11-30, 09:50–10:20 (Europe/Amsterdam), Ernst-Curie
Jupyter Notebooks revolutionized Data Science - Reactive Notebooks build on top of this giant. Reactivity solves a couple of problems:
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Improved safety: It is impossible to get into an invalid state (where you would hit "rerun all" in Jupyter).
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Simplified interactivity: Changing a value also updates those cells which depend on it.
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Simplified deployment: The notebook itself is already a dashboard (with fully customizable html frontend).
In addition, the new notebook allows for self-updates, i.e. listening for some remote events and rerunning notebook cells automatically with the new updated value. This upgrades your notebook to a real-time analytics process.
In this talk I will present the new notebook and go through all its powerful features.
The first Reactive Notebook was build for JavaScript (called Observable), which inspired Pluto.jl, by now a solid reactive notebook for Julia. For Python recently IPyflow was presented, which adds experimental reactivity to Jupyter.
This Python Reactive Notebook builds on top of Pluto, with all the mentioned benefits. The notebook is stored in a plain python file, where cells are are marked by comments (the file is actually executable/importable like a standard python file).
No previous knowledge expected
Stephan Sahm is working as a data scientist and engineer since 7 years, after studying Applied Stochastics and Cognitive Science.
Recently he founded Jolin.io, a company dedicated to support businesses with green data science tools and respective consulting.
For more prudence and care about resource consumption in data science.