From cbeleites at units.it  Tue Jan 18 10:48:48 2011
From: cbeleites at units.it (Claudia Beleites)
Date: Tue, 18 Jan 2011 10:48:48 +0100
Subject: [Rd] R vs. C now rather: how to ease package checking
In-Reply-To: <AANLkTim=ZhYg-X-cvQX=W25c3nY3v5AtmjBFA5Ec8F8+@mail.gmail.com>
References: <AANLkTikbHjP7JvwfWjSaWds7fa4Ek=8LEo14h-Rm5igq@mail.gmail.com>	<19764.34512.640668.433147@max.nulle.part>	<891858.34031.qm@web113714.mail.gq1.yahoo.com>	<4D3493B2.2070907@structuremonitoring.com>	<AANLkTim1jCxVaPLoES_7JZ+0OxeGtAGGReHNFLSOFaPU@mail.gmail.com>	<4D34AD52.20704@structuremonitoring.com>	<6441154A9FF1CD4386AF4ABF141A056D2150F03C@WMEXOSCD2-N2.bocad.bank-banque-canada.ca>	<4D34BF78.7040301@structuremonitoring.com>	<AANLkTi=c961At6WL16g1kBmPgzpfGcPGabWdPG2=bhP9@mail.gmail.com>	<4D34D807.4020004@structuremonitoring.com>
	<AANLkTim=ZhYg-X-cvQX=W25c3nY3v5AtmjBFA5Ec8F8+@mail.gmail.com>
Message-ID: <4D356200.6060004@units.it>

On 01/18/2011 01:13 AM, Dominick Samperi wrote:
> On Mon, Jan 17, 2011 at 7:00 PM, Spencer Graves<
> spencer.graves at structuremonitoring.com>  wrote:
>
>> Hi, Dominick, et al.:
>>
>>
>>       Demanding complete unit test suites with all software contributed to
>> CRAN would likely cut contributions by a factor of 10 or 100.  For me, the R
>> package creation process is close to perfection in providing a standard
>> process for documentation with places for examples and test suites of
>> various kinds.  I mention "perfection", because it makes developing
>> "trustworthy software" (Chamber's "prime directive") relatively easy without
>> forcing people to do things they don't feel comfortable doing.
>>
>
> I don't think I made myself clear, sorry. I was not suggesting that package
> developers include a complete unit
> test suite. I was suggesting that unit testing should be done outside of the
> CRAN release process. Packages
> should be submitted for "release" to CRAN after they have been tested (the
> responsibility of the package
> developers). I understand that the main problem here is that package
> developers do not have access to
> all supported platforms, so the current process is not likely to change.

Regarding access to all platforms: But there's r-forge where building and checks 
are done nightly for Linux, Win, and Mac (though for some months now the check 
protocols are not available for 32 bit Linux and Windows - but I hope they'll be 
back soon).
I found it extremely easy to get an account & project space and building.
Many thanks to r-forge!

complete unit test suites:
To me, it seems nicer and better to favour packages that do it than mechanical 
enforcement. E.g. show icons that announce if a package comes with vignette, 
test suite (code coverage), and etc.

