🧪 Fixing Jupyter Kernels in Conda Environments with Python and R

emmy neutron — Sat, 03 May 2025 21:02:04 +0000

🧩 Introduction

When working with Jupyter notebooks in a cluster environment, managing Conda environments and registering Python and R kernels can be tricky. Here's a practical guide based on my experience solving kernel conflicts and making both Python and R work seamlessly.

🛠️ Environment Setup

Create a Conda Environment

conda create -n conda_env python=3.11 r-base=4.4 -y
conda activate conda_env

Install Python Kernel

python -m ipykernel install --user --name conda_env --display-name "Python_conda_env"

Check if the kernel is registered:

jupyter kernelspec list

📦 Install Required Packages

Make sure the required Jupyter components are installed:

jupyter --version

If any key packages (like notebook, jupyterlab, etc.) are missing, install them:

conda install notebook jupyterlab ipykernel jupyter_client jupyter_core

🧪 Install and Register R Kernel

Check if R is installed:

conda list r-base

If installed, run:

R -e "IRkernel::installspec(user = TRUE, name = 'conda_env_r', displayname = 'R_conda_env')"

🔍 Verify Kernels were added

You should now see both Python and R kernels registered under ~/.local/share/jupyter/kernels/.

# List all registered Jupyter kernels
jupyter kernelspec list

Each registered Jupyter kernel has a kernel.json file that defines how Jupyter launches it. To inspect and verify it:

# Check the kernel.json file to make sure it's pointing to the correct Python or R executable path
cat ~/.local/share/jupyter/kernels/conda_env/kernel.json

You should see something like:

{
  "argv": [
    "/home/yourusername/.conda/envs/conda_env/bin/python",
    "-m",
    "ipykernel_launcher",
    "-f",
    "{connection_file}"
  ],
  "display_name": "Python_conda_env",
  "language": "python"
}

🧹 Kernel Conflicts and Fixes

Remove Conflicting Kernels

If a kernel is broken or duplicated, unregister it:

jupyter kernelspec list
jupyter kernelspec uninstall conda_env_broken
# or
jupyter kernelspec remove conda_env_broken

Fix R Library Path Issues

Sometimes R in conda conflicts with cluster R. Make sure your environment points to the right libraries:

export LD_LIBRARY_PATH=$HOME/.conda/envs/conda_env/lib:$LD_LIBRARY_PATH

✅ Final Check

To confirm that both kernels are ready:

jupyter kernelspec list

✅ Summary

# Add Python Kernel
conda activate conda_env
python -m ipykernel install --user --name conda_env --display-name "Python_conda_env"
cat ~/.local/share/jupyter/kernels/conda_env/kernel.json

# Check if R is installed
conda list r-base

# Register R Kernel
R -e "IRkernel::installspec(user = TRUE, name = 'conda_env_r', displayname = 'R_conda_env')"

✅ Summary of Actions

Installed Jupyter and required kernels
Registered Python and R kernels
Resolved R conflicts using LD_LIBRARY_PATH
Cleaned up unwanted or broken kernels
Verified kernel registration with jupyter kernelspec list

✍️ Written by: Eman

DEV Community: emmy neutron