R and Julia’s aren’t good? They’re in the name, so I would have thought support would continue to be strong. I like Julia’s Pluto and the reactive style more than Jupyter anyway.
Every year, most JuliaCon workshops are presented via Jupyter notebooks; the Julia support is pretty good and has remained stable for a long while.
Some of the unofficial extensions like `code_prettify` don't work for Julia kernels, but at least for my usage, I've never felt the need for such tools in a Jupyter notebook.
IJulia is falling behind. If you look at github activity, it has 1 commit in past month. Compared to 9 authors and 39 commits in past month for IPython. IJulia issues are piling up.
Anaconda foundation does really great marketing, outreach, advocacy, education...it's a good first place for data scientists to land. But actually installing and using Conda is always annoying. I wind up doing everything with pip and venv, because pip jsut works.
On the topic of Conda and Jupyter, install jupyter via a virtualenv pip installation, and then to use a specific conda kernel, load your conda environment in another shell, and install IRkernel in that environment. As long as you install to the main Jupyer prefix, jupyter should see the new conda kernel.
You can do this for as many kernels/conda envs as you need
