jakoch/jupyter-devbox:latest