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emmy neutron
emmy neutron

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🧪 Fixing Jupyter Kernels in Conda Environments with Python and R

#biocluster #kernels #tutorial #jupyter

🧩 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
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Install Python Kernel 

python -m ipykernel install --user --name conda_env --display-name "Python_conda_env"
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Check if the kernel is registered:

jupyter kernelspec list
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📦 Install Required Packages

Make sure the required Jupyter components are installed:

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

conda install notebook jupyterlab ipykernel jupyter_client jupyter_core
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🧪 Install and Register R Kernel

Check if R is installed:

conda list r-base
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If installed, run:

R -e "IRkernel::installspec(user = TRUE, name = 'conda_env_r', displayname = 'R_conda_env')"
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🔍 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
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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
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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" }
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🧹 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
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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
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✅ Final Check

To confirm that both kernels are ready:

jupyter kernelspec list
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✅ 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')"
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✅ 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

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