Jupyter Notebook is a web application for creating and sharing computational documents. This application can be used to create and share documents that contain live code, equations, visualizations, and text.
Accessing Jupyter Notebook and JupyterLab
To access Jupyter Notebook and JupyterLab, visit jupyter.davidson.edu. Chrome and Firefox are suggested browsers.
Log in using your full Davidson email credentials (firstname.lastname@example.org), and password. If you are able to log into a lab computer, you also have access to Juypter.
After your credentials are verified, an instance will be created, and a blue progress bar will be displayed as your server starts up.
The Jupyter Default Interface
The menu bar at the top of JupyterLab has menus that expose actions available in JupyterLab along with their keyboard shortcuts. The default menus are:
- File: actions related to files and directories
- Edit: actions related to editing documents and other activities
- View: actions that alter the appearance of JupyterLab
- Run: actions for running code in different activities such as notebooks and code consoles
- Git: source code version control related actions
- Tabs: a list of the open documents and activities in the dock panel
- Settings: common settings and an advanced settings editor
- Help: a list of JupyterLab and kernel help links
On the top right corner is an indicator of the CPU and the memory usage (in 5-second updates):
The CPU monitor will show CPU usage blue>yellow>red, where red represents approaching the usage threshold. If you exceed the memory threshold, the notebook will shut down.
Additionally, a memory monitor is located at the bottom of the screen with a numerical depiction of memory usage.
On the left-hand side of the screen is a sidebar that provides more information:
- File Browser: The file browser and File menu enable you to work with files and directories on your system. To download from within the file manager, right-click Download as an Archive (.zip, extraction software default on lab machines).
- Running Terminals and Kernels: A list of tabs in the main work and of running kernels and terminals.
- GIT: An interface for making and staging commits while working in a version-controlled directory.
- Table of Contents: An overview (and structure) of the currently active document.
- Extension Manager: Management of third-party extensions.
- Installed: shows currently installed extensions
- Discover: searches among available extensions for installation
Installation of Packages and Kernels
How to install python packages
- Go to terminal, pip3 install –user “name of package”
- Restart kernel
- Any modifications– restart kernel to reload environment
How to add a custom python kernel
- Create a virtual environment with required packages and software (provided methods: venv, mamba, conda, virtualenv).
- Once your virtual environment is activated, install the `ipykernel` package.
- If using virtualenv, venv: pip3 install ipykernel
- If using mamba, conda: conda install ipykernel
- With the virtual environment activated make the new python kernel available to JupyterLab by running the following command:
python -m ipykernel install –user –name “[env-name-here]” –display-name “Python [env-name-here]”substituting “[env-name-here]” with the name of your environment or project.
- Stop Server. If something is crashing or a bug is encountered— from the control panel, select stop server
- My Queue
- Lists running instances and uses batch scheduling (SLURM)
For Support Issues
For any student support needs please email email@example.com.
For most Juypter support needs, please email firstname.lastname@example.org.
For issues that may share personal student information, please contact Michael Blackmon directly.