Re: [Rd] difficulties with setMethod([ and ...
Tony Plate tpl...@acm.org
on Mon, 17 May 2010 20:51:12 -0600 writes:
Jim, yes, I have dealt with that particular challenge that list(...)
throws an error for a call like f(x,,,) where the empty args match to a
... formal argument. Here's some fragments of code that I used to cope
with this:
# to find the empty anon args, must work with the unevaluated dot args
dot.args.uneval - match.call(expand.dots=FALSE)$...
if (length(dot.args.uneval))
missing.dot.args - sapply(dot.args.uneval, function(arg)
is.symbol(arg) as.character(arg)==)
else
missing.dot.args - logical(0)
...
# Now we can work with evaluated dot args.
# Can't do dot.args - list(...) because that will
# stop with an error for missing args.
dot.args - mapply(dot.args.uneval, missing.dot.args,
FUN=function(arg, m) if (!m) eval(arg) else NULL)
I don't have much time at the moment, to delve into Jim's code,
nor to analyze what exactly Tony's does.
Some notes however which I deem important:
1) My experiece in writing many S4 methods for [ -- with the
Matrix package, but also for 'Rmpfr' -- is that you
really need to work with nargs()
rather than with things like length(list(...))
2) If you really want to be compatible to the very rich
semantics of S and R subsetting, you need to spend more time
than you anticipate.
- negative subscripts, names, logicals
- A[i] for an array A where i can be a vector and then the
array is treated as if it had no dim() attribute
- A[i] for an array A where i is a *matrix* with k columns
where k - length(dim(A)) --- (k = 2 for matrices)
- A[]
Are you sure you would not try to use
setClass('myExample', contains = array, representation = ...)
rather than your
setClass('myExample', representation(x = array, ...))
?
You would get all the [ (and other array methods) for free,
and would only need to specify those methods where 'myExample'
really differed from array-subsetting.
3) Lots of well-testedsetMethod([, ) examples
are in the sources of the Matrix package.
There, BTW, I found it useful to use
## for 'i' in x[i] or A[i,] : (numeric = {double, integer})
setClassUnion(index, members = c(numeric, logical, character))
and then, e.g., a simple example method ..
setMethod([, signature(x = denseMatrix, i = index, j = missing,
drop = logical),
function (x, i, j, ..., drop) {
if((na - nargs()) == 3)
r - as(x, matrix)[i, drop=drop]
else if(na == 4)
r - as(x, matrix)[i, , drop=drop]
else stop(invalid nargs()= ,na)
if(is.null(dim(r))) r else as(r, geClass(x))
})
The examples in the Rmpfr package are much less and simpler.
To find the methods, for both, use
fgrep 'setMethod([' R/*R
if you are on a decent OS and in side the package source directory.
--
Martin Maechler, ETH Zurich
Let me know if you need any further explanation.
Several warnings:
* I was using this code with S3 generics and methods.
* There are quite possibly better ways of detecting empty unevaluated
arguments than 'is.symbol(arg) as.character(arg)=='.
* You'll probably want to be careful that the eval() in the last line is
using the appropriate environment for your application.
I didn't read your code in detail, so apologies if the above is
off-the-point, but your verbal description of the problem and the coding
style and comments in the [ method for myExample triggered my memory.
-- Tony Plate
On 05/17/2010 07:48 PM, James Bullard wrote:
Apologies if I am not understanding something about how things are being
handled when using S4 methods, but I have been unable to find an answer
to
my problem for some time now.
Briefly, I am associating the generic '[' with a class which I wrote
(here: myExample). The underlying back-end allows me to read contiguous
slabs, e.g., 1:10, but not c(1, 10). I want to shield the user from this
infelicity, so I grab the slab and then subset in memory. The main
problem
is with datasets with dim(.) 2. In this case, the '...' argument
doesn't
seem to be in a reasonable state. When it is indeed missing then it
properly reports that fact, however, when it is not missing it reports
that it is not missing, but then the call to: list(...) throws an
argument
is missing exception.
