Introduction

Welcome to Installing Python Locally with uv, a short session on setting up a reproducible Python environment for research and teaching.

Almost every computational research project eventually runs into the same problem: code that worked perfectly on one machine fails, produces different numbers, or simply refuses to run on another. Usually the code has not changed — the environment it depends on has.

This short session will explore how to set up a reproducible Python environment for research and teaching. By the end of it you will have installed a modern Python package and project manager, uv, used it to install an isolated Python interpreter, and built a small project whose computational environment can be reconstructed exactly — by you, by a collaborator, or by a peer reviewer — at any point in the future.

Intended learning outcomes

By the end of this session, you will be able to:

  • explain why recording software versions matters for reproducible research;
  • install uv and use it to install a specific version of Python;
  • create a small Python project and identify the files uv uses to describe it;
  • add and remove Python packages from a project;
  • run Python or JupyterLab inside the correct project environment.

Software and access required

You will need:

  • a laptop on which you have permission to install software (if you are on a managed university or company machine and are unsure, ask your local IT support);
  • a terminal application (PowerShell or Command Prompt on Windows; Terminal on macOS; any terminal emulator on Linux);
  • an internet connection, to download the uv installer, a Python interpreter, and a small number of packages.

No prior installation of Python is required — part of the point of this session is that uv can provide one for you, without relying on whatever may or may not already be on your computer.

About this course

These course materials have been designed and developed by Pau Erola, PhD (Jean Golding Institute, University of Bristol).

We used the enhancement of AI in alignment with our institutional guidance:

  • Claude (Sonnet 5) – Writing assistance, expansion of content, and generation of code examples

For queries related to this course please contact .