What are the best alternatives to JuliaBox?

[aerdely]

Since JuliaBox sunset will take place on May 31st what are the best options to run Julia in the cloud for academic users? I don’t mind to pay a reasonable fee. Thank you in advance.

[Oscar_Smith]

If you have institutional support, you can get a server running a jupyter kernel.

[aerdely]

I do not have institutional support. Any alternatives?

[ArchieCall]

repl.it

Not real fast but good in a learning environment.

[davidanthoff]

https://mybinder.org/ supports Julia, but the machines are not very beefy. It is the only free option I’m aware of.

GitHub Codespaces using Visual Studio or browser is nice and works with Julia (after some config). You’ll get the VS Code UI with that and can use the Julia extension for it.

I believe https://nextjournal.com/ and https://codeocean.com/ are also options.

[jling]

Julia on Google Colab: Free GPU-Accelerated Shareable Notebooks

(Disclosure: While I work for Google, this is not an official Google product or announcement.) tl;dr: For Julia on Colab with GPUs, first open this notebook and run the cell (takes ~15-20 minutes), then open this one to start using Julia. [Screenshot%20from%202018-09-21%2015-57-02] Recently, @denizyuret brought up on Slack that it would be nice if Google Colab supported Julia, especially for GPUs. I can’t promise anything about official or built-in support, but it turns out it’s possible to g…

[j_verzani]

Cocalc is an alternative with a very slow free option and modest pay option.

[Tamas_Papp]

You could ask local IT to set up a Jupyter server. If you don’t have a large number of users, a commodity box will be sufficient. The setup is quite simple.

[xiaodai]

Check this list https://github.com/xiaodaigh/awesome-data-science-notebook-engines

I think cocalc and NextJournal will work.

[William_Stein]

You are right, https://CoCalc.com fully supports Julia. We provide Jupyter notebooks with Julia 1.0, 1.3.1 and 1.4 kernels, and continue to ugrade and maintain our Julia support since it is in high demand by an increasing number of CoCalc users. We also provide command line terminal Julia, syntax highlighting and splitting for editing .jl files, X11 graphics, and a 1-click JupyteLab server. CoCalc is sufficiently open source that you can run your own server (see GitHub - sagemathinc/cocalc-docker: Docker setup for running CoCalc as downloadable software on your own computer), but we currently don’t have Dockerfile recipes that include Julia pre-installed (pull requests welcome).

[xiaodai]

@William_Stein

Dockerfile recipes that include Julia pre-installed (pull requests welcome).

GitHub - xiaodaigh/julia-data-science-base-docker-img: Julia Data Science...

Add some magic from here would help.

[kailukowiak]

You can use google colab but it takes maybe 10 minutes each time you start as julia has to install.

[MridulS]

You could also use GESIS notebooks notebooks.gesis[.]org (free for academic use) as an alternative, it builds on top of binderhub (mybinder) and the user sessions are persisted (the sweet spot between a binderhub and a jupyterhub ).

Any binder-able Julia repo can be directly imported in persistent binderhub, Pluto.jl notebooks can also be created and saved on gesis notebooks.

To open a pluto.jl server(just like mybinder) you can use this link, but sign up is required to persist your changes to the notebooks.

To open the demo Julia repo you can use this link, sign up required.

[Arnim]

https://notebooks.gesis.org/ is the Link