slides for my "I Don't Like Notebooks" #JupyterCon talk:https://t.co/30peBFwTbv

— Joel Grus (@joelgrus) August 24, 2018

I don’t like notebooks either. I agree with a lot of @joelgrus ‘s reasons and have a few others of my own https://t.co/D0DxniDyxt

— Ian Goodfellow (@goodfellow_ian) August 25, 2018

Notebooks generally don’t play very friendly with source control tools such as git

— Ian Goodfellow (@goodfellow_ian) August 25, 2018

Some information, such as TensorFlow Prints, gets invisibly printed in the backend rather than in the notebook

— Ian Goodfellow (@goodfellow_ian) August 25, 2018

I like Notebooks and they can be useful even in production-grade environments (see “Beyond Interactive: Notebook Innovation at Netflix” https://t.co/BJjjPQwbpT). However, all of @joelgrus points, especially the one about hidden state, are 100% valid and should be addressed https://t.co/ANUh7wixkX

— Xavier 🎗🤖🏃 (@xamat) August 26, 2018

This really is the best. https://t.co/fTpbn3zYdE

— Chris Albon (@chrisalbon) August 28, 2018

I think notebooks encourage putting everything into a single document, but that goes against clear communication and developing a coherent narrative of an analysis. https://t.co/bYkpED02Gk

— Roger D. Peng (@rdpeng) August 29, 2018

I have “notebooks” filed, informally, as a variant of, e.g. R markdown documents. You mix code and prose and develop interactively.
I happen to be more comfy without the notebook features, probably due to personal history.
Do others make an even bigger distinction?

— Jenny Bryan (@JennyBryan) August 29, 2018

3/ and yet, he completely misses the point of why notebooks have unlocked so much productivity in data science, ML. Notebooks are the only IDEs that support interactive visualization out of the box. I always code visualization pipelines in notebooks before transferring to libs

— Eric Jang (@ericjang11) February 25, 2019

5/ Nowadays, all my personal projects start out as Jupyter notebooks. At work things are a bit trickier, but my ideal: 95% of my development time is spent in notebooks, and 5% spent copying shared code from notebooks to infrastructure.

— Eric Jang (@ericjang11) February 25, 2019