Book Image

Learning Jupyter

By : Dan Toomey
Book Image

Learning Jupyter

By: Dan Toomey

Overview of this book

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It 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, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we’ll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.
Table of Contents (16 chapters)
Learning Jupyter
About the Author
About the Reviewer

Security in Jupyter

Jupyter notebooks are created in order to be shared with other users, in many cases over the Internet. However, Jupyter notebooks can execute arbitrary code and generate arbitrary code. This can be a problem if malicious aspects have been placed in a notebook. The default security mechanisms for Jupyter notebooks include the following:

  • Raw HTML is always sanitized (checked for malicious coding). Further information can be found at

  • You cannot run external JavaScript.

  • Cell contents (especially HTML and JavaScript) are not trusted (requires user validation to continue).

  • The output from any cell is not trusted.

  • All other HTML or JavaScript is never trusted. Clearing the output will cause the notebook to become trusted when saved.

Security digest

Notebooks can also use a security digest to ensure the correct user is modifying the contents. A digest takes into account the entire contents of the notebook and a secret (only known by the notebook creator). This combination ensures that malicious coding is not going to be added to a notebook.

You add a security digest to a notebook using the following command:


Here, you replace the notebook_secret part with your secret.

Trust options

You can specifically apply your trust to a notebook using a command-line option:

jupyter trust /path/to/notebook.ipynb

Or you can do it once the notebook is opened by the File | Trusted  Notebook menu option.