I cannot imagine that this has not occurred before, so I am expecting
someone might be able to point me to some example code. I have attached
some code demonstrating my general problem ((A) and (B) below) as well as
the outline of the sub-selection code. I have to say that coding this has
proven non-trivial and
[Rd] BIC() in stats {was [R-sig-ME] how to extract the BIC value}
MM == Martin Maechler maech...@stat.math.ethz.ch
on Tue, 18 May 2010 12:37:21 +0200 writes:
GaGr == Gabor Grothendieck ggrothendi...@gmail.com
on Mon, 17 May 2010 09:45:00 -0400 writes:
GaGr BIC seems like something that would logically go into stats in the
GaGr core of R, as AIC is already, and then various packages could define
GaGr methods for it.
MM Well, if you look at help(AIC):
Usage:
AIC(object, ..., k = 2)
Arguments:
object: a fitted model object, for which there exists a ‘logLik’
method to extract the corresponding log-likelihood, or an
object inheriting from class ‘logLik’.
...: optionally more fitted model objects.
k: numeric, the _penalty_ per parameter to be used; the default
‘k = 2’ is the classical AIC.
MM you may note that the original authors of AIC where always
MM allowing the AIC() function (and its methods) to compute the BIC,
MM simply by using 'k = log(n)' where of course n must be correct.
MM I do like the concept that BIC is just a variation of AIC and
MM AFAIK, AIC was really first (historically).
MM Typically (and with lme4), the 'n' needed is already part of the
logLik()
MM attributes :
AIC((ll - logLik(fm1)), k = log(attr(ll,nobs)))
MM REML
MM 1774.786
MM indeed gives the BIC (where the REML name may or may not be a
MM bit overkill)
MM A stats-package based BIC function could then simply be defined as
BIC - function (object, ...) UseMethod(BIC)
BIC.default - function (object, ...) BIC(logLik(object), ...)
BIC.logLik - function (object, ...)
AIC(object, ..., k = log(attr(object,nobs)))
{well, modulo the fact that ... should really allow to do
this for *several* models simultaneously}
In addition to that (and more replying to Doug Bates):
Given nlme's tradition of explicitly providing BIC(), and in
analogue to the S3 semantics of the AIC() methods,
- I think lme4 (and lme4a on R-forge) should end up having
working AIC() and BIC() directly for fitted models, instead of
having to use
AIC(logLik(.)) andBIC(logLik(.))
The reason that even the first of this currently does *not*
work is that lme4 imports AIC from stats but should do so
from stats4.
-- I'm about to change that for 'lme4' (and 'lme4a').
However, for the BIC case, ... see below
- I tend to agree with Gabor (for once! :-) that
basic BIC methods (S3, alas) should move from nlme to stats.
For this reason, I'm breaking the rule of do not cross-post
for once, and am hereby diverting this thread to R-devel
Martin
MM --
MM Martin Maechler, ETH Zurich
GaGr On Mon, May 17, 2010 at 9:29 AM, Douglas Bates ba...@stat.wisc.edu
wrote:
On Mon, May 17, 2010 at 5:54 AM, Andy Fugard (Work)
andy.fug...@sbg.ac.at wrote:
Greetings,
Assuming you're using lmer, here's an example which does what you need:
(fm1 - lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
Linear mixed model fit by REML
Formula: Reaction ~ Days + (Days | Subject)
Data: sleepstudy
AIC BIC logLik deviance REMLdev
1756 1775 -871.8 1752 1744
Random effects:
Groups Name Variance Std.Dev. Corr
Subject (Intercept) 612.092 24.7405
Days 35.072 5.9221 0.066
Residual 654.941 25.5918
Number of obs: 180, groups: Subject, 18
Fixed effects:
Estimate Std. Error t value
(Intercept) 251.405 6.825 36.84
Days 10.467 1.546 6.77
Correlation of Fixed Effects:
(Intr)
Days -0.138
(fm1fit - summary(fm1)@AICtab)
AIC BIC logLik deviance REMLdev
1755.628 1774.786 -871.8141 1751.986 1743.628
fm1fit$BIC
[1] 1774.786
That's one way of doing it but it relies on a particular
representation of the object returned by summary, and that is subject
to change.
I had thought that it would work to use
BIC(logLik(fm1))
but that doesn't because the BIC function is imported from the nlme
package but not later exported. The situation is rather tricky - at
one point I defined a generic for BIC in the lme4 package but that led
to conflicts when multiple packages defined different versions. The
order in which the packages were loaded became important in
determining which version was used.
