Why this section matters¶
Technical setup is part of reproducible spatial data science. A stable Python environment, a clear project folder, and basic Git habits make it easier to develop, test, explain and share your SDS320 project.
Spatial Data Science projects often combine several software ecosystems: Python packages, geospatial libraries, machine learning libraries, notebooks, scripts and version-controlled repositories. Small mismatches between environments, packages or file paths can lead to confusing errors later.
This section helps you prepare a working setup for the course lessons. It also gives you a short reactivation of Python and project organisation concepts from SDS210.
What this section covers¶
Use these pages as a practical setup path:
Software setup — install and check the main tools for SDS320, including Python, VS Code, Git and the course environment.
Python reactivation — refresh Python basics that you will need for project work.
Notebooks and scripts — decide when to use notebooks, when to use scripts and how to combine them.
Git basics — use Git to track your project and prepare a public repository.
Troubleshooting — diagnose common problems with environments, packages, paths, notebooks, spatial data and Git.
The pages are connected, but you do not need to master everything at once. Start with the software setup, then return to the other pages when they become relevant for your project.
What you should have ready¶
After completing this section, you should have:
a working Python environment for SDS320,
access to VS Code, Colab, or a comparable Python development environment,
Git installed and available from the terminal,
a basic project folder structure,
a first idea of how notebooks and scripts can work together,
a way to check whether key packages are installed,
a strategy for asking useful technical questions when something breaks.
How to use this section¶
Return to this section whenever your setup changes, your code behaves differently on another machine, your notebook kernel is wrong, or your repository becomes difficult to understand.
You should also return here before final submission. A project that works only on your own computer, only in one notebook state, or only with undocumented manual steps is difficult to reproduce. The setup section helps you avoid these problems early.
Key message¶
Setup is not a one-time hurdle at the beginning of the semester. It is an ongoing part of project work. Treat your environment, folder structure, notebooks, scripts and Git history as part of your analytical workflow.