Jeremy Tuloup, Johan Mabille Navigating the Jupyter Landscape | JupyterCon 2023

JupyterCon · Beginner ·🛡️ AI Safety & Ethics ·2y ago
The Jupyter ecosystem is vast and complex, with many different projects and libraries that work together to support interactive computing and data science. In this talk, we will navigate and explore the Jupyter ecosystem, highlighting the key projects and libraries that make up the ecosystem and discussing how they relate to each other. We will start by introducing the core Jupyter projects, including the Jupyter Notebook and JupyterLab, and explaining how they provide a platform for interactive computing and data visualization. We will then discuss some of the key sub-projects within the Jupyter ecosystem, such as JupyterHub for enabling multi-user access to notebooks and nbconvert for converting notebooks to other formats, and we will explain how they fit into the overall landscape of Jupyter. Next, we will delve into the underlying projects and libraries that make Jupyter and its related projects possible, such as the Jupyter server, the core APIs projects and the traitlets library. We will discuss the different protocols used for communication between the applications and the kernels, and show how it makes Jupyter agnostic to the language. We will also cover some of the key technologies used by Jupyter and its related projects, such as the Tornado web framework or the ZeroMQ messaging library, and we will explain how these technologies fit into the Jupyter landscape. Throughout the talk, we will provide examples of how these tools and technologies can be used in practice and discuss the latest developments and future directions of the Jupyter ecosystem. By the end of the talk, attendees will have a better understanding of the Jupyter ecosystem and how its various projects and libraries fit together to enable interactive computing and data science. Outline: Introduction to the Jupyter ecosystem Overview of the core Jupyter projects (Jupyter Notebook, JupyterLab) Overview of key sub-projects within the Jupyter ecosystem (JupyterHub, nbconvert) Explanation of
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from JupyterCon · JupyterCon · 0 of 60

← Previous Next →
1 Interview   Joshua Patterson NVIDIA
Interview Joshua Patterson NVIDIA
JupyterCon
2 Dave Stuart - Jupyter as an Enterprise “Do It Yourself” (DIY) Analytic Platform | JupyterCon 2020
Dave Stuart - Jupyter as an Enterprise “Do It Yourself” (DIY) Analytic Platform | JupyterCon 2020
JupyterCon
3 Jeffrey Mew - Supercharge your Data Science workflow | JupyterCon 2020
Jeffrey Mew - Supercharge your Data Science workflow | JupyterCon 2020
JupyterCon
4 Michelle Ufford- Supercharging SQL Users with Jupyter Notebooks | JupyterCon 2020
Michelle Ufford- Supercharging SQL Users with Jupyter Notebooks | JupyterCon 2020
JupyterCon
5 Alan Yu - What we learned from introducing Jupyter Notebooks to the SQL community  | JupyterCon 2020
Alan Yu - What we learned from introducing Jupyter Notebooks to the SQL community | JupyterCon 2020
JupyterCon
6 Chris Holdgraf- 2i2c: sustaining open source through hosted Jupyter infrastructure | JupyterCon 2020
Chris Holdgraf- 2i2c: sustaining open source through hosted Jupyter infrastructure | JupyterCon 2020
JupyterCon
7 Yiwen Li - Intro to Elyra - an AI centric extension for JupyterLab | JupyterCon 2020
