JupyterLab is the latest package from Project Jupyter. In some ways, it is kind of a replacement for Jupyter Notebook. However the Jupyter Notebook is a separate project from JupyterLab. I like to think of JupyterLab as a kind of web-based Integrated Development Environment that you an use to to work with Jupyter Notebooks as well as using terminals, text editors and code consoles. You might say JupyterLab is a more powerful version of Jupyter Notebook.

Anyway, here are a few of the things that JupyterLab is capable of:

• Code Consoles – These are coding scratchpads that you can use for running code interactively, kind of like Python’s IDLE
• Kernel-backed documents – These allow you to enable code in any text file (Markdown, Python, R, etc) that can then be run in the Jupyter kernel
• Mirrored Notebook cell outputs – This let’s you create simple dashboards
• Multiple views of the same document – Gives you the ability to live edit documents and see the results in real-time

JupyterLab will allow you to view and handle multiple types of data. You can also display rich output from these formats using various visualizations or Markdown.

For navigation, you can use customizable keyboard shortcuts or key maps from vim, emacs and even SublimeText.

You can add new behavior to your JupyterLab instance via extensions. This includes theming support, file editors and more. Continue reading Getting Started with JupyterLab →

What are Jupyter widgets? A widget is an “eventful python object” that in the case of Jupyter Notebook, resides in the browser and is a user interface element, such as a slider or textbox. Jupyter supports a fairly wide array of widgets including the following:

• Numeric
• Boolean
• Selection
• String
• Image
• Button
• Output
• Animation
• Date picker
• Color picker
• Controller (i.e. game controller)
• Layout

We won’t cover every type of widget in this article, but we will get to see a fairly wide range of them in action. For a full list you can check out the documentation. Or you can run the following code in your Notebook: Continue reading Working with Jupyter Notebook Widgets →

The Jupyter Notebook has a feature known as widgets. If you have ever created a desktop user interface, you may already know and understand the concept of widgets. They are basically the controls that make up the user interface. In your Jupyter Notebook you can create sliders, buttons, text boxes and much more.

We will learn the basics of creating widgets in this chapter. If you would like to see some pre-made widgets, you can go to the following URL:

• http://jupyter.org/widgets

These widgets are Notebook extensions that can be installed in the same way that we learned about in my Jupyter extensions article. They are really interesting and well worth your time if you’d like to study how more complex widgets work by looking at their source code. Continue reading Creating Jupyter Notebook Widgets with interact →

Debugging is an important concept. The concept of debugging is trying to figure out what is wrong with your code or just trying to understand the code. There are many times where I will come to unfamiliar code and I will need to step through it in a debugger to grasp how it works. Most Python IDEs have good debuggers built into them. I personally like Wing IDE for instance. Others like PyCharm or PyDev. But what if you want to debug the code in your Jupyter Notebook? How does that work?

In this chapter we will look at a couple of different methods of debugging a Notebook. The first one is by using Python’s own pdb module. Continue reading Jupyter Notebook Debugging →

There are several methods of extending the functionality of Jupyter Notebooks. Here are four of them:

• Kernels
• IPython kernel extensions
• Notebook extensions
• Notebook server extensions

For the purposes of this article, I will be focusing on the third item, Notebook Extensions. However, let’s take a moment and talk about the other three so that you are aware of how they can affect your Notebook. Continue reading Jupyter Notebook Extension Basics →

Jupyter Notebook can be turned into a slide presentation that is kind of like using Microsoft Powerpoint, except that you can run the slide’s code live! It’s really neat how well it works. The only con in my book is that there isn’t a lot of theming that can be applied to your slides, so they do end up looking a bit plain.

In this article, we will look at two methods of creating a slideshow out of your Jupyter Notebook. The first method is by using Jupyter Notebook’s built-in slideshow capabilities. The second is by using a plug-in called RISE.

Let’s get started!

Note: This article assumes that you already have Jupyter Notebook installed. If you don’t, then you might want to go to their website and learn how to do so. Continue reading Creating Presentations with Jupyter Notebook →