We agreed to use the generic from the nlme package, which is what is
now done. However, I don't want to make the entire nlme package
visible when you have loaded lme4 because of resulting conflicts.
I can get the result as
(fm1 - lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
Linear mixed model fit by REML
Formula: Reaction ~ Days + (Days | Subject)
Data:
Re: [Rd] 00LOCK and nfs
This is a follow-up to an old thread with kind of solution to the 00LOCK problem on NFS. I have made a patch to install.packages to accept a new argument locktype = c(lock, no-lock, pkglock) which is passed to R CMD INSTALL. This addition might have independent interest aside from the NFS problem, as it exposes functionality from R CMD INSTALL to install.packages and the very convenient update.packages. Patches are at http://www.biostat.jhsph.edu/~khansen/packages2.R-patch http://www.biostat.jhsph.edu/~khansen/install.packages.Rd-patch (patches to files in the utils package) and both R-devel (R version 2.12.0 Under development (unstable) (2010-05-17 r52025)) and R-2.11 (R version 2.11.0 Patched (2010-05-17 r52025)) passed make check-all with these two patches applied. I thought about adding a note describing my findings below to the details section, but decided against it. Regarding the 00LOCK problem. In my testing, using the patches above and setting locktype = pkglock, makes it possible to deal with the NFS problem. Specifically, I have not been able to make update.packages() fail midway, due to a un-removable 00LOCK file (which is not too surprising, as I now have a per-package lock). However, sometimes (but far less frequently than before), a 00LOCK-pkgname directory remains after update/install.packages. Sometimes this 00LOCK-pkgname directory does not contain any .nfs* files (!?) and sometimes it does. For this reason, I still precede any install/update.packages with a check for the existence of a 00LOCK-pkgname directory and an attempt to remove it. The difference between using locktype = pkglock and not is specifically that without, it was possible for update.packages to fail midway even though there were no 00LOCK* files at the start of the update process. Originally I hypothesized that the presence of the .nfs* files in the 00LOCK directory had to do with synchronization issues between the file server and the compute node. In order to approach this I tried to insert a system(sleep 10) at the beginning of do_cleanup in tools/R/install.R but that did not work. Since the pkglock approach described above seems to solve this issue for me, I have not pursued the synchronization issue further. Kasper __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] BIC() in stats {was [R-sig-ME] how to extract the BIC value}
Adding to my own statements (below) :
MM == Martin Maechler maech...@stat.math.ethz.ch
on Tue, 18 May 2010 13:05:27 +0200 writes:
MM == Martin Maechler maech...@stat.math.ethz.ch
on Tue, 18 May 2010 12:37:21 +0200 writes:
GaGr == Gabor Grothendieck ggrothendi...@gmail.com
on Mon, 17 May 2010 09:45:00 -0400 writes:
GaGr BIC seems like something that would logically go into stats in the
GaGr core of R, as AIC is already, and then various packages could define
GaGr methods for it.
MM Well, if you look at help(AIC):
Usage:
AIC(object, ..., k = 2)
Arguments:
object: a fitted model object, for which there exists a ‘logLik’
method to extract the corresponding log-likelihood, or an
object inheriting from class ‘logLik’.
...: optionally more fitted model objects.
k: numeric, the _penalty_ per parameter to be used; the default
‘k = 2’ is the classical AIC.
MM you may note that the original authors of AIC where always
MM allowing the AIC() function (and its methods) to compute the BIC,
MM simply by using 'k = log(n)' where of course n must be correct.
MM I do like the concept that BIC is just a variation of AIC and
MM AFAIK, AIC was really first (historically).
MM Typically (and with lme4), the 'n' needed is already part of the
logLik()
MM attributes :
AIC((ll - logLik(fm1)), k = log(attr(ll,nobs)))
MM REML
MM 1774.786
MM indeed gives the BIC (where the REML name may or may not be a
MM bit overkill)
MM A stats-package based BIC function could then simply be defined as
BIC - function (object, ...) UseMethod(BIC)
BIC.default - function (object, ...) BIC(logLik(object), ...)
BIC.logLik - function (object, ...)
