Book Image

Learning Jupyter 5 - Second Edition

Book Image

Learning Jupyter 5 - Second Edition

Overview of this book

The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you’ve explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization.
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Scale


The current implementations of Jupyter have a scaling issue since, as the number of users increases, performance degrades significantly.

With the widespread adoption of Jupyter, the problem is becoming more apparent with additional use/users.

The Jupyter team is devoting a large part of their near-term efforts to enhancing the scalability of Jupyter to handle large numbers of users seamlessly. Some of the solutions being worked on include the following:

  • A proxy API having an API between browsers and server services scales out the application
  • MOAR servers, allowing multiple servers per user
  • Further integration of OAUTH throughout the server/services
  • Stress-testing work by the Jupyter team prior to market release