Custom Conda Environments in JupyterLab¶
If you are used to working with Ipython notebooks and are now migrating your workflow from a local machine to the CoSTAR cluster, using JupyterLab is a great way to get comfortable.
This guide demonstrates how to install your own version of Miniconda, create a custom Python environment, and make that environment available as a “Kernel” inside the cluster’s Open OnDemand JupyterLab portal.
1. Connect and install Miniconda¶
First, SSH into the CoSTAR login node:
ssh ab1234@costar-login01
Next, download and run the Miniconda installer in your home directory. Follow the on-screen prompts (pressing Enter to scroll through the license, typing yes to accept, and yes to initialize Conda).
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
Once installed, log out and log back in to ensure Conda is activated in your terminal. You should see (base) next to your command prompt.
Troubleshooting: No (base) prompt?
If you log back in and do not see the (base) prompt, your cluster profile might not be set up to read your .bashrc file automatically. Run the following command once to fix this:
echo -e "\nif [ -f ~/.bashrc ]; then\n source ~/.bashrc\nfi\n" >> ~/.bash_profile
Then, simply run source ~/.bashrc to activate Conda for your current session.
2. Create your custom environment¶
Now, create a new environment. For this example, we will call it myenv and install Python, numpy, and a crucial package called ipykernel.
conda create -n myenv python=3.13 numpy ipykernel -c conda-forge
conda activate myenv
3. Link the environment to Jupyter¶
With your environment activated, run the following command to register it with Jupyter. This creates a tiny file in your home directory that Open OnDemand reads when it starts up.
python -m ipykernel install --user --name=myenv --display-name="Python (myenv)"
4. Launch JupyterLab via Open OnDemand¶
You are now ready to use the web portal!
Open your web browser and navigate to the CoSTAR Open OnDemand portal.
Go to all available apps Apps > JupyterLab.
Request your resources (e.g. 2 CPU cores, 4 hours, 8GB of Memory, etc) and click Launch.
Once your session starts, click Connect to Jupyter.
When the JupyterLab interface loads, open a new Notebook. In the top right corner (or in the Launcher menu), you will now see Python (myenv) available as a kernel option. Select it, and you are ready to code using the cluster’s compute power!
For an introduction to JupyterLab please visit Jupyter Lab Introduction.