AIC(object, ..., k = log(attr(object,nobs)))
MM {well, modulo the fact that ... should really allow to do
MM this for *several* models simultaneously}
MM In addition to that (and more replying to Doug Bates):
MM Given nlme's tradition of explicitly providing BIC(), and in
MM analogue to the S3 semantics of the AIC() methods,
MM - I think lme4 (and lme4a on R-forge) should end up having
MM working AIC() and BIC() directly for fitted models, instead of
MM having to use
MM AIC(logLik(.)) andBIC(logLik(.))
MM The reason that even the first of this currently does *not*
MM work is that lme4 imports AIC from stats but should do so
MM from stats4.
MM -- I'm about to change that for 'lme4' (and 'lme4a').
MM However, for the BIC case, ... see below
MM - I tend to agree with Gabor (for once! :-) that
MM basic BIC methods (S3, alas) should move from nlme to stats.
MM For this reason, I'm breaking the rule of do not cross-post
MM for once, and am hereby diverting this thread to R-devel
What I *did* find is that the stats4 package has already had
all necessary BIC methods -- S4, not S3.
So for lme4 (and R-forge's lme4a),
I've only needed to change the NAMESPACE file to have both
importFrom(stats4, AIC, BIC, logLik)# so S4 methods are used!
and later
export(AIC, BIC,
.)
and also add 'stats4' to the 'Imports: ' line in DESCRIPTION.
So both (development versions of) lme4 and lme4a now have
working AIC() and BIC(),
and I guess Doug could release a new version of lme4 (not ..a)
pretty soon.
I got private e-mail suggestions for extensive S3 methods for
AIC, BIC and logLik.
I think these should happen more in public (i.e. here, on
R-devel), and while I still advocate that a BIC S3 generic +
simple default methods should be added (as above),
I'd be happy if others joined into the discussion,
(and possibly provided simple patches).
Martin Maechler, ETH Zurich
GaGr On Mon, May 17, 2010 at 9:29 AM, Douglas Bates ba...@stat.wisc.edu
wrote:
On Mon, May 17, 2010 at 5:54 AM, Andy Fugard (Work)
andy.fug...@sbg.ac.at wrote:
Greetings,
Assuming you're using lmer, here's an example which does what you
need:
(fm1 - lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
Linear mixed model fit by REML
Formula: Reaction ~ Days + (Days | Subject)
Data: sleepstudy
AIC BIC logLik deviance REMLdev
1756 1775 -871.8 1752 1744
Random effects:
Groups Name Variance Std.Dev. Corr
Subject (Intercept) 612.092 24.7405
Days 35.072 5.9221 0.066
Residual 654.941 25.5918
Number of obs: 180, groups: Subject, 18
Fixed effects:
Estimate Std. Error t value
(Intercept) 251.405 6.825 36.84
Days 10.467 1.546 6.77
Correlation of Fixed Effects:
(Intr)
Days -0.138
(fm1fit - summary(fm1)@AICtab)
AIC BIC logLik deviance REMLdev
1755.628 1774.786 -871.8141 1751.986 1743.628
fm1fit$BIC
Re: [Rd] difficulties with setMethod([ and ...
On Tue, 18 May 2010 10:22:03 +0200, Martin Maechler
maech...@stat.math.ethz.ch wrote:
Tony Plate tpl...@acm.org
on Mon, 17 May 2010 20:51:12 -0600 writes:
Jim, yes, I have dealt with that particular challenge that
list(...)
throws an error for a call like f(x,,,) where the empty args match
to a
... formal argument. Here's some fragments of code that I used
to
cope
with this:
# to find the empty anon args, must work with the unevaluated dot
args
dot.args.uneval - match.call(expand.dots=FALSE)$...
if (length(dot.args.uneval))
missing.dot.args - sapply(dot.args.uneval, function(arg)
is.symbol(arg) as.character(arg)==)
else
missing.dot.args - logical(0)
...
# Now we can work with evaluated dot args.
# Can't do dot.args - list(...) because that will
# stop with an error for missing args.
dot.args - mapply(dot.args.uneval, missing.dot.args,
FUN=function(arg, m) if (!m) eval(arg) else NULL)
I don't have much time at the moment, to delve into Jim's code,
nor to analyze what exactly Tony's does.
Some notes however which I deem important:
1) My experiece in writing many S4 methods for [ -- with the
Matrix package, but also for 'Rmpfr' -- is that you
really need to work with nargs()
rather than with things like length(list(...))
2) If you really want to be compatible to the very rich
semantics of S and R subsetting, you need to spend more time
than you anticipate.
