blocks|key|3108207|text|我也是have+been+looking+at+Julia+ever+since+Doug+Bates+sent+me+a+heads-up+in+January。但就像@gsk3一样，我在"Rcpp级别“上衡量这一点，因为我希望将丰富的R对象传递给Julia。而这一点现在似乎根本不受支持。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3108208|Julia有一个很好的简单的C接口。这样我们就可以得到像.C()这样的东西。但正如最近在r-devel上讨论的那样，你实际上并不需要.C()，在大多数情况下，你宁愿使用.Call()来传递代表真实R对象的实际SEXP变量。因此，由于这一限制，我现在认为Julia在R中的应用范围很小。|style|CODE|3108209|也许在Julia成熟一点之前，使用tcp/ip到Rserve的间接接口可以是第一个开始，我们可以得到一个合适的C%2B%2B接口。或者在进入中间层之前，我们使用基于Rcpp的东西从R获取到C%2B%2B，就像实际的Rcpp只提供C层一样。我不知道。|3108210|在一天结束的时候，可能需要一些耐心。我大约在1996年或1997年开始关注R，当时Fritz+Leisch在comp.os.linux.announce新闻组上发布了第一个公告。而R当时的功能相当有限(但S语言的全部承诺，当然，我们知道我们有一个赢家)。几年后，我准备让它成为我的主要建模语言。当时克朗的包裹还不到100个……|3108211|朱莉娅很有可能做到这一点。但就目前而言，我怀疑我们中的许多人都会在R上完成工作，并且只会好奇地瞥一眼Julia。|3108212|entityMap|0|LINK|mutability|MUTABLE|url|https://plus.google.com/u/0/109246313993679724191/posts/1kYs5UouPgA^0|3|26|0|0|S|4|1U|4|2C|7|0|0|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@]|9|@$A|W|B|X|1|Y]]|C|$]]|$1|D|3|E|5|6|7|Z|8|@$A|10|B|11|F|G]|$A|12|B|13|F|G]|$A|14|B|15|F|G]]|9|@]|C|$]]|$1|H|3|I|5|6|7|16|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|17|8|@]|9|@]|C|$]]|$1|L|3|M|5|6|7|18|8|@]|9|@]|C|$]]|$1|N|3|-4|5|6|7|19|8|@]|9|@]|C|$]]]|O|$P|$5|Q|R|S|C|$T|U]]]]

I too <a href="https://plus.google.com/u/0/109246313993679724191/posts/1kYs5UouPgA" rel="nofollow noreferrer">have been looking at Julia ever since Doug Bates sent me a heads-up in January</a>. But like @gsk3, I measure this on an &quot;Rcpp scale&quot; as I would like to pass rich R objects to Julia. And that does not seem to be supported at all right now.
Julia has a nice and simple C interface. So that gets us something like <code>.C()</code>. But as recently discussed on r-devel, you really do not want <code>.C()</code>, in most cases you rather want <code>.Call()</code> in order to pass actual SEXP variables representing real R objects. So right now I see little scope for Julia from R because of this limitation.
Maybe an indirect interface using tcp/ip to Rserve could be a first start before Julia matures a little and we get a proper C++ interface. Or we use something based on Rcpp to get from from R to C++ before we enter an intermediate layer [which someone would have to write] from which we data feed to Julia, just like the actual R API only offers a C layer. I don't know.
And the end of the day, some patience may be needed. I started to look at R around 1996 or 1997 when Fritz Leisch made the first announcements on the comp.os.linux.announce newsgroup. And R had rather limited facilities then (but the full promise of the S language, of course, si we knew we had a winner). And a few years later I was ready to make it my primary modeling language. At that time CRAN had still way less than 100 packages...
Julia may well get there. But for now I suspect many of us will get work done in R, and have just a few curious glimpses at Julia.