Yiwen Li - Intro to Elyra - an AI centric extension for JupyterLab | JupyterCon 2020
JupyterCon
8 Luciano Resende - What's new on Elyra - A set of AI centric JupyterLab extensions | JupyterCon 2020
Luciano Resende - What's new on Elyra - A set of AI centric JupyterLab extensions | JupyterCon 2020
JupyterCon
9 Alan Chin - Explore and Extend AI Pipeline Runtimes with Elyra and JupyterLab | JupyterCon 2020
Alan Chin - Explore and Extend AI Pipeline Runtimes with Elyra and JupyterLab | JupyterCon 2020
JupyterCon
10 Eduardo Blancas- Streamline your Data Science projects with Ploomber | JupyterCon 2020
Eduardo Blancas- Streamline your Data Science projects with Ploomber | JupyterCon 2020
JupyterCon
11 Thorin Tabor - Democratizing the accessibility of computational workflows | JupyterCon 2020
Thorin Tabor - Democratizing the accessibility of computational workflows | JupyterCon 2020
JupyterCon
12 Simon Willison- Using Datasette with Jupyter to publish your data | JupyterCon 2020
Simon Willison- Using Datasette with Jupyter to publish your data | JupyterCon 2020
JupyterCon
13 Brendan O'Brien - Using Qri (“query”) to fetch, query, combine and publish datasets.|JupyterCon 2020
Brendan O'Brien - Using Qri (“query”) to fetch, query, combine and publish datasets.|JupyterCon 2020
JupyterCon
14 Georgiana Dolocan - Putting the JupyterHub puzzle pieces together | JupyterCon 2020
Georgiana Dolocan - Putting the JupyterHub puzzle pieces together | JupyterCon 2020
JupyterCon
15 Yuvi Panda- Running nonjupyter applications on JupyterHub with jupyter-server-proxy| JupyterCon 2020
Yuvi Panda- Running nonjupyter applications on JupyterHub with jupyter-server-proxy| JupyterCon 2020
JupyterCon
16 Richard Wagner- The Streetwise Guide to JupyterHub Security | JupyterCon 2020
Richard Wagner- The Streetwise Guide to JupyterHub Security | JupyterCon 2020
JupyterCon
17 TamNguyen- Handling Custom Jupyter Data Sources | JupyterCon 2020
TamNguyen- Handling Custom Jupyter Data Sources | JupyterCon 2020
JupyterCon
18 Immanuel Bayer- ipyannotator - the infinitely hackable annotation framework  | JupyterCon 2020
Immanuel Bayer- ipyannotator - the infinitely hackable annotation framework | JupyterCon 2020
JupyterCon
19 Rebecca Kelly- A shared Python, R and Q  Jupyter Notebook - A Quant Sandbox Dream |JupyterCon 2020
Rebecca Kelly- A shared Python, R and Q Jupyter Notebook - A Quant Sandbox Dream |JupyterCon 2020
JupyterCon
20 Itay Dafna - Leap of faith: Transitioning from Excel to Jupyter-based applications | JupyterCon 2020
Itay Dafna - Leap of faith: Transitioning from Excel to Jupyter-based applications | JupyterCon 2020
JupyterCon
21 Damián Avila - Using the Jupyterverse to power MADS | JupyterCon 2020
Damián Avila - Using the Jupyterverse to power MADS | JupyterCon 2020
JupyterCon
22 Chiin Rui Tan- From Zero to Hero | JupyterCon 2020
Chiin Rui Tan- From Zero to Hero | JupyterCon 2020
JupyterCon
23 Firas Moosvi- Teaching an Active Learning class with Jupyter Book| JupyterCon 2020
Firas Moosvi- Teaching an Active Learning class with Jupyter Book| JupyterCon 2020
JupyterCon
24 Daniel Mietchen- Jupyter in the Wikimedia ecosystem | JupyterCon 2020
Daniel Mietchen- Jupyter in the Wikimedia ecosystem | JupyterCon 2020
JupyterCon
25 Qiusheng Wu- How Jupyter and geemap enable interactive mapping and analysis | JupyterCon 2020
