IJulia.jl

Yes - you need to use the IJulia kernel: https://github.com/JuliaLang/IJulia.jl

Pluto.jl appears to be a Julia centric notebook alternative to Jupyter and its multi-language Kernels, including IJulia [1]. I imagine there are many trade-offs between the two but the primary one I see is the runtime size/Python-dependencies of Jupyter versus the reach of the platform. There is also a great deal of overlap between IDEs and Notebook platforms. [1] https://github.com/JuliaLang/IJulia.jl Edit: "pure Julia" => "Julia centric" based on jakobnissen's comment

I think this is what you're looking for: https://github.com/JuliaLang/IJulia.jl

Ok that puts some bounds on it; we are talking 1/10ths of seconds as significant? Or 1/2 seconds? There is work on this (https://github.com/JuliaLang/IJulia.jl/issues/346) and later versions of Julia 0.4 feel pretty snappy to me compared to R (which is the other tool I generally use nowadays)

The language agnostic Jupyter with its interactive notebook comes close to Mathematica's environment. http://jupyter.org/ Jupyter supports Python and other languages like Julia (https://github.com/JuliaLang/IJulia.jl ). I don't know if there are JS and Lua bindings but both would lend themself because of their first class functions and functional language features.

Not quite native, but you can use Knitr with Julia. Carson Sievert (IA State stats grad student) has written up some slides: http://heike.github.io/stat590f/gadfly/carson-knitr IJulia[1] is probably closest to the community supported equivalent, but it's based on IPython [1]: https://github.com/JuliaLang/IJulia.jl

Very cool. There are native IPython notebook kernels for Python, Julia [1], R [2], Haskell [3] and now Erlang. Which is why the project is being made even more language-agnostic and being renamed as Jupyter [4]. [1] https://github.com/JuliaLang/IJulia.jl [2] https://github.com/takluyver/IRkernel [3] http://gibiansky.github.io/IHaskell [4] http://jupyter.org/

It depends on what you need. DataFrames [1] is a pretty good replacement for R's data frames. Distributions [2] is pretty amazing. Gadfly.jl [3] is a great ggplot-style plotting library that integrates nicely with IJulia [4]. If you have questions about specific things you need to do and want pointers, post on the julia-users list [5] and you should get some good answers. [1] http://harlanh.github.io/DataFrames.jl/ [2] http://distributionsjl.readthedocs.org/en/latest/ [3] https://github.com/dcjones/Gadfly.jl [4] https://github.com/JuliaLang/IJulia.jl [5] https://groups.google.com/forum/#!forum/julia-users

Regarding workflow, the best option is IJulia (https://github.com/JuliaLang/IJulia.jl) which has nice integration with plotting and useful things like LaTeX. Vi and Emacs are well-supported, and I know the Sublime tools have gotten a lot of attention from several people. Not directly related to performance, but you might be interested in this: https://github.com/helgee/JPLEphemeris.jl

It should be noted that the IPython Notebook is being developed to support multiple backends. People are working on backends for Haskell[1], Scala [2], and Julia[3]. I'd love to see a Clojure backend. All of this does not obviate the challenges of setting up IPython, but that could also be (somewhat)resolved via cloud services[4][5][6]. [1] http://gibiansky.github.io/IHaskell/ [2] https://github.com/mattpap/IScala [3] https://github.com/JuliaLang/IJulia.jl [4] http://www.windowsazure.com/en-us/develop/python/tutorials/i... [5] https://www.wakari.io/ [6] http://blog.picloud.com/2012/12/23/introducing-the-picloud-n...

Excellent work with IHaskell; I don't want to hijack this thread, but since it came up organically: The PyCall.jl [1] package allows transparent calling of Python from Julia. It's quite stable and exceptionally well done (it was written by Steven G. Johnson of FFTW [2] fame – his software is uniformly impressive). The IJulia package [3], which primarily provides a pure Julia IPython kernel so that you can interact with Julia via the various IPython front-ends, also includes [4] a Python package for calling Julia from Python plus IPython "magics" for calling Julia from a normal IPython process. This is rather more experimental than IJulia, but should be usable. [1] https://github.com/stevengj/PyCall.jl [2] http://fftw.org [3] https://github.com/JuliaLang/IJulia.jl [4] https://github.com/JuliaLang/IJulia.jl/tree/master/python

I'm impressed by how LightTable works with iPython to provide a good environment for data analysis, but I'm keeping my fingers crossed and wishing that the stars will align to see LT be the go-to environment for Julia. They are both early projects, and seem to be a fantastic complement to one another. Julia also is able to talk to the iPython notebook backend, so I don't think this would be so difficult. I only wish I had the time and expertise to do it myself. https://github.com/JuliaLang/IJulia.jl

Not sure if you know about IJulia [0]--they've been working a lot with the IPython folks. I haven't tried it, but it looks promising. [0] https://github.com/JuliaLang/IJulia.jl