Jupyter Notebooks on Azure

Jupyter notebooks on Microsoft Azure


The purpose of this page is to present the Microsoft Azure Jupyter notebook hosting service as an extremely valuable (currently free) tool for research.

In general we advocate using Jupyter notebooks to create research sandboxes, to develop paper content, to share reproducible results, and to communicate on a technical level. Jupyter notebooks support Python, R, F Sharp, Julia and other programming languages. They also support markdown including LaTeX mathematical formatting.

Microsoft to their immense credit has created a Jupyter notebook hosting service on their Azure cloud platform. This has two advantages over hosting a Jupyter notebook on a machine that you manage: First Azure takes care of the basics of managing the notebook and its host machine; so you don’t. Second the Azure Jupyter notebook is connected to other useful technogies; so it is already built into a broader technical context or ecosystem. These extensions include Azure Machine Learning Studio and GitHub, just to begin with. We believe this service has a great future and is well worth your time exploring.


  • ** Azure hosting of Jupyter is under development so be prepared to shoot them a ‘help!’ email. The other important thing to realize is that from a Python cell you can issue a Linux command using ‘!command’. In particular the link above on data loading tells you how to use !curl to load data from GitHub; and you may also want to avail yourself of ‘!conda install’ at the top of a particular notebook to make sure your added libraries are in place. **
  • * When your notebook shuts down any data you have uploaded will evaporate. It does not persist. We have an entire section below called ‘Rehydration’ on how to deal with this by parking the necessary files on GitHub. Please note: GitHub does have file size restrictions so you may need to resort to other means.*


As of spring 2017 Azure Jupyter notebooks do not persist data that you upload when the Notebook shuts down. This means that you have to “rehydrate” your data supply when you re-start; but this can be done with an initialization cell running Python as follows:

An Azure Jupyter notebook cell executing Python can run Linux commands by prefacing them with an exclamation mark ‘!’. In particular you can use the Linux curl command to inhale files (particularly in our case: Smallish data files and important figures, say .png files)
to the current Notebook session from GitHub. The GitHub URL to use is not necessarily easy to find; so let’s place it right here.

The key information is as follows:

My github account is 'my_username'
My repository is called 'my_reponame'
My branch is 'my_branchname'
My file is 'my_filename.png'

The curl command to retrieve this to /nbuser/home (where it will be called file0001.png) is:

!curl https://raw.githubusercontent.com/my_username/my_reponame/my_branchname/my_filename.png -o file0001.png
Tags: Jupyter