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

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

Base: Debian 12 - Bookworm

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

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

These programming languages are included:

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

The installed Python libraries are:

• jupyter ipykernel docutils pyyaml pylint
• h5py
• tensorflow keras
• pandas pandas-datareader
• numpy scipy sklearn
• matplotlib seaborn plotly graphviz
• opencv-python-headless
• imutils
• sqlalchemy
• pyautogui
• yfinance alpha_vantage nasdaq-data-link
• financetoolkit financedatabase
• statsmodels
• requests_cache

You need the following things to run this:

• Docker
• Visual Studio Code

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.

1. Get the source: clone this repository using git or download the zip

2. 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...

3. Open the file notebooks\test.ipynb

4. You might get a warning message for "untrusted" Notebook content.

   Click Trust to allow executing the content of the Notebook.

5. 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.

6. Enjoy! 😎

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