<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>narwally</author><text>I feel the same way, especially as an emacs user. Org-babel seems to be a superior implementation of the same idea. Org  is just a text document, so git and git diffs work. I can use any combination of languages I want in a document and have them running in different sessions. And best of all I can edit code blocks using my customized major mode for that language. On top of that you get all the goodness that comes with org-mode, not least of which is the ability export it to dozens of other human readable formats for easy sharing. I think there&amp;#x27;s even an exporter for jupyter notebooks (there&amp;#x27;s at least one for ipython notebooks).</text><parent_chain><item><author>zmmmmm</author><text>As with so many things python related (including python itself), I am perplexed by how willing people seem to be to fall in love with solutions that have so many limitations and problems. I find Jupyter just barely usable. I constantly have issues with editing in the cells, diagrams not sizing correctly, cells accidentally displaying huge amounts of data and freezing my browser, complete failure of autocompletion in many languages, a very awkward security model involving manual cutting and pasting of auth tokens around, nearly impossible to get a reasonable rendering of the notebook into something reasonable like PDF (yes there attempts at solutions, they are full of problems). Many limitations derive directly from the architecture where the kernels are limited in what they can do because specific parts have to be interpreted in the browser that are language specific.&lt;p&gt;From my perspective, it&amp;#x27;s a dumpster fire - in 2018 there should be something so much better than this. RStudio is a thousand times better but only does R. I used to like Beaker Notebook but it gave up due to Jupyter&amp;#x27;s popularity and converted itself into a bunch of Jupyter extensions which now have all of Jupyter&amp;#x27;s limitations.&lt;p&gt;Yet despite all this I can see that there&amp;#x27;s this enormous community that loves this and keeps developing and contributing to it.</text></item></parent_chain></comment><story><title>Why Jupyter is data scientists’ computational notebook of choice</title><url>https://www.nature.com/articles/d41586-018-07196-1</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>stult</author><text>I love everything about RStudio, except for all the R stuff.</text><parent_chain><item><author>zmmmmm</author><text>As with so many things python related (including python itself), I am perplexed by how willing people seem to be to fall in love with solutions that have so many limitations and problems. I find Jupyter just barely usable. I constantly have issues with editing in the cells, diagrams not sizing correctly, cells accidentally displaying huge amounts of data and freezing my browser, complete failure of autocompletion in many languages, a very awkward security model involving manual cutting and pasting of auth tokens around, nearly impossible to get a reasonable rendering of the notebook into something reasonable like PDF (yes there attempts at solutions, they are full of problems). Many limitations derive directly from the architecture where the kernels are limited in what they can do because specific parts have to be interpreted in the browser that are language specific.&lt;p&gt;From my perspective, it&amp;#x27;s a dumpster fire - in 2018 there should be something so much better than this. RStudio is a thousand times better but only does R. I used to like Beaker Notebook but it gave up due to Jupyter&amp;#x27;s popularity and converted itself into a bunch of Jupyter extensions which now have all of Jupyter&amp;#x27;s limitations.&lt;p&gt;Yet despite all this I can see that there&amp;#x27;s this enormous community that loves this and keeps developing and contributing to it.</text></item></parent_chain></comment><story><title>Why Jupyter is data scientists’ computational notebook of choice</title><url>https://www.nature.com/articles/d41586-018-07196-1</url></story>