The IPython kernel for a Conda/virtual environment* must be installed on Jupyter prior to use.
Install kernel
Load the preferred version of Python or Miniconda3 using the command:
module load python
or
module load miniconda3
Replace "python" or "miniconda3" with the appropriate version, which could be the version you used to create your Conda/venv environment. You can check available Python versions by using the command:
module spider python
Run one of the following commands based on how your Conda/virtual environment was created. Replace "MYENV" with the name of your Conda environment or the path to the environment.
If the Conda environment was created via conda create -n MYENV command, use the following command:
~support/classroom/tools/create_jupyter_kernel conda MYENV
If the Conda environment was created via conda create -n /path/to/MYENV command, use the following command:
~support/classroom/tools/create_jupyter_kernel conda /path/to/MYENV
If the Python virtual environment was created via python3 -m venv /path/to/MYENV command, use the following command
~support/classroom/tools/create_jupyter_kernel venv /path/to/MYENV
The resulting kernel name appears as "MYENV [/path/to/MYENV]" in the Jupyter kernel list. You can change the display name by appending a preferred name in the above commands. For example:
~support/classroom/tools/create_jupyter_kernel conda MYENV "My Research Project"
This results in the kernel name "My Research Project" in the Jupyter kernel list.
Install Jupyterlab Debugger kernel
According to Jupyterlab page, debugger requires ipykernel >= 6. Please create your own kernel with conda using the following commands:
$ module load miniconda $ conda create -n jupyterlab-debugger -c conda-forge "ipykernel>=6" xeus-python $ ~support/classroom/tools/create_jupyter_kernel conda jupyterlab-debugger
You should see a kernelspec 'conda_jupyterlab-debugger' created in home directory. Once the debugger kernel is done, you can use it:
1. go to OnDemand
2. request a JupyterLab app with kernel 3
3. open a notebook with the debugger kernel.
4. you can enable debug mode at upper-right kernel of the notebook
Remove kernel
If the envirnoment is rebuilt or renamed, users may want to erase any custom jupyter kernel installations.
rm -rf ~/.local/share/jupyter/kernels/${MYENV}
Manually install kernel
If the create_jupyter_kernel script does not work for you, try the following steps to manually install kernel:
# change to the proper version of python
module load python
# replace with the name of conda env
MYENV=useful-project-name
# Activate your conda/virtual environment
## For Conda environment
source activate $MYENV
# ONLY if you created venv instead of conda env
## For Python Virtual environment
source /path/to/$MYENV/bin/activate
# Install Jupyter kernel
python -m ipykernel install --user --name $MYENV --display-name "Python ($MYENV)"