blocks|key|233082|text|正如我在this+answer中描述的那样，Julia开发计划允许将Julia代码编译到共享库中，可使用C调用。一旦发生这种情况，从R调用Julia代码就像调用C/C%2B%2B代码一样容易。然而，在这成为可能之前，还需要做大量的工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|233083|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/a/10711762/659248^0|4|B|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

The Julia development plan, as I described in <a href="https://stackoverflow.com/a/10711762/659248">this answer</a> is to allow compilation of Julia code to shared libraries, callable using the C ABI. Once this happens, it will be as easy to call Julia code from R as it is to call C/C++ code. There is, however, a fair amount of work required before this becomes possible.

blocks|key|3108260|text|快速更新。自从这个问题被提出以来，已经有了Julia包的开始，它允许从Julia内部调用R程序。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3108261|更多信息请点击这里：https://github.com/lgautier/Rif.jl|offset|length|3108262|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/lgautier/Rif.jl^0|0|A|Y|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

A quick update. Since this question was asked, there has been the beginnings of a Julia package that allows one to call R programs from within Julia. 

More here: <a href="https://github.com/lgautier/Rif.jl" rel="noreferrer">https://github.com/lgautier/Rif.jl</a>

blocks|key|235630|text|有没有人看过这个项目？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|235631|https://github.com/armgong/RJulia|offset|length|235632|相当新，但似乎正在做所要求的事情！|235633|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|X|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|P|8|@]|9|@$D|Q|E|R|1|S]]|A|$]]|$1|F|3|G|5|6|7|T|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|U|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|C]]]]

Has anyone seen this project?

<a href="https://github.com/armgong/RJulia">https://github.com/armgong/RJulia</a>

Fairly new but seems to be doing exactly what is requested!

blocks|key|2894547|text|从R开始，RJulia+R包看起来相当不错。R+CMD+check运行时没有警告或错误(如果正确安装了julia+)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2894548|在我看来，最大的任务是让Julia返回命名列表，它构成了R中真正基本的、灵活的通用数据结构。|2894549|请注意，Doug+Bates提醒我注意RCall，这是一个从Julia到R的双向接口(即，从R到Julia的另一个方向)。此外，Doug还建议将julia+0.4.0作为目标，而不是当前julia的稳定版本。|BOLD|2894550|自编写上述代码以来，又出现了几个接口:现在(2021-04)，我们已经有了R包|2894551|2894552|JuliaCall+(~2017)将Julia嵌入到R中，并积极维护available+from+CRAN.|unordered-list-item|2894553|JuliaConnectoR+(~2019)，也可以从目标更高的CRAN获得，例如，将julia对象直接导入R|2894554|2894555|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/armgong/RJulia|1|https://github.com/JuliaStats/RCall.jl|2|https://github.com/Non-Contradiction/JuliaCall|3|https://cran.r-project.org/package=JuliaCall|4|https://github.com/stefan-m-lenz/JuliaConnectoR|5|https://cran.r-project.org/package=JuliaConnectoR^0|M|B|1F|5|5|6|0|0|0|26|5|J|5|1|0|0|0|0|9|0|9|2|Y|J|3|0|0|E|0|E|4|W|4|5|0|0^^$0|@$1|2|3|4|5|6|7|1B|8|@$9|1C|A|1D|B|C]|$9|1E|A|1F|B|C]]|D|@$9|1G|A|1H|1|1I]]|E|$]]|$1|F|3|G|5|6|7|1J|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|1K|8|@$9|1L|A|1M|B|J]]|D|@$9|1N|A|1O|1|1P]]|E|$]]|$1|K|3|L|5|6|7|1Q|8|@]|D|@]|E|$]]|$1|M|3|-4|5|6|7|1R|8|@]|D|@]|E|$]]|$1|N|3|O|5|P|7|1S|8|@$9|1T|A|1U|B|C]]|D|@$9|1V|A|1W|1|1X]|$9|1Y|A|1Z|1|20]]|E|$]]|$1|Q|3|R|5|P|7|21|8|@$9|22|A|23|B|C]]|D|@$9|24|A|25|1|26]|$9|27|A|28|1|29]]|E|$]]|$1|S|3|-4|5|6|7|2A|8|@]|D|@]|E|$]]|$1|T|3|-4|5|6|7|2B|8|@]|D|@]|E|$]]]|U|$V|$5|W|X|Y|E|$Z|10]]|11|$5|W|X|Y|E|$Z|12]]|13|$5|W|X|Y|E|$Z|14]]|15|$5|W|X|Y|E|$Z|16]]|17|$5|W|X|Y|E|$Z|18]]|19|$5|W|X|Y|E|$Z|1A]]]]

