Another point I have not yet seen mentioned: If your code is
painfully slow, that can often be fixed without leaving R by
experimenting with different ways of doing the same thing -- often after
using profiling your code to find the slowest part as described in
chapter 3 of "Writing R Extensions".
If I'm given code already written in C (or some other language),
unless it's really simple, I may link to it rather than recode it in R.
However, the problems with portability, maintainability, transparency to
others who may not be very facile with C, etc., all suggest that it's
well worth some effort experimenting with alternate ways of doing the
same thing in R before jumping to C or something else.
Hope this helps.
Spencer
On 1/17/2011 10:57 AM, David Henderson wrote:
I think we're also forgetting something, namely testing. If you write your
routine in C, you have placed additional burden upon yourself to test your C
code through unit tests, etc. If you write your code in R, you still need the
unit tests, but you can rely on the well tested nature of R to allow you to
reduce the number of tests of your algorithm. I routinely tell people at Sage
Bionetworks where I am working now that your new C code needs to experience at
least one order of magnitude increase in performance to warrant the effort of
moving from R to C.
But, then again, I am working with scientists who are not primarily, or even
secondarily, coders...
Dave H
----- Original Message ----
From: Dirk Eddelbuettel<e...@debian.org>
To: Patrick Leyshock<ngkbr...@gmail.com>
Cc: r-devel@r-project.org
Sent: Mon, January 17, 2011 10:13:36 AM
Subject: Re: [Rd] R vs. C
On 17 January 2011 at 09:13, Patrick Leyshock wrote:
| A question, please about development of R packages:
|
| Are there any guidelines or best practices for deciding when and why to
| implement an operation in R, vs. implementing it in C? The "Writing R
| Extensions" recommends "working in interpreted R code . . . this is normally
| the best option." But we do write C-functions and access them in R - the
| question is, when/why is this justified, and when/why is it NOT justified?
|
| While I have identified helpful documents on R coding standards, I have not
| seen notes/discussions on when/why to implement in R, vs. when to implement
| in C.
The (still fairly recent) book 'Software for Data Analysis: Programming with
R' by John Chambers (Springer, 2008) has a lot to say about this. John also
gave a talk in November which stressed 'multilanguage' approaches; see e.g.
http://blog.revolutionanalytics.com/2010/11/john-chambers-on-r-and-multilingualism.html
In short, it all depends, and it is unlikely that you will get a coherent
answer that is valid for all circumstances. We all love R for how expressive
and powerful it is, yet there are times when something else is called for.
Exactly when that time is depends on a great many things and you have not
mentioned a single metric in your question. So I'd start with John's book.
Hope this helps, Dirk
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