Qiusheng Wu- How Jupyter and geemap enable interactive mapping and analysis | JupyterCon 2020
JupyterCon
26 Stephanie Juneau- Jupyterenabled astrophysical analysis for researchers and students|JupyterCon 2020
Stephanie Juneau- Jupyterenabled astrophysical analysis for researchers and students|JupyterCon 2020
JupyterCon
27 Denton Gentry- The Care and Feeding of JupyterHub for Climate Solution Models| JupyterCon 2020
Denton Gentry- The Care and Feeding of JupyterHub for Climate Solution Models| JupyterCon 2020
JupyterCon
28 Tingkai Liu- FlyBrainLab: Interactive Computing in the Connectomic/Synaptomic Era  | JupyterCon 2020
Tingkai Liu- FlyBrainLab: Interactive Computing in the Connectomic/Synaptomic Era | JupyterCon 2020
JupyterCon
29 Kunal Bhalla- A Notebook Style Guide| JupyterCon 2020
Kunal Bhalla- A Notebook Style Guide| JupyterCon 2020
JupyterCon
30 Julia Wagemann - How to avoid 'Death by Jupyter Notebooks' | JupyterCon 2020
Julia Wagemann - How to avoid 'Death by Jupyter Notebooks' | JupyterCon 2020
JupyterCon
31 David Pugh - Best practices for managing Jupyter-based data science  | JupyterCon 2020
David Pugh - Best practices for managing Jupyter-based data science | JupyterCon 2020
JupyterCon
32 Karla Spuldaro - Debugging notebooks and python scripts in JupyterLab | JupyterCon 2020
Karla Spuldaro - Debugging notebooks and python scripts in JupyterLab | JupyterCon 2020
JupyterCon
33 Shreyas Dalia - assert browserTest == True # Frontend Testing JupyterLab  | JupyterCon 2020
Shreyas Dalia - assert browserTest == True # Frontend Testing JupyterLab | JupyterCon 2020
JupyterCon
34 Chris Holdgraf - The new Jupyter Book stack | JupyterCon 2020
Chris Holdgraf - The new Jupyter Book stack | JupyterCon 2020
JupyterCon
35 Hamel Husain - Fastpages - A new, open source Jupyter notebook blogging system | JupyterCon 2020
Hamel Husain - Fastpages - A new, open source Jupyter notebook blogging system | JupyterCon 2020
JupyterCon
36 Marc Wouts - Jupytext: Jupyter Notebooks as Markdown Documents | JupyterCon 2020
Marc Wouts - Jupytext: Jupyter Notebooks as Markdown Documents | JupyterCon 2020
JupyterCon
37 Sheeba Samuel- ProvBook |JupyterCon 2020
Sheeba Samuel- ProvBook |JupyterCon 2020
JupyterCon
38 Philipp Rudiger - To Jupyter and back again | JupyterCon 2020
Philipp Rudiger - To Jupyter and back again | JupyterCon 2020
JupyterCon
39 Jacob Tomlinson - What is my GPU doing? | JupyterCon 2020
Jacob Tomlinson - What is my GPU doing? | JupyterCon 2020
JupyterCon
40 Afshin Darian - A visual debugger in Jupyter | JupyterCon 2020
Afshin Darian - A visual debugger in Jupyter | JupyterCon 2020
JupyterCon
41 Eric Charles - Jupyter Real Time Collaboration| JupyterCon 2020
Eric Charles - Jupyter Real Time Collaboration| JupyterCon 2020
JupyterCon
42 Devin Robison - Optimizing model performance | JupyterCon 2020
Devin Robison - Optimizing model performance | JupyterCon 2020
JupyterCon
43 Junhua zhao - PayPal Notebooks: ML & Data Science experience | JupyterCon 2020
Junhua zhao - PayPal Notebooks: ML & Data Science experience | JupyterCon 2020
JupyterCon
44 April Wang - Redesigning Notebooks for Better Collaboration | JupyterCon 2020
April Wang - Redesigning Notebooks for Better Collaboration | JupyterCon 2020
JupyterCon
45 Bryan Weber - Distributing and Collecting Jupyter Notebooks for Manual Grading| JupyterCon 2020
Bryan Weber - Distributing and Collecting Jupyter Notebooks for Manual Grading| JupyterCon 2020