The <a href="https://github.com/armgong/RJulia" rel="noreferrer">RJulia</a> R package looks quite good now from R. <code>R CMD check</code> runs without warnings or errors (if <code>julia</code> is properly installed).
Biggest TODO in my view is to get Julia to return named lists which constitute the really basic flexible general data structure in R.
Note that Doug Bates alerted me about <a href="https://github.com/JuliaStats/RCall.jl" rel="noreferrer">RCall</a> a bi-directional interface from Julia to R (i.e., the other direction than R to Julia). Also, Doug recommended to target julia 0.4.0 rather than the current stable versions of julia.
Several more interfaces have appeared since the above was written:
Now (2021-04), we've got R packages
<ul>
<li><a href="https://github.com/Non-Contradiction/JuliaCall" rel="noreferrer"><code>JuliaCall</code></a> (~2017) which embeds Julia in R, and is actively maintained <a href="https://CRAN.R-project.org/package=JuliaCall" rel="noreferrer">available from CRAN</a>.</li>
<li><a href="https://github.com/stefan-m-lenz/JuliaConnectoR" rel="noreferrer"><code>JuliaConnectoR</code></a> (~2019), also available from <a href="https://CRAN.R-project.org/package=JuliaConnectoR" rel="noreferrer">CRAN</a> which aims even higher, e.g., directly importing julia objects into R</li>
</ul>

blocks|key|230267|text|还有来自XR系列软件包的XRJulia+package，旨在实现eXtend+R，作者是John+Chambers+(R的创造者之一)。它使用一种稍有不同的方法(JSON)在Julia和R之间传输数据，然后是rJulia和类似的包。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|230268|entityMap|0|LINK|mutability|MUTABLE|url|https://cran.r-project.org/web/packages/XR/index.html|1|https://cran.r-project.org/web/packages/XRJulia/index.html^0|X|1|13|1|4|2|0|C|F|1|0^^$0|@$1|2|3|4|5|6|7|P|8|@$9|Q|A|R|B|C]|$9|S|A|T|B|C]]|D|@$9|U|A|V|1|W]|$9|X|A|Y|1|Z]]|E|$]]|$1|F|3|-4|5|6|7|10|8|@]|D|@]|E|$]]]|G|$H|$5|I|J|K|E|$L|M]]|N|$5|I|J|K|E|$L|O]]]]

There is also the <a href="https://cran.r-project.org/web/packages/XRJulia/index.html" rel="noreferrer">XRJulia package</a> from <a href="https://cran.r-project.org/web/packages/XR/index.html" rel="noreferrer">XR</a> family of packages aiming to eXtend R by John Chambers (one of the creators of R). It uses a bit different approach (JSON) to transfer data between Julia and R then rJulia and similar packages.

