This is a repost of a rather old blog entry. John Myles White has subsequently become one of Julia's most prolific core developers, having created and contributed a variety of very high quality stats and machine learning packages for (and in) Julia:<p><a href="https://github.com/johnmyleswhite/BloomFilters.jl" rel="nofollow">https://github.com/johnmyleswhite/BloomFilters.jl</a>
<a href="https://github.com/johnmyleswhite/Calculus.jl" rel="nofollow">https://github.com/johnmyleswhite/Calculus.jl</a>
<a href="https://github.com/johnmyleswhite/Clustering.jl" rel="nofollow">https://github.com/johnmyleswhite/Clustering.jl</a>
<a href="https://github.com/HarlanH/DataFrames.jl" rel="nofollow">https://github.com/HarlanH/DataFrames.jl</a>
<a href="https://github.com/johnmyleswhite/DimensionalityReduction.jl" rel="nofollow">https://github.com/johnmyleswhite/DimensionalityReduction.jl</a>
<a href="https://github.com/JuliaStats/Distributions.jl" rel="nofollow">https://github.com/JuliaStats/Distributions.jl</a>
<a href="https://github.com/johnmyleswhite/FileFind.jl" rel="nofollow">https://github.com/johnmyleswhite/FileFind.jl</a>
<a href="https://github.com/JuliaStats/GLM.jl" rel="nofollow">https://github.com/JuliaStats/GLM.jl</a>
<a href="https://github.com/johnmyleswhite/Graphs.jl" rel="nofollow">https://github.com/johnmyleswhite/Graphs.jl</a>
<a href="https://github.com/johnmyleswhite/KLDivergence.jl" rel="nofollow">https://github.com/johnmyleswhite/KLDivergence.jl</a>
<a href="https://github.com/JuliaStats/LM.jl" rel="nofollow">https://github.com/JuliaStats/LM.jl</a>
<a href="https://github.com/johnmyleswhite/Languages.jl" rel="nofollow">https://github.com/johnmyleswhite/Languages.jl</a>
<a href="https://github.com/johnmyleswhite/Loss.jl" rel="nofollow">https://github.com/johnmyleswhite/Loss.jl</a>
<a href="https://github.com/doobwa/MCMC.jl" rel="nofollow">https://github.com/doobwa/MCMC.jl</a>
<a href="https://github.com/johnmyleswhite/NHST.jl" rel="nofollow">https://github.com/johnmyleswhite/NHST.jl</a>
<a href="https://github.com/johnmyleswhite/Optim.jl" rel="nofollow">https://github.com/johnmyleswhite/Optim.jl</a>
<a href="https://github.com/johnmyleswhite/RDatasets.jl" rel="nofollow">https://github.com/johnmyleswhite/RDatasets.jl</a>
<a href="https://github.com/johnmyleswhite/Resampling.jl" rel="nofollow">https://github.com/johnmyleswhite/Resampling.jl</a>
<a href="https://github.com/johnmyleswhite/TextAnalysis.jl" rel="nofollow">https://github.com/johnmyleswhite/TextAnalysis.jl</a>
<a href="https://github.com/johnmyleswhite/kNN.jl" rel="nofollow">https://github.com/johnmyleswhite/kNN.jl</a><p>The moral of the story might be that John puts his money where is mouth is. He thought Julia was awesome and now he's done a huge amount to make it even more so.
Why do people think that computing Fibonacci numbers recursively is a good benchmark of anything?<p>Doesn't it require O(n^2) function calls for something that can be computed in O(1)?
Finally there are downloadable binaries for Windows and OSX! <a href="http://code.google.com/p/julialang/downloads/list" rel="nofollow">http://code.google.com/p/julialang/downloads/list</a><p>Also, previous discussion: <a href="http://news.ycombinator.com/item?id=3784349" rel="nofollow">http://news.ycombinator.com/item?id=3784349</a>
I can understand the need for new programming languages to be continually developed, especially with differing power continuums. So I have nothing against this post, or Julia itself.<p>But when someone advertises that they want x feature and y feature in one language, such that the respective languages of x and y are essentially obsolete, I get a little skeptical. I'm certainly not the type of person who tries to vaguely advocate all languages are more or less the same and it's just taste; not at all.<p>But I think there are <i>reasons</i> why it's intrinsically difficult to design a language to have both the speed of C and the abstraction power of Lisp, for example. Things come at a price; this doesn't mean there isn't generally a clear victor for what you're trying to do, just that getting a paragon of linguistic design is very difficult.<p>But his test of Julia is promising, though honestly I'd really like to see a speed comparison on at least 100 lines of code, preferably a full application really.
Am I the only one with hopes of Julia actually evolving into a general purpose programming language?<p>With almost C++ level performance and homoiconicity it seems really sweet and I'd love to see it used instead of Go. Though 1-indexed arrays are definitely annoying as fuck...
Julia's math library is starting to shape up:<p><a href="http://docs.julialang.org/en/latest/stdlib/base/#mathematical-functions" rel="nofollow">http://docs.julialang.org/en/latest/stdlib/base/#mathematica...</a><p>It even has a digamma, Riemann zeta, and Bessel functions with fractional orders, which you won't find in Excel.<p>The statistics built-ins are a bit weak, however.
Can anyone venture a guess on how successful this will be ? Given that R is pretty widespread <i>right now</i>, and Scipy/Numpy/Blaze is looking to win in the future (with the Darpa funding for Continuum[1]).<p>Wonder if Julia was considered for the Darpa grant.<p>[1] <a href="http://www.itworld.com/big-data/340570/python-gets-big-data-boost-darpa" rel="nofollow">http://www.itworld.com/big-data/340570/python-gets-big-data-...</a>
Wow, the list of modules has gotten very respectable since the first time I heard about Julia.<p>I have one concern though: how well-tested are they? There's one really prominent contributor (John Myles White), who has written a rather large number of packages. But there are only a limited number of <i>bug-free</i> LOCs that a human can write in a given time-span.<p>So Julia might well be a better language than R, but is it standard library as reliable? And how much time will it take until it becomes as trusted as that of R?
Julia's benchmarks just turned me off. They are ignoring the "reasonable idioms" of each language, and specifically focusing only on RECURSIVE and ITERATIVE algos. And also ignoring other competing peers like lua based GSL Shell.
Please read
<a href="https://groups.google.com/forum/#!topic/julia-dev/2MJQ_uADH40" rel="nofollow">https://groups.google.com/forum/#!topic/julia-dev/2MJQ_uADH4...</a>
I've just started learning Julia and I'm also loving it so far.<p>It's really well designed with loads of great features (and decent libraries) for scientific computing.
I don't think many projects with such a horrible() distribution system succeeded in the past.<p>()horrible for package maintainers. Try to create a package from this... There are <i>no</i> releases. I don't see any use of DESTDIR. And bundled libraries are also a major setback. It seems like the developers want to make it as hard as possible to distribute their software.<p>And I see more and more software going this direction. :(
Lord knows there aren't enough Bobby Sherman references.<p><a href="http://www.youtube.com/watch?v=f7PLcHnMNKE" rel="nofollow">http://www.youtube.com/watch?v=f7PLcHnMNKE</a>