JupyterCon 2023

Omer Dunay

A Software Engineer at Meta, Ex Microsoft, excited about notebooks, language services and everything related to making developing Python.
Linkedin - https://www.linkedin.com/in/omer-dunay-505a9544/
Would love to chat on:
1. Notebook Product in enterprise environment.
2. Python Language Services (An Example for a language server I wrote https://developers.facebook.com/blog/post/2022/07/18/enabling-faster-python-authoring-with-wasabi/)
3. GenAI for notebooks - How GPT-4 alike can be leveraged for notebooks.
4. Supporting ML tools through notebooks.
5. Any other topic that comes to mind!

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Autoreload in Production at Meta
Omer Dunay, Omer Dunay

An underappreciated aspect of Jupyter and IPython experiences in general is their ability to autoreload Python modules during running sessions via the autoreload extension. At Meta, we began leveraging this functionality to power interactive test sessions that allow software engineers to quickly iterate on their projects without waiting for slow restart times.

However, the base autoreload algorithm suffers from a number of reliability issues and can easily crash, thereby necessitating a costly restart. In this presentation, we’ll describe references reload, which is our new and improved autoreload algorithm with a number of benefits over the basic autoreload functionality. We’ll show how we use references reload in production to save developers hours of time, and we’ll close with a concrete use case for development on top of Bento server, which is Meta’s internal version of the Jupyter notebook server.

Enterprise Jupyter Infrastructure
Louis Armand 1