Announcing .NET Jupyter Notebooks – Scott Hanselman

• To start a new notebook, you can either type jupyter lab Anaconda prompt or launch a notebook using the Anaconda Navigator.

• Once Jupyter Lab has launched in your preferred browser, you have the option to create a C# or a F# notebook

For more information on our APIs via C# and F#, please check out our documentation on the binder side or in the dotnet/try repo in the NotebookExamples folder.

Features

To explore some of the features that .NET notebooks ships with, I put together dashboard for the Nightscout GitHub repo.

HTML output : By default .NET notebooks ship with several helper methods for writing HTML. From basic helpers that enable users to write out a string as HTML or output Javascript to more complex HTML with PocketView. Below I’m using the display() helper method.

Importing packages : You can load NuGet packages using the following syntax. If you’ve used Rosyln-powered scripting this #r for a reference syntax will be familiar.

#r "nuget:,"

For Example

#r "nuget:Octokit, 0.32.0"
#r "nuget:NodaTime, 2.4.6"
using Octokit;
using NodaTime;
using NodaTime.Extensions;
using XPlot.Plotly;

Do note that when you run a cell like this with a #r reference that you’ll want to wait as that NuGet package is installed, as seen below with the … detailed output.

Object formatters : By default, the .NET notebook experience enables users to display useful information about an object in table format.

The code snippet below will display all opened issues in the nightscout/cgm-remote-monitor repo.

display(openSoFar.Select(i => new {i.CreatedAt, i.Title, State = i.State.StringValue,  i.Number}).OrderByDescending(d => d.CreatedAt));

With the object formatter feature, the information will be displayed in a easy to read table format.

Plotting

Visualization is powerful storytelling tool and,a key feature of the Jupyter notebook experience. As soon as you import the wonderful XPlot.Plotly F# Visualization Package into your notebooks(using Xplot.Ploty;) you can begin creating rich data visualizations in .NET.

The graphs are interactive too! Hover over the different data points to see the values.

Learn, Create and Share

To learn, create and share .NET notebooks please check out the following resources:

• Learn: To learn online checkout the dotnet/try binder image for a zero install experience.
• Create: To get started on your machine check out the dotnet/try repo. Select the option highlighted option
   
• Share: If you want to share notebooks you have made using the .NET Jupyter kernel, the easiest way is to generate a Binder image that anyone can run on the web. For more information on how to do this please check out the .NET Jupyter documentation.

Checkout the online .NET Jupyter Notebook I created for to explore the NightScout GitHub project using C# and the Octokit APIs.

We hope you enjoy this new .NET Interactive experience and that you’re pleasantly surprised by this evolution of the .NET Try interactive kernel.

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