What becomes possible once you have the machinery set up, and why geographers need code rather than just GUI tools. No setup required.
Scientific Computing Foundations
Set up Python, manage your environment, and learn the tools every computational geographer needs.
Setup Guide
Scientific Computing Foundations
Before you can run a flood model or classify a satellite image, you need a machine that knows how to compute. This section builds that foundation β Python installed, environments isolated, packages managed, notebooks running, and your work tracked with Git.
You don't need any prior coding experience. By the end you'll have a professional-grade scientific computing setup ready for any pathway.
10 chapters
~5 hours total
Windows Β· Mac Β· Linux
No experience needed
Setup Route
From Zero To A Working Scientific Python Environment In Ten Steps
The setup path works best when each layer is confirmed before building the next one. Start with motivation and a first taste of code, move through installation and isolation, then add the workflow tools β notebooks, debugging, IDEs, and version control.
First
Motivation and First Code
Understand why computation matters, then write and run Python immediately β no installation needed.
β
Then
Shell, Python, and Environments
Learn the command line, install Python on your machine, and isolate each project in its own sandbox.
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Then
Packages and Notebooks
Populate your environment with scientific libraries and learn the interactive workflow that powers exploration.
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Finally
Professional Tools
Learn to read errors, move from notebooks to scripts in a proper IDE, and track your work with Git.
Chapter Map
Write and run Python in your browser right now β no installation. Print text, do math, write a conditional. Code is just instructions you write.
Navigate your computer without a mouse. Learn
pwd, ls, cd, and mkdir β the four commands Python needs you to know first.Anaconda vs standard Python β which path fits your work. Step-by-step instructions for Windows, Mac, and Linux. Verify it works before moving on.
Why global installations cause dependency conflicts. Create, activate, and deactivate isolated sandboxes using
venv or conda.Expand Python with
pip and conda. Install NumPy, SciPy, and geographic libraries. Freeze your setup into requirements.txt for reproducibility.Install and launch Jupyter, write code and markdown cells, run them in sequence. The interactive environment you'll use throughout all three pathways.
The three ways Python runs: shell, notebook, and script. How to read a traceback from the bottom up and fix the five most common error types.
When to graduate from notebooks to scripts. VSCode vs PyCharm β what each is for and how to point it at your virtual environment.
Track every change to your code. Clone, status, add, commit, push β the five-step lifecycle that replaces
model_final_v3_USE_THIS_ONE.py.