The Basics Of Jupyter Notebooks

Nigel Meakings has an introductory post to Jupyter Notebooks:

The Jupyter notebok environment consists of a browser-based notebook UI and a back-end server, running on port 8888 by default (if this port is taken it will start up on the next available port). This web server-based delivery of Notebooks means that you can browse to a remote server and execute your code there. This is the case, for example, when using a ready-made cluster such as an HDInsight Spark cluster, where all the tooling has been pre-installed for you. You open the notebook in the cluster portal within Azure, and it logs you in to the Jupyter server running on a node within the cluster. Note that if you want to allow multi-user access to your local Jupyter environment, you’ll need to be running a product such as JupyterHub.

I love using Jupyter when presenting because it’s the easiest way to intermix code, documentation, and images in one package, so it’s nice for pedagogical purposes.

Related Posts

Creating Big Data Clusters with Azure Data Studio

Niels Berglund takes us through the creation of a Big Data Cluster by using Azure Data Studio to generate a notebook: I wrote a blog post back in November 2018, about how to install and deploy SQL Server 2019 Big Data Cluster on Azure Kubernetes Service. Back then SQL Server 2019 Big Data Cluster was in private preview, (CTP 2.1 I […]

Read More

Develop BDC PySpark Jobs in Visual Studio Code

Jenny Jiang announces a new capability in Visual Studio Code: With the Visual Studio Code extension, you can enjoy native Python programming experiences such as linting, debugging support, language service, and so on. You can run current line, run selected lines of code, or run all for your PY file. You can import and export a .ipynb notebook and perform […]

Read More

Categories

February 2018
MTWTFSS
« Jan Mar »
 1234
567891011
12131415161718
19202122232425
262728