Maybe of interest to the community: The more IDE-like JupyterLab was just released in beta: https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906 (and HN thread). Looks pretty cool. As far as I understand it, it should just work with IJulia. Has anyone tried it?
Very cool! I just installed it and am now playing around with it. it seems to work fine so far.
I’ve tried it and I like it!
I also think that Julia is given good support. I can’t find much that it can do with python that it can’t do in Julia, which is good since its still in beta.
It has a super responsive data viewer for importing .csv files, but you can’t have the same viewer for dataframe objects. This is a functionality that Julia, and I think also python, lack, but is super helpful for data exploration, like R’s View() function and Stata’s browse function. So I hope something gets implemented to that effect.
The tab-autocompletion doesn’t work for Julia. It works for python, though.
That’s https://github.com/jupyterlab/jupyterlab/issues/3705 and should be resolved in next release.
I spent most of today using it, and it’s great. The missing tab completion is annoying, but I’m sure it’ll be resolved soon. Being able to pin a cell’s output to a new pane is surprisingly excellent.
It is excellent. One more quality of life improvement is I can select the kernel in jupyterlab rather than typing a rather hard to remember name on the command line for the notebook or qtconsole.
In the standard Notebook you can select the kernel in
Kernel -> Change kernel.
Tab completion fix has been merged to IJulia master with support for displaying types in Jupyterlab:
I also just made a new pull request to IJulia that I think improves tab completion for symbols: https://github.com/JuliaLang/IJulia.jl/pull/634
I was looking into this today, I’ve never been big on Jupyter notebooks, but I’m more and more starting to see the value in them from a collaboration/(get a nice document at the end of the workday) point of view. However, I was wondering if it was possible to directly inject code from a julia file into a running notebook. I ask this because I like to reuse a lot of code that I make, and so I sort of develop the package capabilities as I am working. My workflow now consists of using
Atom to have one script file, and then when I want to add/alter a function to the package I just quickly evaluate the function definition in the respective file/module. I’m not sure if that can be mimicked using notebooks and
Revise.jl, without actually copy pasting the code left and right.
Couldn’t you just use
include from the notebook (in combination with Revise.jl)?
In the console mode I’ve found that just arrows up and down for previous entries means i don’t have to copy and paste very much. just “up, up, up, shift-enter”
Yea I think I underestimated the power of
Revise.jl, last time I looked at it was over a year ago. It seems that now it should be able to accomplish what I want to do.
Does anyone happen to know if it is possible to run a kernel on the server, but with the packages etc from the local machine? I managed to get a regular notebook server running to which I can then connect and start notebooks, but that’s not really what I want. I would like to connect local notebooks to the server. I found this
jupyter_kernel_gateway thing but I have no clue how to configure it and can’t find too many references online.
In their docs, there is a
Usecases section stating:
“Attach a local Jupyter Notebook server to a compute cluster in the cloud running near big data (e.g., interactive gateway to Spark)”
Which sounds exactly what I want to do. Any ideas?