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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (12) Chapters Close

Preface 1. Installation and Setting up the Environment 2. Adding an Engine FREE CHAPTER 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Providing multiuser with Docker


Docker is another mechanism that can be used to allow multiple users of the same Notebook without collision. Docker is a system that allows you to construct sets of applications into an image that can be run in the Docker container (much like ships at a dock).

Docker runs in most environments. Docker allows many instances of an image to be run in the same machine, but each maintains a separate address space. So, each user of a Docker image has their own instance of the software and their own set of data/variables. Exactly what we are looking for with our Notebook!

Each image is a complete stack of software necessary to run, for example, a web server, web applications, APIs, and so on.It is not a large leap to think of an image of your Notebook. The image contains Jupyter server code and your Notebook. The result is a completely intact unit that does not share any space with anyone else.

Getting ready

Installing Docker involves downloading the latest version (the...

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