feedgnuplot VS oni

Thanks for the post. The obvious comparison is feedgnuplot: https://github.com/dkogan/feedgnuplot/

That works similarly in that it plots standard input. The backend is gnuplot, which is a double-edged sword: it's far more full-featured than brplot, but almost certainly is much slower also. I'll try out brplot to see if it would be a good replacement for cases where speed is important. Thanks!

Oh hey Dima.

Feedgnuplot is really slick.

https://github.com/dkogan/feedgnuplot

It's in the debian repos too.

Is there a declarative language or framework to create ad-hoc GUIs that consume structured data from stdin stream and spit-out a GUI?

Like feedgnuplot [1] but not only restricted to graphs.

[1] https://github.com/dkogan/feedgnuplot

I found using shell as an interactive environment to be pretty productive using https://github.com/dkogan/feedgnuplot and https://github.com/dkogan/vnlog. The filesystem becomes your state (instead of in memory state of your Python interpreter) which forces you to write Unix-style tools. Plotting with feedgnuplot spins up an interactive Qt plotter which I often used to explore 3D plots. It's not "inline" and fancy and does take a bit of grokking but I eventually found it more productive than Jupyter, especially as my development moved away from Python.

One of the tools I absolutely love is feedgnuplot which presents a stdin CLI interface to gnuplot.

Also, if one doesn't want to learn Gnuplot's DSL try using feedgnuplot which presents a stdin interface for whitespace delimited tabular data.

Write space delimited tabular data (ideally in vnlog format) and plot it using feedgnuplot. Also helps decouple concerns (data generating application focuses on generating data).

Now here comes the endboss: Jupyter. For the first time, I feel like I'm missing out on stuff when using vim. I've started a job in datascience, which is actually awesome. However, I work a lot with image data. I also do a lot of analysis on results, meaning I do a lot of fancy plots that hopefully show the weaknesses of our prediction models. I recently wrote an augmentation algorithm where I had to see the output in form of an image after every step to make sure it's correct. This is not a possible workflow in vim right now. I know of many solutions that I already tried, like for example jupyter-vim or the jupyter vim mode. I'd like to work inside my terminal though. I'm not this kind of purist who needs to have a terminal that is compatible with VT100 or whatever people came up with in the 80ies. I also don't care if my terminal in based on an ascii like grid or actually rendered in HTML. I just want (Neo)vim, with the functionality of jupyter (inline plotting) even if this means vim has to be rendered inside an electron app or whatever people use these days for fancy GUIs. Imagine an electron based editor like Oni which not only runs the "real" neovim in the background, but is also able to do inline figures, images, plots and even interactive stuff. It seems to me like I can't be the only one who wants this. So after all this, here's the question: Is there anything you now of that allows for this kind of stuff? Is there any other workflow that I'm not aware of? Or do people just not use those features when working with vim? Pls help a vimmer stay at vim.

Oni or Oni2

SpaceVim - A community-driven vim distribution

While learning Vim, I went through the `vimtutor` many times until I felt really comfortable. After that you can try more advanced stuff (I applied the same pattern with the oni[0] built-in tutorial). Last but not least there are Youtube channels: theprimeagen[1] and Greg Hurell[2] come to my mind. I particularly recommend theprimeagen (he is a Netflix engineer) because he has videos about real-life workflow. And speaking about real life, I was amazed by this video[3] the first time I saw it, it's a very good introduction to macros.

0: https://github.com/onivim/oni

1: https://www.youtube.com/channel/UC8ENHE5xdFSwx71u3fDH5Xw

2: https://www.youtube.com/channel/UCXPHFM88IlFn68OmLwtPmZA/vid...

3: https://youtube.com/watch?v=hraHAZ1-RaM