I’m starting the process of learning how to use Jupyter Notebooks. Notebooks are documents that contain live code, commentary, results, pictures and more. Jupyter Notebooks are used for presentations, documentation, run books, troubleshooting guides and lots more. Their support within Azure Data Studio opens up lots of opportunities.
Azure Data Studio
If you’re interested in learning about notebooks yourself, or, as I publish the notebooks that I put together and you want to consume them, you need to have a mechanism. There are any number of third party or open source solutions to read notebooks. However, since I’m focused primarily on the Microsoft data platform, I’m using Azure Data Studio to do this work.
I’ve written in the past about using Azure Data Studio (ADS). I also have a bunch of videos (with a lot more on the way) on various aspects of ADS. Between them, I hope that they help you in using this new tool. Get the latest copy of ADS and you too can start learning about notebooks. I already have one video introducing Jupyter Notebooks ready for you.
GitHub
In addition to the work here on the blog and the videos that I’m going to continue producing, the principal source for the notebooks themselves will be my listings on GitHub. You can access the Notebooks I’m working on here. I’m actively updating these. I’ll add lots more. Please feel free to use my software published there under the MIT license.
I’m currently working on three different notebooks. I’m putting together a notebook for a presentation on containers. My plan is to use the notebook as the presentation itself and have it perform all the demo code as I present. Prepare to see more of this type of presentation from others. I’m also learning some Python as I put together this presentation, so I’m documenting my learning process with another notebook. Finally, as an experiment, I’m converting the first chapter of my book on execution plans into a notebook.
Conclusion
My goal with the Jupyter Notebooks is three fold. First, I want to know the technology, so I’m going to use it in order to learn it. Second, I want to try to share the learning with you so that you can take advantage of it. Finally, I’m hoping that you’ll also take part, make some suggestions, feedback and comments because, that will all loop back around to my first goal of learning the technology.
Please, watch this space because there’s more to come.
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I’ve been learning Jupyter Notebooks & Python on-off for a short while now and I have to say that once you get use to the notebook style of doing your work, it’s fantastic to use. Unfortunately I’ve been using Anaconda release to do this which just always ends up in a big mess when trying to simply keep it up to date with the latest version of modules and features.
I tried ADS before it was renamed, and at the time thought it seemed very, beta and struggled to see where it was heading really. If they intend to focus on data science/analytics, graphing data quick and easily that’ll be amazing, especially if they can do it inside notebooks, but I won’t hold my breath since they have http://notebooks.azure.com already.
It’ll be pleasure to learn what you learn as you share it.
So far, it’s been a struggle. Still, I’ll keep going with it, see where things end up. ADS was originally shipped as a very minimal viable product. However, they’ve kept updating it and today, it’s actually WAY more than minimal. It’s worth checking out. Depending on what you’re doing with your data, I’d say it’s a full blown alternative to SSMS.
[…] April, I said I was going to start learning Jupyter Notebooks. It’s November. Let’s get going with your first Jupyter […]
[…] I don’t know. This is one of those times I’m using the blog as a way to learn while simultaneously sharing with you (and yeah, I know that some of you hate this approach of […]