Introduction

Last updated on 2026-07-14 | Edit this page

Estimated time: 20 minutes

Overview

Questions

  • What is Colab?
  • Is it the same or different than a Jupyter notebook?
  • Can it do more than just python?
  • How do I use it to write or execute python code?

Objectives

  • Learn how to open a shared Colab notebook, edit it, and save it.
  • Learn how to execute python from within Colab.

Three things that are easy to confuse

Before we open a single notebook, it helps to untangle three terms that often get used interchangeably but really mean different things: Python, Jupyter notebooks, and Colab. In short, Python is a language, a Jupyter notebook is a place to write and run that language interactively, and Colab is a way to use those notebooks in the cloud without installing anything. If you keep that hierarchy in mind — language, then notebook, then cloud host — everything else in this workshop will fit into place.

Python: the language

Python is a programming language — the actual instructions you write to tell a computer what to do. It was created by Guido van Rossum and first released in 1991, and, contrary to popular belief, it is named after the British comedy troupe Monty Python’s Flying Circus, not the snake. Python was designed to be readable and approachable, which is a big part of why it has become one of the most widely used languages in science, data analysis, and education. The current version is Python 3.14 (released in late 2025), and you can read more about its history and design on the official Python website and its Wikipedia entry.

On its own, Python is just the language. To use it, you need some environment that can read your code and run it — and that is where notebooks come in.

Jupyter notebooks: the interactive environment

A Jupyter notebook is a document that lets you write and run code in small, editable chunks called cells, and it stitches together live code, the output that code produces (numbers, tables, plots), and formatted explanatory text all in one place. That mix of “code plus narrative” is what makes notebooks so popular for teaching and for exploratory science. The notebook file itself has the extension .ipynb, and you open and run it inside an application — either the classic Jupyter Notebook interface or the more modern, IDE-like JupyterLab.

Callout

IDE stands for Interactive Development Environment, and refers to a program that enables you to both edit and execute computer code.

Notebooks have a lovely origin story for a physics audience. The project began as IPython, built in 2001 by Fernando Pérez while he was a particle-physics graduate student looking for a better way to poke at his simulation data. The browser-based IPython Notebook arrived in 2011, and in 2014 it was rebranded as part of the broader Project Jupyter. The name “Jupyter” is a nod to three core languages — Julia, Python, and R — and an homage to Galileo’s own notebooks documenting the moons of Jupiter. That history hints at an important point: notebooks are not limited to Python. Jupyter runs code through interchangeable kernels, so the same notebook interface can execute R, Julia, and dozens of other languages, as well as ordinary shell commands.

Colab: Jupyter in the cloud

Google Colaboratory — “Colab” for short — is a free, cloud-based service from Google Research (first released in 2017) that lets you run Jupyter-style notebooks entirely in your web browser, with nothing to install. The notebooks run on Google’s computers rather than yours, save to your Google Drive like any other Google document, and can be shared and edited collaboratively the way a Google Doc can. Colab also gives you free (if limited) access to more powerful hardware such as GPUs. You can explore it at colab.research.google.com and read the details in the Colab FAQ.

So, to answer two of our opening questions directly: Colab is essentially Jupyter hosted in the cloud. If you already know Jupyter, you know Colab — a handful of menu items and keyboard shortcuts differ, but the cell-based, code-plus-text experience is the same. And because it is built on the same kernel system as Jupyter, it can run more than just Python. The tidy summary to carry with you: Python is the language, Jupyter is the notebook environment that runs it, and Colab is Google’s cloud version of that environment.

Saving your own copy so your edits stick

There is one habit worth building early. When you open a notebook we have shared with you, your changes are not automatically saved back to a copy you own — and anything you type can be lost when the session ends. To keep your work, make your own copy in your Google Drive as soon as you open a shared notebook.

Callout

Save a copy to your Drive first

In the Colab menu, choose File → Save a copy in Drive. This creates a personal copy in your own Google Drive that you can edit freely, and your changes will persist across sessions. You will need to be signed in to a Google account to do this.

Optional!

Running the notebooks locally instead

You are not required to stay in the cloud. If you would rather run these notebooks on your own machine — for offline work, for privacy, or simply to keep them after the workshop — you can download any Colab notebook and open it in Jupyter locally.

  1. In Colab, choose File → Download → Download .ipynb to save the notebook file to your computer.
  2. Install Python together with Jupyter. The simplest route for newcomers is the Anaconda distribution, which bundles Python, JupyterLab, and most of the scientific libraries you’ll need. Alternatively, install Python and then run pip install jupyterlab (see the Jupyter installation guide).
  3. Launch JupyterLab and open your downloaded .ipynb file.

Keep in mind that a few Colab conveniences do not carry over: mounting Google Drive, the free GPUs, and Colab’s pre-installed packages are cloud features, so when running locally you may need to install some libraries yourself with pip or conda.

What’s next

With those distinctions in hand, you’re ready for the hands-on part. The shared Colab notebooks will walk you step by step through opening, editing, and executing cells — so you can start writing and running Python right away.

Key Points
  • Python is a programming language; a Jupyter notebook is an interactive environment that runs code in cells alongside text and output; Colab is Google’s free, cloud-hosted version of that notebook environment.
  • Colab is essentially Jupyter in the cloud — if you know one, you can use the other.
  • Notebooks are not Python-only; they can run other languages (and shell commands) through different kernels.
  • Opening a shared notebook does not save your edits. Use File → Save a copy in Drive to keep a persistent, editable copy.
  • You can download any notebook (File → Download → Download .ipynb) and run it locally with Jupyter, e.g. via Anaconda.