2  Running Python

One of the defining characteristics of Python is that it is an interpreted language. If you’ve used a language like Java or C you’re used to having to compile your code. Python is instead typically translated to an intermediate representation (bytecode) and immediately executed without a separate compilation step.

To do this, we need a Python interpreter, a program called python (sometimes python3).

There are a lot of ways to install Python, but for this class we’ll use a tool called uv to manage Python and various dependencies.

Installing uv

  1. Go to this page, and follow the instructions for your environment: installing uv.
  2. Once uv is installed, type uv python install 3.13 in your terminal.
  3. After Python is installed, verify the version with uv run python -V. You should see a version that starts with 3.13.

The Python REPL

One of the benefits of an interpreted language is that it is possible to run it one line at a time, in an interactive session.

uv run python

This feature of most interpreted languages is called a REPL (pronounced rep-el).

REPL stands for:

  • Read - takes user input, typically one line at a time
  • Evaluate - evaluate user input, running the code in the current context
  • Print - print the output of the evaluation automatically (without the need for a print())
  • Loop - repeat, until the user quits

This is incredibly useful, many Python programmers keep a REPL open at all times, to try out ideas / test things / look up documentation.

Exercise: python-demos directory

Let’s set up a small local Python project using uv so that we can try a different REPL and run some code together.

  1. Open a terminal and navigate (using cd) to a location where you’d like to create our demo repository.
  2. Make a new directory (mkdir python-demos) and then enter it (cd python-demos).
  3. Initialize the directory as a uv project with uv init.

This will create a pyproject.toml and some other files that aren’t needed for our purposes.

pyproject.toml exists at the root of a Python project and configures what other packages are needed.

  1. Let’s install a package with uv, run uv add ipython

This will update your pyproject.toml and uv.lock files and install the package for use from within this directory.

  1. To use this new package you can type uv run ipython from within the python-demos directory, and you will see ipython.

We’ll talk more about package management and what this tool is doing later in the course.

ipython vs python

ipython is an enhanced REPL for Python. It is using the same version of Python you already installed, but providing a different interface.

It provides command history, syntax highlighting, and a handful of other useful features that make it many people’s preferred REPL. It is up to you which you prefer, both provide access to the same core language.

You will often see interactive Python prompts shown as:

>>> x = 4 * 3
>>> print(x)
12

The lines that begin with >>> are the Python prompt, and lines without >>> indicating output.

In ipython input/output lines are marked with In[0] and Out[0] prefixes, but when showing interactive output I will stick to convention and use >>>.

Tip: Don’t use pip (or conda)

You will see instructions using tools other than uv, but it is best to stick to a single tool.

When you are looking at Python libraries, which we’ll discuss later, you will often see instructions which state you should run pip install foo.

When you see pip install foo you should use uv add foo instead.

conda install instructions can usually be translated to uv add as well.

These tools are older than uv and can easily leave your system in a broken state, where uv restricts installs to the directory you are working in.