I'd wish the VSCode team could somehow integrate the concept. They seem to be excellent at execution.
(Or, if they finish their work on "html zones" (block decorators in atom), I'll start doing it myself)
Afaik, hydrogen plugin for atom does this [2] And there is another plugin that just wraps the notebook to live inside of atom [3]
[1] https://talkpython.fm/episodes/show/44/project-jupyter-and-i... [2] https://atom.io/packages/hydrogen [3] https://github.com/jupyter/atom-notebook
RStudio's new feature to R is Notebooks and it is available in RStudio version 1.0+. It takes what is great about Jupyter Notebooks and adds easier version control and much easier to batch process your reports. Which are both huge wins for me.
http://rmarkdown.rstudio.com/r_notebooks.html
Blog Post: https://blog.rstudio.org/2016/10/05/r-notebooks/
"Interactive R Markdown
As an authoring format, R Markdown bears many similarities to traditional notebooks like Jupyter and Beaker. However, code in notebooks is typically executed interactively, one cell at a time, whereas code in R Markdown documents is typically executed in batch.
R Notebooks bring the interactive model of execution to your R Markdown documents, giving you the capability to work quickly and iteratively in a notebook interface without leaving behind the plain-text tools and production-quality output you’ve come to rely on from R Markdown."
I haven't played with it yet, but another HN user pointed it out to me recently.
With that in, now the Monaco integration is being worked on: https://github.com/jupyterlab/jupyterlab/pull/1382.
We all want stronger editing capabilities, but it doesn't make sense for the Jupyter team to get into the business of writing text editors (plenty of better folks doing a great job on that already). So we're just trying to make it easier to integrate other text editors into the everyday workflow.
Thanks Fernando, Brian, Min & team for everything you've done with Jupyter. Looking fwd to using Jlab soon!
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But yes, JLab is shaping up quite nicely, opening up a lot of interesting possibilities. For advanced users/early adopters I think it's time to start playing with it (and filing issues for anything that's broken/sub-optimal, we really want to provide a great user experience with it once we hit 1.0).
Admittedly, I don't use a code editor, perhaps because I'm just too old, and got used to living without one. I remember when being able to edit a program in full screen mode was a big deal. But I certainly wouldn't turn down better editing for Jupyter.
...but perhaps software developers aren't the target audience in the first place. I tried to use Jupyter a few times, first when it was still only IPython, and it never seemed to fit in my code-execute-fix workflow that you have when developing scripts. In particular having to always reset the kernel to reexecute everything from scratch drove me crazy.
The only thing that's really missing for me is a more persistent data store in between kernel restarts. If it took more than 5 minutes to run something to transform or process my data, I don't want to have to redo it when I restart the kernel. I think there are a couple of plugins that handle this for you, but it would really be nice if it was implemented natively. The solution right now just seems to be producing a bunch of intermediate files that you reload when you restart the kernel.
Or had access to papers and videos showing how the development environments at Xerox(Lisp, Mesa/Cedar, Smalltalk) and Genera (Lisp) worked.
Hence why I am not found of having a graphics workstation full of xterms.
We need to make these workflows mainstream, not something that our descendants are reading about in paper and videos.
The restarting the kernel biz is painful, of course. But the interspersed plots and code are really useful.
Admittedly, most of my experience is with ipython but it is perfect for that. If there is a new algorithm/method I want to explore or I am figuring out an interface/structure, it is great. And I tend to not have to reset the kernel too often.
In that sense, jupyter was a great idea as you can now integrate documentation with code in a nice format.
Unfortunately, it also led to a strong focus on treating them as containers for the purpose of deploying code (more traditional software development).
Do you know of a better tool for such a flow, combined with the ability to have markdown+latex docs intermingled with the code? 'cause this is my workflow, but jupyter's code editor and kernell restart drives me crazy and anything else will have me keep the notes/docs separate from the code...
And please don't suggest Mathematica :) I absolutely love it's ux/i, but nobody uses it in ML/AI...
You can use whatever editor you want, but I quite like rstudio (I'm generally not a huge R person, so an environment with more help is useful, whereas with python I'd prefer just my own setup).
Edit - Importantly though, you actually don't need to use R, you can use python. I'm not sure how well that works with caching, as I've never tried it, but it's probably worth a go.
(Right now I use jupyter for some things, ipython gui for others, and pycharm for "real coding" tasks. Tried Spyder, but something about it makes it neither a good IDE nor a good notes/documentation system... though I can understand its appeal for Matlab folks).