JupyterCon
46 Georgiana Dolocan - The Littlest JupyterHub distribution | JupyterCon 2020
Georgiana Dolocan - The Littlest JupyterHub distribution | JupyterCon 2020
JupyterCon
47 Tim Metzler - Electronic Examination using Jupyter Notebook | JupyterCon 2020
Tim Metzler - Electronic Examination using Jupyter Notebook | JupyterCon 2020
JupyterCon
48 Blaine Mooers - Why develop a snippet library for Jupyter in your subject domain? | JupyterCon 2020
Blaine Mooers - Why develop a snippet library for Jupyter in your subject domain? | JupyterCon 2020
JupyterCon
49 Ryan Abernathey - Cloud Native Repositories for Big Scientific Data | JupyterCon 2020
Ryan Abernathey - Cloud Native Repositories for Big Scientific Data | JupyterCon 2020
JupyterCon
50 Tanya Rai - Introducing Bento: Jupyter Notebooks @ Facebook | JupyterCon 2020
Tanya Rai - Introducing Bento: Jupyter Notebooks @ Facebook | JupyterCon 2020
JupyterCon
51 Kenton McHenry - From Papers to Notebooks | JupyterCon 2020
Kenton McHenry - From Papers to Notebooks | JupyterCon 2020
JupyterCon
52 Ryan Herr - After model.fit, before you deploy| JupyterCon 2020
Ryan Herr - After model.fit, before you deploy| JupyterCon 2020
JupyterCon
53 Ana Ruvalcaba - Community building is a sustainability strategy | JupyterCon 2020
Ana Ruvalcaba - Community building is a sustainability strategy | JupyterCon 2020
JupyterCon
54 Martin Renou - Xeus: an ecosystem of Jupyter kernels | JupyterCon 2020
Martin Renou - Xeus: an ecosystem of Jupyter kernels | JupyterCon 2020
JupyterCon
55 Michael Wilson - Teaching teenagers to understand Dark Energy | JupyterCon 2020
Michael Wilson - Teaching teenagers to understand Dark Energy | JupyterCon 2020
JupyterCon
56 Davide De Marchi - Voilà dashboards for policy support | JupyterCon 2020
Davide De Marchi - Voilà dashboards for policy support | JupyterCon 2020
JupyterCon
57 Marcos Lopez Caniego - ESASky's JupyterLab widget| JupyterCon 2020
Marcos Lopez Caniego - ESASky's JupyterLab widget| JupyterCon 2020
JupyterCon
58 Praveen Kanamarlapud - Kernel Life Cycle Management | JupyterCon 2020
Praveen Kanamarlapud - Kernel Life Cycle Management | JupyterCon 2020
JupyterCon
59 Aaron Bray - Pulse Physiology Engine | JupyterCon 2020
Aaron Bray - Pulse Physiology Engine | JupyterCon 2020
JupyterCon
60 Aaron Watters - Using WebGL2 transform/feedback in Jupyter widgets | JupyterCon 2020
Aaron Watters - Using WebGL2 transform/feedback in Jupyter widgets | JupyterCon 2020
JupyterCon

Related AI Lessons

Addictive AI Could Become The Next Big Business Risk
AI-driven digital products can be addictive, posing risks to mental health and customer behavior, making it a significant business concern
Forbes Innovation
AI Compliance Checklist 2026: SOC 2, HIPAA, GDPR Guide
Learn how to ensure AI compliance with major regulations like SOC 2, HIPAA, and GDPR using a comprehensive checklist
Dev.to AI
Catch AI Hallucinations Before Your Audience Does: A Validation System That Actually Works
Learn to catch AI hallucinations before your audience does with a validation system that actually works
Dev.to · binky
Anti-AI Sentiment is Destroying the Environment
Anti-AI sentiment is linked to environmental harm, highlighting the need to reassess AI's role in sustainability
Medium · Cybersecurity
Up next
Risk Management Excellence with ISO 31000 Frameworks
Coursera
Watch →