My 2 ct,

Claudia


>
> Dominick
>
>
>>
>>       If you need more confidence in the software you use, you can build
>> your own test suites -- maybe in packages you write yourself -- or pay
>> someone else to develop test suites to your specifications.  For example,
>> Revolution Analytics offers "Package validation, development and support".
>>
>>
>>        Spencer
>>
>>
>>
>> On 1/17/2011 3:27 PM, Dominick Samperi wrote:
>>
>>> On Mon, Jan 17, 2011 at 5:15 PM, Spencer Graves<
>>> spencer.graves at structuremonitoring.com>   wrote:
>>>
>>>   Hi, Paul:
>>>>
>>>>
>>>>       The "Writing R Extensions" manual says that *.R code in a "tests"
>>>> directory is run during "R CMD check".  I suspect that many R programmers
>>>> do
>>>> this routinely.  I probably should do that also.  However, for me, it's
>>>> simpler to have everything in the "examples" section of *.Rd files.  I
>>>> think
>>>> the examples with independently developed answers provides useful
>>>> documentation.
>>>>
>>>>   This is a unit test function, and I think it would be better if there
>>> was a
>>> way to unit test packages *before* they
>>> are released to CRAN. Otherwise, this is not really a "release," it is
>>> test
>>> or "beta" version. This is currently
>>> possible under Windows using http://win-builder.r-project.org/, for
>>> example.
>>>
>>> My earlier remark about the release process was more about documentation
>>> than about unit testing, more
>>> about the gentle "nudging" that the R release process does to help insure
>>> consistent documentation and
>>> organization, and about how this nudging might be extended to the C/C++
>>> part
>>> of a package.
>>>
>>> Dominick
>>>
>>>
>>>        Spencer
>>>>
>>>>
>>>>
>>>> On 1/17/2011 1:52 PM, Paul Gilbert wrote:
>>>>
>>>>   Spencer
>>>>>
>>>>> Would it not be easier to include this kind of test in a small file in
>>>>> the
>>>>> tests/ directory?
>>>>>
>>>>> Paul
>>>>>
>>>>> -----Original Message-----
>>>>> From: r-devel-bounces at r-project.org [mailto:
>>>>> r-devel-bounces at r-project.org]
>>>>> On Behalf Of Spencer Graves
>>>>> Sent: January 17, 2011 3:58 PM
>>>>> To: Dominick Samperi
>>>>> Cc: Patrick Leyshock; r-devel at r-project.org; Dirk Eddelbuettel
>>>>> Subject: Re: [Rd] R vs. C
>>>>>
>>>>>
>>>>>         For me, a major strength of R is the package development
>>>>> process.  I've found this so valuable that I created a Wikipedia entry
>>>>> by that name and made additions to a Wikipedia entry on "software
>>>>> repository", noting that this process encourages good software
>>>>> development practices that I have not seen standardized for other
>>>>> languages.  I encourage people to review this material and make
>>>>> additions or corrections as they like (or sent me suggestions for me to
>>>>> make appropriate changes).
>>>>>
>>>>>
>>>>>         While R has other capabilities for unit and regression testing, I
>>>>> often include unit tests in the "examples" section of documentation
>>>>> files.  To keep from cluttering the examples with unnecessary material,
>>>>> I often include something like the following:
>>>>>
>>>>>
>>>>> A1<- myfunc() # to test myfunc
>>>>>
>>>>> A0<- ("manual generation of the correct  answer for A1")
>>>>>
>>>>> \dontshow{stopifnot(} # so the user doesn't see "stopifnot("
>>>>> all.equal(A1, A0) # compare myfunc output with the correct answer
>>>>> \dontshow{)} # close paren on "stopifnot(".
>>>>>
>>>>>
>>>>>         This may not be as good in some ways as a full suite of unit
>>>>> tests, which could be provided separately.  However, this has the
>>>>> distinct advantage of including unit tests with the documentation in a
>>>>> way that should help users understand "myfunc".  (Unit tests too
>>>>> detailed to show users could be completely enclosed in "\dontshow".
>>>>>
>>>>>
>>>>>         Spencer
>>>>>
>>>>>
>>>>> On 1/17/2011 11:38 AM, Dominick Samperi wrote:
>>>>>
>>>>>   On Mon, Jan 17, 2011 at 2:08 PM, Spencer Graves<
>>>>>> spencer.graves at structuremonitoring.com>     wrote:
>>>>>>
>>>>>>         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
>>>>>>>>
>>>>>>>>
