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title Setup

Overview

This lesson is designed to be run on a personal computer. All of the software and data used in this lesson are freely available online, and instructions on how to obtain them are provided below.

Install Python

In this lesson, we will be using Python 3 with some of its most popular scientific libraries. We'll use uv, a modern Python package manager that makes installation simple and reliable.

Step 1: Install uv

First, install uv using one of these methods:

Windows (PowerShell):

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

or

winget install -e --id astral-sh.uv

macOS/Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

or

brew install uv

Step 2: Install Python

uv makes Python installation simple - it will automatically install Python when needed:

uv python install

This installs the latest stable Python version. You can also specify a version:

uv python install 3.12

Step 3: Install Required Libraries

Create a new project for this workshop:

uv init swc-python
cd swc-python

Add the scientific libraries we'll need:

uv add numpy matplotlib

This automatically creates a virtual environment and installs the packages.

Obtain lesson materials

  1. Download python-programming-foundations-data.zip and python-programming-foundations-code.zip.
  2. Move downloaded files to your swc-python project directory.
  3. Unzip the files.

You should see two folders called data and code in the swc-python directory.

Launch Python interface

To start working with Python, we'll use uv to run Python in your project environment. This ensures you have access to all the libraries we installed. Below are several options for working with Python:

Recommended: Using uv run

The simplest approach is to use uv run with your preferred Python interface. This automatically uses your project's virtual environment.

Option A: Jupyter Notebook

A Jupyter Notebook provides a browser-based interface for working with Python.

First, add Jupyter to your project:

uv add jupyter

Then launch a notebook using uv:

  1. Navigate to your project directory:
cd swc-python
  1. Navigate to the data directory:
cd data
  1. Start Jupyter using uv:
uv run jupyter notebook
  1. In the browser window that opens, click "New" and select "Python 3" to create a new notebook.

Option B: IPython interpreter

IPython is an alternative solution situated somewhere in between the plain-vanilla Python interpreter and Jupyter Notebook. First add IPython to your project:

uv add ipython

To start using IPython with uv:

uv run ipython

Option C: Plain Python interpreter

To launch a plain Python interpreter using uv:

uv run python

This ensures you're using the Python version and packages from your project environment.

Why use uv?

uv is a modern Python package manager that provides several benefits for beginners:

  • Automatic environment management: Creates isolated environments for each project
  • Fast and reliable: Downloads and installs packages quickly
  • Simple commands: uv add package_name instead of complex pip commands
  • No conflicts: Each project has its own dependencies
  • Automatic Python installation: No need to manually install Python first