Link Conda to Jupyter

This guide explains how to link your Conda environment — whether it’s Python or R — to JupyterLab on Rockfish.

Connect to Rockfish

Open a terminal and connect:

ssh YourUserID@login.rockfish.jhu.edu

Start an Interactive Session (Compute Node)

interact -p shared -n 4 -t 02:00:00

Load Anaconda and Activate Your Environment

module load anaconda3/2024.02-1
conda activate my_env

Replace my_env with the name of your Conda environment.

Install and Register the Jupyter Kernel

For Python

# Install ipykernel (if not installed)
pip install ipykernel

# Register kernel
ipython kernel install --user --name=my_env --display-name "Python - my_env"

For R

Inside the R prompt:

# Install the IRkernel package (if not installed)
install.packages("IRkernel")

# Register the kernel
IRkernel::installspec(name = "my_env", displayname = "R - my_env")

# Exit R
q()

Note

💡 Explanation: - --name / name: Internal identifier used by Jupyter (no spaces or dots). - --display-name / displayname: Friendly name that appears in the JupyterLab interface.

Confirm Kernel Registration

jupyter kernelspec list

You should see your environment listed (e.g., my_env).

Deactivate the Environment

conda deactivate

Exit the Compute Node

exit

You’re All Set!

The next time you launch JupyterLab on Rockfish, your kernel(s) will be available as options:

➡️ Python - my_env
➡️ R - my_env

Just select the one you need and start coding!