JupyterLab — The Complete Guide: Transparent Engineering Calculation Notebooks for Free
JupyterLab is a free, open-source workspace for writing notebooks: cells of code with the results, tables and plots right below them, alongside explanatory text and equations. It runs locally in the browser, with no external server, and works with Python, Julia, R and other languages.
JupyterLab
Project Jupyter
Interactive computing notebooks — code, results, plots and explanations in one shareable document.
Get it from the vendorWhy it suits engineering calculations
An Excel sheet hides its formulas in cells and is hard to check. In a notebook every step is visible: the data, the assumptions, the formula and the result, with explanations in between. Change an input, re-run, and everything updates. That turns the notebook into calculation documentation another engineer can check and reproduce.
Common uses
- Processing lab test results and field measurements, including plots for the report.
- Repeated design calculations — a beam, a pipe, a heat exchanger — with parameters that change from project to project.
- Driving engineering programs from Python, such as OpenSees or Gmsh, and collecting the results.
- Interactive teaching material for courses.
Getting started
The simple route: install Python, then pip install jupyterlab, or download the JupyterLab Desktop app, which comes with everything. Add NumPy, SciPy, pandas and matplotlib and open a new notebook. It is worth adding the pint library for units, so the calculation checks for you that the dimensions work out.
What to watch for
A notebook whose cells were run out of order can show results that do not match the code. Before handing anything in, run “Restart and Run All”. To export a tidy report to PDF or Word, use Quarto, which reads notebooks directly.
Python
Python Software Foundation
The language behind most modern engineering computation, and its full ecosystem.
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Quarto
Posit
Technical reports from code and data — Python, R or Julia into Word, PDF, HTML and slides.
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Julia
JuliaLang
A programming language for fast scientific computing — as easy to write as Python, close to C in speed.
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Spyder
Spyder project
A MATLAB-style scientific Python environment — editor, variable explorer, console and plots in one window.
Get it from the vendorThe bottom line
JupyterLab is probably the best tool for engineering calculations that need to be documented and checked. If you prefer a MATLAB-style environment with a variable explorer, you will find it in Spyder — and the two can work on the same files.