- negative subscripts, names, logicals
- A[i] for an array A where i can be a vector and then the
array is treated as if it had no dim() attribute
- A[i] for an array A where i is a *matrix* with k columns
where k - length(dim(A)) --- (k = 2 for matrices)
- A[]
I might not get all of the way, but random access and logical subsetting
seem very doable.
Are you sure you would not try to use
setClass('myExample', contains = array, representation = ...)
rather than your
setClass('myExample', representation(x = array, ...))
?
You would get all the [ (and other array methods) for free,
and would only need to specify those methods where 'myExample'
really differed from array-subsetting.
My example is completely contrived. My back end are hdf5 files and so the
'[' method calls C functions, which at the moment grab contiguous blocks.
3) Lots of well-testedsetMethod([, ) examples
are in the sources of the Matrix package.
There, BTW, I found it useful to use
## for 'i' in x[i] or A[i,] : (numeric = {double, integer})
setClassUnion(index, members = c(numeric, logical,
character))
and then, e.g., a simple example method ..
setMethod([, signature(x = denseMatrix, i = index, j =
missing,
drop = logical),
function (x, i, j, ..., drop) {
if((na - nargs()) == 3)
r - as(x, matrix)[i, drop=drop]
else if(na == 4)
r - as(x, matrix)[i, , drop=drop]
else stop(invalid nargs()= ,na)
if(is.null(dim(r))) r else as(r, geClass(x))
})
The examples in the Rmpfr package are much less and simpler.
To find the methods, for both, use
fgrep 'setMethod([' R/*R
if you are on a decent OS and in side the package source directory.
Thanks, I had briefly scanned the matrix package - and the pointer to
nargs is extremely helpful.
thanks again, jim
--
Martin Maechler, ETH Zurich
Let me know if you need any further explanation.
Several warnings:
* I was using this code with S3 generics and methods.
* There are quite possibly better ways of detecting empty
unevaluated
arguments than 'is.symbol(arg) as.character(arg)=='.
* You'll probably want to be careful that the eval() in the last
line is
using the appropriate environment for your application.
I didn't read your code in detail, so apologies if the above is
off-the-point, but your verbal description of the problem and the
coding
style and comments in the [ method for myExample triggered my
memory.
-- Tony Plate
On 05/17/2010 07:48 PM, James Bullard wrote:
Apologies if I am not understanding something about how things
are
being
handled when using S4 methods, but I have been unable to find an
answer to
my problem for some time now.
Briefly, I am associating the generic '[' with a class which I
wrote
(here: myExample). The underlying back-end allows me to read
contiguous
slabs, e.g., 1:10, but not c(1, 10). I want to shield the user
from
this
infelicity, so I grab the slab and then subset in memory. The
main
problem
is with datasets with dim(.) 2. In this case, the '...'
argument
Re: [Rd] [R] avoiding reinstall already installed *package*
On Tue, May 18, 2010 at 22:38, William Dunlap wdun...@tibco.com wrote:
-Original Message-
From: r-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org] On Behalf Of Martin Maechler
Sent: Tuesday, May 18, 2010 1:25 PM
To: milton ruser
Cc: r-h...@r-project.org
Subject: Re: [R] avoiding reinstall already installed *package*
On Tue, May 18, 2010 at 18:06, milton ruser
milton.ru...@gmail.com wrote:
Hi Martin,
thanks for your reply, and very thanks for your kind tips
about package
and library
So, I was trying to understand *why* we load packages using
library().
I've started to use and suggest using require(.) instead
{as my efforts to introduce use() or usePackage() *and* deprecating
library() where met with strong opposition}
I hate to get into arguments over function names, but
I would have thought that require(pkg) would throw
an error if the required pkg was not available. It seems
like require() can be used when pkg is not really required
but library(pkg) is easiest when pkg is required to
continue:
{ require(noSuchPackage); functionFromNoSuchPackage() }
Loading required package: noSuchPackage
Error: could not find function functionFromNoSuchPackage
In addition: Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE,
logical.return = TRUE, :
there is no package called 'noSuchPackage'
{ library(noSuchPackage); functionFromNoSuchPackage() }
Error in library(noSuchPackage) :
there is no package called 'noSuchPackage'
Well, both require() and library() pretty soon lead to an error if the
package is not available... but I agree that you'd prefer to get the more
helpful error message immediately rather than belatedly.
