"Link to [install-singularity-jupyter-kernel.sh](https://docs.jupyter-jsc.fz-juelich.de/github/kreuzert/jupyter-jsc-notebooks/blob/documentation/03-HowTos/details/install-singularity-jupyter-kernel.sh)"
"Link to [install-singularity-jupyter-kernel.sh](https://gitlab.jsc.fz-juelich.de/jupyter4jsc/j4j_notebooks/-/raw/master/03-HowTos/details/install-singularity-jupyter-kernel.sh)"
<h1style="text-align: center">Install containerized Jupyter kernel at Jupyter-JSC</h1>
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This Jupyter notebook will walk you through the installation of a containerized Jupyter kernel (for use at Jupyter-JSC, but it should actually work with any Jupyter server on a system where Singularity is installed). Considerable performance improvements (especially with respect to kernel start-up times) over e.g. conda-based Jupyter kernels on distributed filesystems, as are typically installed on HPC systems, might be experienced. In the example below, the `base-notebook` from the [Jupyter docker stacks](https://jupyter-docker-stacks.readthedocs.io/en/latest/) is used as an IPython kernel (already having the required `ipykernel` package installed), the approach presented here might be extended to any other [Jupyter kernel compatible programming language](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels), though.
Requirements:
* Python environment with an installed `ipykernel` package in a Docker (or Singularity) container
*`container` group access for the JSC systems as described [here](https://apps.fz-juelich.de/jsc/hps/juwels/container-runtime.html#getting-access) in the docs
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Check that the Singularity container runtime is available via the JupyterLab environment,
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``` bash
singularity --version
```
%% Output
singularity version 3.6.4-1.el8
%% Cell type:markdown id: tags:
Specify the filesystem location that stores the Singularity container image,
Optional, if you already have a Singularity container image available at the above location: Convert a containerized Python environment (e.g. the Jupyter `base-notebook` that is [available via Dockerhub](https://hub.docker.com/r/jupyter/base-notebook)) into a Singularity container image to be used as an example here,
%% Cell type:code id: tags:
``` bash
mkdir-p${IMAGE_TARGET_DIR}
```
%% Cell type:markdown id: tags:
Note that pulling and converting the Dockerhub image will take a bit of time,
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INFO: Creating SIF file...
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Check that the Singularity image is available,
%% Cell type:code id: tags:
``` bash
ls-lah${IMAGE_TARGET_DIR}
```
%% Output
total 177M
drwxr-sr-x 2 hoeflich1 cesmtst 4.0K Jan 19 11:59 .
drwxr-sr-x 5 hoeflich1 cesmtst 4.0K Jan 19 11:59 ..
-rwxr-xr-x 1 hoeflich1 cesmtst 183M Jan 19 11:59 jupyter-base-notebook.sif
%% Cell type:markdown id: tags:
Now, setup a Jupyter kernel specification with the `install-jupyter-kernel.sh` script from this repository (which basically writes a `kernel.json` file to the home directory location that Jupyter expects for user-specific kernels),
%% Cell type:code id: tags:
``` bash
KERNEL_DISPLAY_NAME=Singularity-Python # don't use whitespaces here!
Link to [install-singularity-jupyter-kernel.sh](https://docs.jupyter-jsc.fz-juelich.de/github/kreuzert/jupyter-jsc-notebooks/blob/documentation/03-HowTos/details/install-singularity-jupyter-kernel.sh)
Link to [install-singularity-jupyter-kernel.sh](https://gitlab.jsc.fz-juelich.de/jupyter4jsc/j4j_notebooks/-/raw/master/03-HowTos/details/install-singularity-jupyter-kernel.sh)
If so, you should be able to choose and connect to the containerized Python kernel from the drop down menu and/or the kernel launcher tab (a reload of the JupyterLab web page might be necessary).
