Jupyter Tutorial - Read the Docs

Jupyter Tutorial

Release 1.1.0 Veit Schiele

Jun 26, 2023

CONTENTS

1 Introduction

3

1.1 Target group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Why Jupyter? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Jupyter infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.4 Workspace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 What's new?

5

3 Notebook

7

3.1 Install Jupyter Notebook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.2 Create notebook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3.3 Keyboard shortcuts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.4 Jupyter paths and configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.5 Parameterisation and scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.6 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4 JupyterLab

29

4.1 Install JupyterLab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.2 JupyterLab extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.3 JupyterLab on JupyterHub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.4 Real-time collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.5 Scheduler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5 JupyterHub

35

5.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

5.2 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5.3 systemdspawner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 5.4 Create service nbviewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 5.5 ipyparallel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

6 Binder

61

7 nbconvert

63

7.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

7.2 Use on the command line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

7.3 nb2xls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

7.4 Own exporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

8 nbviewer

67

8.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

8.2 Extending the Notebook Viewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

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8.3 Access control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

9 Kernels

69

9.1 Install, view and start the kernel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

9.2 Python2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

9.3 What's new in Python 3.8? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

9.4 What's new in Python 3.9? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

9.5 What's New In Python 3.10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

9.6 R-Kernel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

10 ipywidgets

83

10.1 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

10.2 Widget list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

10.3 Widget events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

10.4 Custom widget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

10.5 ipywidgets libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

10.6 Embed Jupyter widgets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

11 nbextensions

131

11.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

11.2 List of extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

11.3 Create plugin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 11.4 setup.ipynb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 11.5 ipylayout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141

12 Visualise data

145

13 Dashboards

147

13.1 Jupyter Dashboards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148

13.2 Appmode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151

13.3 Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153

13.4 Voil? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

13.5 jupyter-flex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209

14 Sphinx

213

14.1 nbsphinx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

14.2 Executable Books . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218

15 Use cases

219

16 Index

221

Index

223

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Jupyter Tutorial, Release 1.1.0

Jupyter notebooks are growing in popularity with data scientists and have become the de facto standard for rapid prototyping and exploratory analysis. They inspire experiments and innovations enormously and as well they make the entire research process faster and more reliable. In addition, many additional components are created that expand the original limits of their use and enable new uses.

What do you want to do?

JupyterNotebook

Single user

Teamwork

Convert Java, R, Julia etc. Extend notebooks

Embed notebooks

nbconvert Kernels

Conversion service

JupyterLab JupyterHub

Binder nbviewer Widgets nbextensions Visualise

data

Examples

Dashboards in HTML

Enterprise applications

nbsphinx Executable Books

CONTENTS

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Jupyter Tutorial, Release 1.1.0

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CONTENTS

CHAPTER

ONE

INTRODUCTION

1.1 Target group

The users of Jupyter notebooks are diverse, from data scientists to data engineers and analysts to system engineers. Their skills and workflows are very different. However, one of the great strengths of Jupyter notebooks is that they allow these different experts to work closely together in cross-functional teams. Data scientists

explore data with different parameters and summarise the results. Data engineers

check the quality of the code and make it more robust, efficient and scalable. Data analysts

use the code provided by data engineers to systematically analyse the data. System engineers

provide the research platform based on the JupyterHub on which the other roles can perform their work. In this tutorial we address system engineers who want to build and run a platform based on Jupyter notebooks. We then explain how this platform can be used effectively by data scientists, data engineers and analysts.

1.2 Why Jupyter?

How can these diverse tasks be simplified? You will hardly find a tool that covers all of these tasks, and several tools are often required even for individual tasks. Therefore, on a more abstract level, we are looking for more general patterns for tools and languages with which data can be analysed and visualised and a project can be documented and presented. This is exactly what we are aiming for with Project Jupyter. The Jupyter project started in 2014 with the aim of creating a consistent set of open source tools for scientific research, reproducible workflows, computational narratives and data analysis. In 2017, Jupyter received the ACM Software Systems Award ? a prestigious award which, among other things, shares with Unix and the web. To understand why Jupyter notebooks are so successful, let's take a closer look at the core functions: Jupyter Notebook Format

Jupyter Notebooks are an open, JSON-based document format with full records of the user's sessions and the code they contain. Interactive Computing Protocol The notebook communicates with the computing kernel via the Interactive Computing Protocol, an open network protocol based on JSON data via ZMQ and WebSockets.

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Jupyter Tutorial, Release 1.1.0

Kernels Kernels are processes that execute interactive code in a specific programming language and return the output to the user.

See also: ? Jupyter celebrates 20 years

1.3 Jupyter infrastructure

A platform for the above-mentioned use cases requires an extensive infrastructure that not only allows the provision of the kernel and the parameterisation, time control and parallelisation of notebooks, but also the uniform provision of resources. This tutorial provides a platform that enables fast, flexible and comprehensive data analysis beyond Jupyter notebooks. At the moment, however, we are not yet going into how it can be expanded to include streaming pipelines and domaindriven data stores. However, you can also create and run the examples in the Jupyter tutorial locally.

1.4 Workspace

Setting up the workspace includes installing and configuring IPython and Jupyter notebooks, nbextensions and ipywidgets.

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Chapter 1. Introduction

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