JupyterHub Tools

Integrated Tools in Jupyter Hub

JupyterHub is a web-based Integrated Development Environment (IDE) that provides a unified workspace where you can manage every stage of your workflow—from editing scripts and running analyses to visualizing results—all from a single, browser-accessible dashboard, as shown in the figures below.

Each user session comes equipped with Notebooks, Consoles, Terminal Access, and text-file editors. Jupyter Hub supports Python like Julia, MATLAB, and R — useful for researchers integrating multi-language workflows.

You can click the “Open in DesignSafe” button to start a JupyterHub session – you will be asked to log in:

The tools can be accessed from the JupyterHub Launcher, shown in the figure below: You can access the launcher by pressing the blue “+” on the top left of the Jupyter dashboard. You can launch any item by double-clicking on it.

As shown in the figures at the bottom of this page: You can have multiple items open symultaneously. You can arrange them as windows or as tabs.

Terminal

• A full Linux command-line interface (CLI) that allows users to run OpenSees (Tcl or Python) scripts directly, compile code, use Git, or execute batch-style workflows.

• Provides real-time error messages, standard input/output handling, and access to the full Python and Unix toolchain.

• Especially useful for:

• Running OpenSees, OpenSeesMP, OpenSeesSP, or OpenSeesPy jobs at the command line

• File manipulation and quick testing

• Using tools like grep, awk, sed, and tar for advanced scripting

Console

• A standalone REPL (Read-Eval-Print Loop) environment for Python.

• Allows you to test snippets of OpenSeesPy code without launching a full notebook.

• Can also be used to execute full .py scripts.

• Jupyter Hub supports Python like Julia, MATLAB, and R

Notebook Interface (Jupyter Notebooks)

• Combines executable code, documentation, and visualizations in a single document.

• Ideal for OpenSeesPy workflows, where users can iteratively run cells, plot results, and write notes alongside their code.

• Great for pre- and post-processing, exploring parameter sweeps, and documenting research workflows.

• Jupyter Hub supports Python like Julia, MATLAB, and R

File Manager

• Visual interface for navigating, organizing, renaming, and deleting files in your Jupyter workspace.

• Drag-and-drop support for uploading or downloading files.

• Makes it easy to keep your project folder tidy and to stage input/output files for HPC runs.

Text Editor (Code Editor)

• Built-in lightweight code editor with syntax highlighting for Tcl, Python, JSON, and other formats.

• Allows quick edits to scripts without switching to a notebook or terminal editor like vim.

• Useful for:

• Editing input scripts

• Creating SLURM job files

• Modifying metadata.json or app.json files when working with Tapis

The following screenshot is an “extreme” example of how you can use all of these tools symultaneously:

Summary

The Jupyter Hub environment is your workbench for development, debugging, testing, and launching HPC jobs — all without leaving your browser.