IJulia Kernel not starting unless IJulia is installed in the global environment, ie (v1.1)

essenciary · February 25, 2019, 11:56am

I recently updated my mac to latest Mojave (10.14.3) and it looks like IJulia no longer works (Safari 12.0.3). The executed cell just hangs and never returns. I see lots of JS errors.

julia> versioninfo()
Julia Version 1.1.0
Commit 80516ca202 (2019-01-21 21:24 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin14.5.0)
  CPU: Intel(R) Core(TM) i7-6820HQ CPU @ 2.70GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, skylake)

cormullion · February 25, 2019, 2:07pm

Works for me.

stevengj · February 25, 2019, 2:16pm

If you’re seeing Javascript errors, then the problems aren’t due to IJulia but rather to Jupyter itself. If you are using an old Jupyter installation maybe you need to update it. (If you are using Julia’s own Jupyter installation, do using Conda; Conda.update())

essenciary · February 25, 2019, 11:13pm

Thanks. I did a fresh install so it’s the latest Conda. Also, I can’t run using Conda as it’s not explicitly added to the project.

(data-exploration) pkg> st
    Status `~/Dropbox/Projects/data-exploration/Project.toml`
  [a93c6f00] DataFrames v0.17.1
  [c91e804a] Gadfly v1.0.1
  [7073ff75] IJulia v1.17.0
  [39abe10b] MySQL v0.7.0+ #master (https://github.com/JuliaDatabases/MySQL.jl.git)
  [295af30f] Revise v1.0.2
  [340e8cb6] SearchLight v0.8.0 [`~/.julia/dev/SearchLight`]

julia> using Conda
ERROR: ArgumentError: Package Conda not found in current path:
- Run `import Pkg; Pkg.add("Conda")` to install the Conda package.

Upon further investigation, the JS errors seem irrelevant. The real issue seems to be that the Julia Kernel doesn’t start. The Python kernel starts just fine (despite showing a bunch of JS errors too).

essenciary · February 25, 2019, 11:16pm

Hmmm… Looks like the actual problem is that IJulia won’t work unless it’s installed in the global environment, ie (v1.1). If it is installed in a Project only, it seems to fail to start the kernel.

stevengj · February 27, 2019, 10:09pm

If you want to run it in particular project, you can do so but you need to install a custom kernel specification that passes --project=.... when it launches julia.

tkf · February 28, 2019, 4:52pm

Is it possible to detect that IJulia is installed in a non-default project in the build script? It would be nice to not install the kernelspec and show a warning message when there is no IJulia in the default project.

stevengj · February 28, 2019, 7:15pm

I guess the build script could install the kernel for the current project?

tkf · February 28, 2019, 7:28pm

You mean to create ~/.local/share/jupyter/kernels/julia-$PROJECT_ID-1.1 (and alike in non-*nix)? But how do you determine $PROJECT_ID? Maybe the sha1 of the path to Project.toml or something?

Actually, I think it’s better to discourage people for installing IJulia to non-default project. We have stackable LOAD_PATH so I don’t think you need to install IJulia in each project for most of the cases (though I’m not super sure).

MA_Laforge · July 24, 2021, 3:10am

Thanks @essenciary! I have just been bit by the exact same problem you described here.

My Julia 1.6.2 kernel kept failing to load on my new Jupyter installation as well. I was unable to figure out the cause until I read this thread.

Typical setup (AFAIK)

To get Jupyter running, I did what I assume most people would given IJulia’s README.md file. I let “IJulia create and manage its own Python/Jupyter installation” (quote from https://github.com/JuliaLang/IJulia.jl/blob/master/README.md):

using IJulia
notebook()

What was atypical in my setup

I’m getting more proficient with environments now, so I never added IJulia to the v1.6 (default) environment for Julia v1.6.1.

Instead, I created a project/environment called “EnvJupyter” that I use for the sole purpose of launching Jupyter notebooks from a “clean” environment.
The intent was to limit EnvJupyter to only have essential (known) packages when the Jupyter notebook server is launched.
So I added only IJulia and Revise to this EnvJupyter environment.

Surprising result

I was really surprised to see that my Julia kernel kept failing to load in this clean environment.

Suggestions regarding custom kernel specs

Sadly, I don’t fully appreciate the suggestions given above by @stevengj & @tkf regarding custom kernel specifications (I would need to play around with this feature to get a better feel).

But, from what I can tell:

It looks like they are customizations allowing users to overwrite the default behaviour, which is to initialize kernels with the default v1.6 environment (or whatever version of Julia you are using).

What I would expect

Maybe this is just me, but I would have expected there to be a little blurb on the IJulia/README.md file explaining that,

by default:

Kernels are initialized from Julia’s default (ex: v1.6) release-dependent environment, and that IJulia had to be added to that environment for Kernels to be initialized.

otherwise:

Users can install and specify custom kernels & associated environments using the steps outlined here: Making kernels for Jupyter — jupyter_client 7.1.0 documentation

At the moment, the README.md file does point to the steps for specifying custom kernels, but does not really explain how it relates to the default behaviour. My guess is that users are expected to piece together this concept from the “custom kernel” section and the installation section of the docs.

Then again, I suppose this might all just be my tendency to “do things the wrong way”.