Technically I see the JVM as an advantage. F# now as well as Julia are seen
as the data science languages contenders of the future.

Clojure has a lot going for it but never gets a mention,  just could not
understand why that is. Spark implements Scala and Python as languages to
use,  again you would wonder why not clojure here.

Is there a level of advocacy missing?

Sayth

On Tue, 31 Mar 2015 5:06 PM Mikera <mike.r.anderson...@gmail.com> wrote:

>
>
> On Tuesday, 31 March 2015 00:01:32 UTC+8, Phillip Lord wrote:
>
>>
>>
>>
>> Sayth Renshaw <flebbe...@gmail.com> writes:
>> > I last learned clojure in 1.2. Just curious why Clojure hasn't
>> > developed as a go to for data science?
>> >
>> > It never seems to get a mention R,Python and now Julia get the
>> > attention. By design it would appear that Clojure would be a good fit.
>> > Is it a lack of libraries, ease of install, no good default
>> > environment (R Rstudio, IPython ) where as you would need to use emacs
>> > with clojure, or is there just a better default use of Clojure?
>>
>>
>> I would say, lack of numpy or equivalent. And nice tools to link between
>> Clojure and the many C/Fortran numeric libraries. Python and R do this
>> natively.
>>
>
> core.matrix is effectively the equivalent of NumPy
>
> In some ways it is much more versatile, because it works with a general
> array abstraction rather than a specific concrete array format. There are
> core.matrix implementations (e.g. Clatrix) that link to native numerical
> libraries. There are also core.matrix implementations that run in pure,
> portable JVM code (e.g. vectorz-clj). You can also use plain old Clojure
> persistent vectors as a (slow but convenient) core.matrix implementation.
> Having all these options usable via the *same API* is a big win.
>
> core.matrix is certainly not yet as mature or fully featured as NumPy. But
> if it doesn't do what you need - please help improve it! PRs, bug reports
> and enhancement ideas all gratefully accepted.
>
> https://github.com/mikera/core.matrix
>
> There is also a Google Group here specifically dedicated to numerical
> topics in Clojure:
>
> https://groups.google.com/forum/#!forum/numerical-clojure
>
>
>>
>> Maybe if Clojure pulls itself away from the JVM this will change. One
>> big problem with both python and R for data science is that a lot of
>> interactive data visualisation happens on the web these days, and
>> neither python nor R support that so well. An ecosystem with a C hosted
>> clojure at the back end and Clojure script at the front end might work
>> well.
>>
>
> I agree Clojure is a great back-end for data-driven web applications.
>
> I would argue however that you don't need a "C-hosted" Clojure to get
> native back end performance since you can use tools like Clatrix to access
> BLAS etc. And aside from that, the JVM gives you a lot of big advantages on
> the server side (sophisticated memory management, excellent JIT
> compilation, concurrency, portability, library ecosystem etc.). I never
> quite understand the motivation of people who seem to want to reinvent all
> of this (probably badly) in native code. The JVM is an amazing piece of
> engineering, and I believe that a lot of the sucess of Clojure comes from
> taking advantage of this.
>
> I've personally had good experiences with Clojure on the back end and
> JavaScript/ClojureScript on the front end, and never once worried about
> performance.
>
>

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