To use a Python kernel from a Conda environment, install the ipykernel package in the Conda environment and then create a kernel. Condaįirst, set up your shell for Conda and create your environment-see the Using Conda user guide for instructions. After loading, start or restart the R kernel. Alternatively, when JupyterLab is launched, navigate to the Lmod tab (labeled "Softwares") on the left side, search for the modules via keyword, and then load them. To use R packages that need certain libraries (via modules), add the modules to the "Modules to load" option (e.g., gcc/11.3.0 gsl/2.7.1) on the JupyterLab app form page. The kernel will be able to access your user-installed R packages. Then within an R session, install the IRkernel package and create a kernel with a command like the following: > install.packages("IRkernel") > IRkernel::installspec(name = "r422", displayname = "R 4.2.2") To install an R kernel, first modify PATH to add the JupyterLab install path and load the R module version of your choice: module purge export PATH=/spack/conda/envs/ood-jupyterlab/bin:$PATH module load gcc/11.3.0 openblas/0.3.20 r/4.2.2 After loading, start or restart the Python kernel. To use Python packages that need certain libraries (via modules), add the modules to the "Modules to load" option (e.g., gcc/11.3.0 cuda/11.6.2) on the JupyterLab app form page. The kernels will be able to access your user-installed Python packages. For example, enter a set of commands like the following: module purge module load gcc/8.3.0 python/3.7.6 pip install ipykernel -user python -m ipykernel install -user -name p圓76 -display-name "Python 3.7.6" To use other versions of Python, install the ipykernel package and then create a kernel. This kernel is ready to be used when Jupyter is launched. The default kernel is for Python 3.9.12, based on the modules gcc/11.3.0 python/3.9.12. Many software kernels are available for use with Jupyter. Once installed, when launching Jupyter on OnDemand, the kernels will show up on a Launcher tab (File > New Launcher) and when selecting kernels through other methods. When installing kernels, make sure to use descriptive names in order to distinguish among them. To learn more about installing software on CARC systems using the software module system, see the Software Module System user guide. Install the kernels when logged in to CARC systems before accessing them via the JupyterLab OnDemand interactive app. The following provides installation instructions for a few popular Jupyter kernels, which will be installed in your home directory at ~/.local/share/jupyter/kernels. For more information about OnDemand and using Jupyter notebooks, see the Getting Started with CARC OnDemand user guide.Ī Jupyter kernel is a programming language-specific process that executes the code contained in a Jupyter notebook. This user guide provides instructions for installing Jupyter kernels for use with the JupyterLab interactive app via CARC OnDemand.
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