blocks|key|3108418|text|我最近创建了一个名为JuliaCall的R包，它将Julia嵌入到R中。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3108419|https://cran.r-project.org/web/packages/JuliaCall/index.html|3108420|https://github.com/Non-Contradiction/JuliaCall|3108421|该包的用法如下：|3108422|library(JuliaCall)
julia+<-+julia_setup()
julia_command("a+=+sqrt(2)");+julia_eval("a")
julia_eval("sqrt(2)")
julia_call("sqrt",+2)
julia_eval("sqrt")(2)|code-block|syntax|javascript|3108423|正如您所看到的，您可以很容易地发送命令字符串和调用Julia函数。|3108424|还有一些使用JuliaCall包装Julia包的R包，例如，|3108425|使用Convex.jl在R中进行有纪律的凸编程的|3108426|convexjlr，也是在CRAN.|unordered-list-item|3108427|ipoptjlr，上使用Julia+package+Ipopt.jl.|3108428|的内点编程R接口(IPOPT)|3108429|欢迎对JuliaCall的任何反馈！！|3108430|entityMap|0|LINK|mutability|MUTABLE|url|1|2|https://github.com/Non-Contradiction/convexjlr|3|https://github.com/Non-Contradiction/ipoptjlr^0|A|9|0|0|1O|0|0|0|1A|1|0|0|0|0|6|9|0|0|0|9|0|9|2|0|0|8|Q|8|0|8|3|0|0|3|9|0^^$0|@$1|2|3|4|5|6|7|1H|8|@$9|1I|A|1J|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1K|8|@]|D|@$9|1L|A|1M|1|1N]]|E|$]]|$1|H|3|I|5|6|7|1O|8|@]|D|@$9|1P|A|1Q|1|1R]]|E|$]]|$1|J|3|K|5|6|7|1S|8|@]|D|@]|E|$]]|$1|L|3|M|5|N|7|1T|8|@]|D|@]|E|$O|P]]|$1|Q|3|R|5|6|7|1U|8|@]|D|@]|E|$]]|$1|S|3|T|5|6|7|1V|8|@$9|1W|A|1X|B|C]]|D|@]|E|$]]|$1|U|3|V|5|6|7|1Y|8|@]|D|@]|E|$]]|$1|W|3|X|5|Y|7|1Z|8|@$9|20|A|21|B|C]]|D|@$9|22|A|23|1|24]]|E|$]]|$1|Z|3|10|5|Y|7|25|8|@$9|26|A|27|B|C]|$9|28|A|29|B|C]]|D|@$9|2A|A|2B|1|2C]]|E|$]]|$1|11|3|12|5|6|7|2D|8|@]|D|@]|E|$]]|$1|13|3|14|5|6|7|2E|8|@$9|2F|A|2G|B|C]]|D|@]|E|$]]|$1|15|3|-4|5|6|7|2H|8|@]|D|@]|E|$]]]|16|$17|$5|18|19|1A|E|$1B|G]]|1C|$5|18|19|1A|E|$1B|I]]|1D|$5|18|19|1A|E|$1B|1E]]|1F|$5|18|19|1A|E|$1B|1G]]]]

I create an R package called <code>JuliaCall</code> recently, which embeds Julia in R. The package is on CRAN. 

<a href="https://cran.r-project.org/web/packages/JuliaCall/index.html" rel="noreferrer">https://cran.r-project.org/web/packages/JuliaCall/index.html</a>

<a href="https://github.com/Non-Contradiction/JuliaCall" rel="noreferrer">https://github.com/Non-Contradiction/JuliaCall</a>

The usage of the package is like this:

<pre><code>library(JuliaCall)
julia &lt;- julia_setup()
julia_command("a = sqrt(2)"); julia_eval("a")
julia_eval("sqrt(2)")
julia_call("sqrt", 2)
julia_eval("sqrt")(2)
</code></pre>

As you can see, you could send command strings and call Julia functions really easily.

And there are also some R packages wrapping Julia packages using <code>JuliaCall</code>, for example, 

<ul>
<li><a href="https://github.com/Non-Contradiction/convexjlr" rel="noreferrer"><code>convexjlr</code></a> for Disciplined Convex Programming in R using Convex.jl, which is also on CRAN.</li>
<li><a href="https://github.com/Non-Contradiction/ipoptjlr" rel="noreferrer"><code>ipoptjlr</code></a>, an R Interface for Interior Point OPTimizer (IPOPT) using Julia package <code>Ipopt.jl</code>.</li>
</ul>

