Seitenhistorie

...

https://jakevdp.github.io/blog/2017/12/05/installing-python-packages-from-jupyter/#How-to-use-Pip-from-the-Jupyter-Notebook

Install individual Python

...

kernel

Jupyter allows you to work in with your own virtual environment using the Python modules installed on the HPC. Start by loading the Python interpreter/module you want to work with, . You can use e.g. conda for this task. Start by creating a new conda environment:

module purge   ##just in case you are using jupyter terminal
module load PythonMiniconda/3.11.3

...

1
conda create -p /gpfs/project/$USER

...

python -m venv --prompt py311 --system-site-packages/py310 python=3.10
conda activate /gpfs/project/$USER/py311

PIP_CONFIG_FILE=/software/python/pip.conf pip install --user --upgrade pip setuptools wheel

Activate this environment and install all packages you want to work with - at least ipykernel must be installed

py310

Hint: this only works if you have defined a .condarc with channels pointing to our repo server (see also Conda)

Install the programs that you need with conda install , at least  ipykernel must be installed:

conda 

source /gpfs/project/$USER/py311/bin/activate

PIP_CONFIG_FILE=/software/python/pip.conf pip install ipykernel

Create a new file "kernel.sh" in the main directory of your environment and make it executable

cd /gpfs/project/$USER/py311py310
vi kernel.sh

Contents of the file kernel.sh:

 
----------------------------------------------------
#!/bin/bash
sourceexport PYTHONPATH=/gpfs/project/$USER/py311/bin/activate/py310/lib/python3.10/site-packages
export PATH=/gpfs/project/$USER/py310/bin:$PATH
exec python -m ipykernel $@
----------------------------------------------------

Make the file executable with

chmod a+x kernel.sh

Create a new directory for your kernel in your /home/.local/share folder

mkdir -p /home/$USER/.local/share/jupyter/kernels/py311py310
cd /home/$USER/.local/share/jupyter/kernels/py311py310

Create a new file "kernel.json" with contents (!!replace $USER with your explicit username here!!)

{
"argv": [
  "/gpfs/project/$USER/py311py310/kernel.sh",
  "-f",
  "{connection_file}"
 ],
 "display_name": "VenvPython 3.10 (py311conda)",
 "language": "python",
 "metadata": {
  "debugger": true
 }
}

In your next jupyterhub session a new kernel with the name "venv (py311Python 3.10 (conda)" will then be available.

Hint: This seems to only work with Python versions < 3.11 !