davidelanz/jupyter repository overview

⁠Jupyter-Docker | Docker image enabled with Jupyter

Repository for the davidelanz/jupyter⁠ docker image. It provides a quick, dockerized set up for Jupyter Lab with multiple Conda environments.

	Features
	The image comes with jupyterlab_code_formatter⁠ already installed
	The image comes with LSP Python language server for JupyterLab⁠ (jedi 0.17.2) already installed
	The image comes already with a Python3.7 Conda environment with OpenCV support called opencv-py3.7

• Loading the image⁠
  • Mount from DockerHub⁠
  • Build from GitHub⁠
• Using the image⁠
  • Creating and loading new Conda environment⁠

⁠Loading the image

⁠Mount from DockerHub

Download the image from davidelanz/jupyter⁠, then mount the container (the image exposes JupyterLab on the 8888 port):

docker run -p CONTANER_PORT:8888 -v EXTERNAL_FOLDER:/workspace --name CONTAINER_NAME davidelanz/jupyter

Your workspace will be available at localhost:CONTANER_PORT⁠.

⁠Build from GitHub

The image can be directly built from the GitHub repository:

$ git clone https://github.com/davidelanz/jupyter-docker
$ cd jupyter-docker/
$ docker build . -t davidelanz/jupyter

⁠Using the image

⁠Creating and loading new Conda environment

You can create a new enviroment as follows (you can easily do it from the JupyterLab console):

conda create -y --name <DESIRED_ENV_NAME> python=<DESIRED_PYTHON_VERSION>

Then you can load it to JupyterLab as follows:

conda activate <DESIRED_ENV_NAME> && conda install -y ipykernel && python -m ipykernel install --name <DESIRED_ENV_NAME> --user

With Jupyter installed you get the list of currently installed kernels with:

jupyter kernelspec list

If you want to uninstall an unwanted kernel:

jupyter kernelspec uninstall <UNWANTED_KERNEL>