Welcome for any feedback on <code>JuliaCall</code>!!

blocks|key|230277|text|你可能还想看看我的尝试：JuliaConnectoR+R-package。该软件包可从GitHub和CRAN获得。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|230278|它的目标是将Julia中的函数直接导入R中，这样它们就可以像R代码中的R函数一样使用。Julia函数的返回值被转换为R数据结构，可以在R中使用，也可以传递回Julia。为了进一步集成Julia和R，还可以通过将R函数作为回调函数传递给R来从Julia回调。|230279|与XRJulia类似，JuliaConnectoR依赖于TCP，但它是面向功能的，并使用优化的自定义流格式，而不是像XRJulia那样使用基于文本的JSON消息。通过TCP通信的一个优点是相对于不同版本的Julia和R的稳定性，这在像RCall和JuliaCall这样的C接口级别的集成中很难维护。|230280|该软件包适用于Julia≥1.0和各种R版本。|230281|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/stefan-m-lenz/JuliaConnectoR|1|https://cran.r-project.org/web/packages/JuliaConnectoR/^0|C|E|17|6|0|1E|4|1|0|0|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@$9|W|A|X|B|C]]|D|@$9|Y|A|Z|1|10]|$9|11|A|12|1|13]]|E|$]]|$1|F|3|G|5|6|7|14|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|15|8|@]|D|@]|E|$]]|$1|J|3|K|5|6|7|16|8|@]|D|@]|E|$]]|$1|L|3|-4|5|6|7|17|8|@]|D|@]|E|$]]]|M|$N|$5|O|P|Q|E|$R|S]]|T|$5|O|P|Q|E|$R|U]]]]

You also might want to check out my attempt: The <code>JuliaConnectoR</code> R-package. The package is available from <a href="https://github.com/stefan-m-lenz/JuliaConnectoR" rel="nofollow noreferrer">GitHub</a> and <a href="https://cran.r-project.org/web/packages/JuliaConnectoR/" rel="nofollow noreferrer">CRAN</a>.

It's goal is to import functions from Julia directly in R such that they can be used like R functions in R code. The return values of Julia functions are translated to R data structures, which can be used in R and also be passed back to Julia.
For a further integration of Julia and R, it is also possible to call back from Julia to R by passing R functions as callback functions.

Similar to XRJulia, the JuliaConnectoR relies on TCP, but it is functionally oriented and uses an optimized custom streaming format instead of text-based JSON messages as XRJulia does.
One advantage of communicating by TCP is the stability with respect to different versions of Julia and R. This is much harder to maintain with an integration at the level of C interfaces like RCall and JuliaCall do.

The package works with Julia &ge; 1.0 and a wide range of R versions.

Julia looks very promising for fast and syntax-sane computation (e.g. <a href="http://www.johnmyleswhite.com/notebook/2012/03/31/julia-i-love-you/" rel="noreferrer">here</a>), but I suspect it will not be anywhere near R in terms of overall statistics workflow for some time yet. So I'd like to use it where C++ is mainly used in R programs: to optimize slow portions of code. Before I invest the time in learning Julia, though, I am curious what facilities there are for embedding Julia snippets in R code.

So:

<ul>
<li>What facilities are out there for linking R and Julia?</li>
<li>How robust and well-thought-out are they, on a scale of zero to Rcpp?</li>
</ul>

I want to call Julia from R, just as Rcpp allows calling C++ from within R right now. I do not want to call R from Julia. (So RCall.jl would not work)

Linking R and Julia?

数据结构

Julia

JSON

Julia看起来非常有希望进行快速和语法合理的计算(例如)，但我怀疑在一段时间内，它在总体统计工作流程方面还不会接近R。所以我想在C++主要用于R程序的地方使用它:来优化代码的慢速部分。不过，在我花时间学习Julia之前，我想知道在R代码中嵌入Julia代码片段有哪些工具。所以：有什么设施可以连接R和Julia？从零到...

问把R和Julia联系起来？
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