Connecting to JupyterLab
Prerequisites Must be Fulfilled
Connect to VPN
You MUST be connected to the Stanford VPN to connect to JupyterLab; information about setting up the VPN is available at Stanford VPN
Navigate to JupyterLab via Web Browser
Overview of Jupyter Concepts
What is Jupyter? In a nutshell: it’s a tool for collaborating. It’s built for writing and sharing code and text, within the context of a web page.
JupyterLab is the next UI generation for Project Jupyter, a interactive development environment for working with language specific notebooks, code and data.
Within JupyterLab you can create a Jupyter Notebooks, which provides an environment, where you can document your code, run it, look at the outcome, visualize data and see the results without leaving the environment. Each notebook is associated with a programming language(referred to as kernel), like Python or R.
The JupyterLab UI also provides additional components: file browser, text editor and terminal.
From the Launcher Tab, click on the desired language you would like to use.
- This will create a Untitled.ipynb file. Each .ipynnb file is a text file that describes the contents of your notebook in a format called JSON.
- This notebook has an associated kernel (programming language), these kernels provide the desired language support and executes the code contained in the notebook.
- Cells within a notebook are the containers for text to be displayed or code to be executed by the notebook’s kernel.
Check out the JupyterLab Documentation for a full breakdown of the JupyterLab Notebook Interface - Interface
We currently offer several popular kernels including Python, R, Stata, and SAS. These can be accessed via JupyterLab Landing Launcher Tab.
RStudio is also accessible but for now needs to be accessed via classic notebook.
noVNC desktop-like GUI environment is also available. This can be accessed within your classic notebook. From within your Nero Jupyter interface click Help, Launch Classic Notebook, New (on the right next to the upload button), noVNC Desktop. You must use Chrome for noVNC or it will not work.
Each notebook relates to a specific language(kernel), the same way you’d create Python script or SAS script, etc.
Screenshot Jupyter Lab Launcher Tab
Install R Packages in Jupyter
Check out the Installing R Packages in Jupyter documentation to view these instructions.
Using Custom Anaconda Environments in Jupyter
You can also use Jupyter with your own custom created conda environments. There are a few other packages you need to install and a special file to create. Once done, going to nero.compute.stanford.edu will load your custom conda environment.
Check out the Custom Anaconda Environment in Jupyter documentation to view the details.
Running Jupyter on Slurm GPU Nodes
If you require the use of GPUs for your Jupyter Notebooks, our documentation of Running Jupyter on Slurm walks you through the process of launching a Jupyter Lab server on a Slurm GPU node, and connecting to it.