Enable NCL Kernel in Jupyterhub#
Issue#
Can’t use NCL (Python) as kernel in Jupyter
This tutorial won’t work
In order to use NCL in Jupyter notebooks you need to install this in
your conda env. The setup.py already includes the steps described in Kernels,
so you do not need to execute instructions again!
For Jupyterhub, there is an additional step to do after installing the kernel.
Solution#
The solution is to add the location of the conda env to the PATH using
the kernel.json.
How?#
The easiest way to add path to missing library is to modify the
kernel.json as described
here <own_kernel>.
For the ncl example, the original generated kernel.json looks
like this:
{
"argv": [
"/path/to/your/conda_env/bin/python",
"-m",
"ncl_kernel",
"-f",
"{connection_file}"
],
"display_name": "NCL",
"language": "ncl",
"name": "ncl_kernel"
}
The modified kernel.json should look like this:
{
"argv": [
"/path/to/your/conda_env/bin/python",
"-m",
"ncl_kernel",
"-f",
"{connection_file}"
],
"display_name": "NCL",
"language": "ncl",
"name": "ncl_kernel",
"env": {
"PATH":
"$PATH:/path/to/your/conda_env/bin"
}
}
You need to restart the kernel after you change this.
Note
Currently, the installation fails with IPython < 4 due to this line. The workaround is to import from the paths and not from utils.path.
Note
kernel.json can be found in
.local/share/jupyter/kernels/your_kernel/.