[ploika]

I also primarily write ML-focused Python. For me, having originally learned R and C at the same time, nothing has ever surpassed RStudio as a dev environment. For the past several years my preferred setup has been tmux and Vim with vim-slime in one pane and IPython in the other.

(Personally, and speaking only for myself, I hate Jupyter notebooks with a burning passion. I think they are one of the worst things ever to have happened to software development, and definitely the worst thing ever to have happened to ML/data science.)

[proamdev123]

Why do you hate Jupyter notebooks so much that it reaches “worst thing to ever have happened“ status?

Why do you love R Studio so much? (I’ve never used it, so no judgment)

[huganabaga]

> Why do you hate Jupyter notebooks so much that it reaches “worst thing to ever have happened“ status?

It's the "with a passion" part. A certain sub-population is prone to deciding that they love or hate something, based on some early experience or social context, and then every future experience with the thing is then strong-armed into supporting that supposed strong opinion. There is no rational reason for this. It's a very extreme form of confirmation bias.

It's pretty fascinating actually, as it's often times employed by rather intelligent people. With a slight tendency towards the autistic end of the spectrum, but there is certainly more research into this needed. Perhaps somebody working on a degree in sociology is interested i digging further?

[ploika]

I can't justify it - it's pure preference and opinion, irrationally held. A big part of it is probably that type of programming I generally need to do is closer to using an overgrown calculator (with DataFrames) than doing proper Software Development to build a thing.

I much prefer having the code over _here_, and then having the results in a separate pane over _there_. Jupyter style mixing of inputs and outputs tends to confuse me, and in my hands gets very messy very quickly.

The slides in this light hearted talk from JupyterCon in 2018 probably give a better explanation than I could.

https://conferences.oreilly.com/jupyter/jup-ny/public/schedu...

[account-5]

If like to know too. I learned python in jupyter notebooks. It makes experimenting and incremental development much easier (IMO) provided you remember to account for the current state of the notebook, which sometimes has me pulling my hair out.