>>>>>>>>   This makes sense, but I have seem some very transparent algorithms
>>>>>>>>
>>>>>>> turned
>>>>>> into vectorized R code
>>>>>> that is difficult to read (and thus to maintain or to change). These
>>>>>> chunks
>>>>>> of optimized R code are like
>>>>>> embedded assembly, in the sense that nobody is likely to want to mess
>>>>>> with
>>>>>> it. This could be addressed
>>>>>> by including pseudo code for the original (more transparent) algorithm
>>>>>> as
>>>>>> a
>>>>>> comment, but I have never
>>>>>> seen this done in practice (perhaps it could be enforced by R CMD
>>>>>> check?!).
>>>>>>
>>>>>> On the other hand, in principle a well-documented piece of C/C++ code
>>>>>> could
>>>>>> be much easier to understand,
>>>>>> without paying a performance penalty...but "coders" are not likely to
>>>>>> place
>>>>>> this high on their
>>>>>> list of priorities.
>>>>>>
>>>>>> The bottom like is that R is an adaptor ("glue") language like Lisp
>>>>>> that
>>>>>> makes it easy to mix and
>>>>>> match functions (using classes and generic functions), many of which
>>>>>> are
>>>>>> written in C (or C++
>>>>>> or Fortran) for performance reasons. Like any object-based system there
>>>>>> can
>>>>>> be a lot of
>>>>>> object copying, and like any functional programming system, there can
>>>>>> be
>>>>>> a
>>>>>> lot of function
>>>>>> calls, resulting in poor performance for some applications.
>>>>>>
>>>>>> If you can vectorize your R code then you have effectively found a way
>>>>>> to
>>>>>> benefit from
>>>>>> somebody else's C code, thus saving yourself some time. For operations
>>>>>> other
>>>>>> than pure
>>>>>> vector calculations you will have to do the C/C++ programming yourself
>>>>>> (or
>>>>>> call a library
>>>>>> that somebody else has written).
>>>>>>
>>>>>> Dominick
>>>>>>
>>>>>>
>>>>>>
>>>>>>   ----- Original Message ----
>>>>>>
>>>>>>> From: Dirk Eddelbuettel<edd at debian.org>
>>>>>>>> To: Patrick Leyshock<ngkbr8es at gmail.com>
>>>>>>>> Cc: r-devel at 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
>>>>>>>>
>>>>>>>>   ______________________________________________
>>>>>>>>
>>>>>>> R-devel at r-project.org mailing list
>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>>>>>
>>>>>>>   ______________________________________________
>>>>>>
>>>>> R-devel at r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>>>
>>>>>
>>>>> ====================================================================================
>>>>>
>>>>> La version fran?aise suit le texte anglais.
>>>>>
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------------
>>>>>
>>>>> This email may contain privileged and/or confidential information, and
>>>>> the
>>>>> Bank of
>>>>> Canada does not waive any related rights. Any distribution, use, or
>>>>> copying of this
>>>>> email or the information it contains by other than the intended
>>>>> recipient
>>>>> is
>>>>> unauthorized. If you received this email in error please delete it
>>>>> immediately from
>>>>> your system and notify the sender promptly by email that you have done
>>>>> so.
>>>>>
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------------
>>>>>
>>>>> Le pr?sent courriel peut contenir de l'information privil?gi?e ou
>>>>> confidentielle.
>>>>> La Banque du Canada ne renonce pas aux droits qui s'y rapportent. Toute
>>>>> diffusion,
>>>>> utilisation ou copie de ce courriel ou des renseignements qu'il contient
>>>>> par une
>>>>> personne autre que le ou les destinataires d?sign?s est interdite. Si
>>>>> vous
>>>>> recevez
>>>>> ce courriel par erreur, veuillez le supprimer imm?diatement et envoyer
>>>>> sans d?lai ?
>>>>> l'exp?diteur un message ?lectronique pour l'aviser que vous avez ?limin?
>>>>> de votre
>>>>> ordinateur toute copie du courriel re?u.
>>>>>
>>>>
>
> 	[[alternative HTML version deleted]]
>
>
>
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel


-- 
Claudia Beleites
Dipartimento dei Materiali e delle Risorse Naturali
Universit? degli Studi di Trieste
Via Alfonso Valerio 6/a
I-34127 Trieste

phone: +39 0 40 5 58-37 68
email: cbeleites at units.it



[Rd] R vs. C now rather: how to ease package checking
Claudia Beleites