Hi Reader,

Last week, I shared my 25 most useful keyboard shortcuts for Jupyter Notebook. If you want to reference it later, here's the blog post:

🔗 Fly through Jupyter with keyboard shortcuts

Let’s move on to this week’s tip!

👉 Tip #4: How to start coding in under 10 seconds

Has this ever happened to you?

You get an idea for some code you want to try out, and you sit down at a computer, but it’s not your usual machine. You don’t want to set up your development environment right now, but you also don’t want to abandon your idea.

What do you do?

I’ve got two ideas for you, and both will get you coding in your web browser in under 10 seconds, including access to common data science libraries like scikit-learn and pandas! 🐼

Option 1: JupyterLite

Go to try.jupyter.org and click on JupyterLab or Jupyter Notebook. In just a few seconds, you’ll be ready to code!

This interface is powered by JupyterLite, which is a JupyterLab distribution that runs entirely in the browser. (Technically, the Notebook option is actually “RetroLab”, a project that duplicates the Notebook experience using JupyterLab components.)

Unfortunately, this service sometimes times out when there are lots of users. In that case, I recommend that you google for “jupyterlite”, click the first link (which is the JupyterLite documentation), and then click “Lab” or “Retro” at the top of the page.

Option 2: Colab Scratchpad

Go to https://colab.research.google.com/notebooks/empty.ipynb, or google for “colab scratchpad” and click the first link. You’ll be taken to a Colab Notebook, which is very similar to the Jupyter Notebook.

Scratchpad is better than the Colab start page because you’re taken directly to a notebook, plus it doesn't create an “Untitled” notebook in your Google Drive. (However, you still have to be logged into a Google account in order to use Scratchpad.)

Unlike JupyterLite, Colab rarely seems to time out since it’s run on Google's servers, and code consistently runs quickly!

How helpful was today’s tip?


See you next Tuesday!

- Kevin

P.S. A tale of data science romance 😍

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