If that's an issue, the typical use of require() would be
if(require(...)) {
...
...
} else {
stop(. not available; do this or that )
}
but instead of stop(..) which can provide a context dependent, customized
error message, you can also work around the absence of the package in other
ways.
a usePackage() function would typically use best of library() and
require() ,
maybe not allowing usePackage(MASS)
but requiring usePackage(MASS)
but also working logically e.g. for
mylme - lme4
usePackage(mylme)
i.e. not allowing non-standard evaluation.
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
I suggest that developers killl the problem on its root,
deleting library
function :-)
Good to know already installed packages will not be reinstalled.
cheers
milton
On Tue, May 18, 2010 at 12:49 PM, Martin Maechler
maech...@stat.math.ethz.ch wrote:
{ I've modified the subject; I can't stand it hitting square into
my face ... }
mr == milton ruser milton.ru...@gmail.com
on Tue, 18 May 2010 12:36:23 -0300 writes:
mr Dear R-experts,
mr I am installing new libraries using
mr install.packages(ggplot2,dependencies=T).
mr But I perceive that many dependencies are already
installed. As I
am using
mr a low-band internet, how can avoid reinstall
installed libraries?
There's no problem with installed libraries, as ...
they DO NOT EXIST.
These are *PACKAGES* !
Why do you think are you talking about the function
install.packages()
---
To answer the question you did want to ask:
Do not be afraid: Depedencies are only installed when needed,
i.e., no package will be downloaded and installed if it already
is there.
Martin Maechler, ETH Zurich
mr cheers
mr milton
mr [[alternative HTML version deleted]]
(another thing you should learn to avoid, please)
[[alternative HTML version deleted]]
__
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https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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[Rd] R in sandbox/jail (long question)
Hello, I have a setup similar to Rweb ( http://www.math.montana.edu/Rweb/ ): I get R scripts from users and need to execute them in in a safe manner (they are executed automatically, without human inspection). I would like to limit the user's script to reading from STDIN and writing to STDOUT/ERR. Specifically, preventing any kind of interaction with the underlying operating system (files, sockets, system(), etc.). I've found this old thread: http://r.789695.n4.nabble.com/R-in-a-sandbox-jail-td921991.html But for technical reasons I'd prefer not to setup a chroot jail. I have written a patch that adds a --sandbox parameter. When this parameter is used, the user's script can't create any kind of connection object or run system(). My plan is to run R like this: cat INPUT | R --vanila --slave --sandbox --file SCRIPT.R OUTPUT Where 'INPUT' is my chosen input and 'SCRIPT.R' is the script submitted by the user. If the script tries to create a conncetion or run a disabled function, an error is printed. This is the patch: http://cancan.cshl.edu/labmembers/gordon/files/R_2.11.0_sandbox.patch So my questions are: 1. Would you be willing to consider this feature for inclusion ? 2. Are there any other 'dangerous' functions I need to intercept ( .Internal perhaps ?) All comments and suggestions are welcomed, thanks, -gordon __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] pretty.Date(): new halfmonth time step
Hi R-devel / R-core In the new pretty() methods for Date and POSIXct https://svn.r-project.org/R/trunk/src/library/grDevices/R/prettyDate.R there is currently a pretty time step listed as 15 DSTdays... but this actually doesn't line up well with months. Much better to implement directly what this is trying to do: i.e. to have a halfmonth time step. This is just the union of two monthly sequences, one on the 1st of each month and another on the 15th of each month. With this in place we have: prettyDate(as.Date(c(2002-02-02, 2002-05-01))) # [1] 2002-02-15 2002-03-01 2002-03-15 2002-04-01 2002-04-15 2002-05-01 The proposed patch is attached. Regards -Felix -- Felix Andrews / 安福立 Postdoctoral Fellow Integrated Catchment Assessment and Management (iCAM) Centre Fenner School of Environment and Society [Bldg 48a] The Australian National University Canberra ACT 0200 Australia M: +61 410 400 963 T: + 61 2 6125 4670 E: felix.andr...@anu.edu.au CRICOS Provider No. 00120C -- http://www.neurofractal.org/felix/ __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] R in sandbox/jail (long question)
On 18/05/2010 10:38 PM, Assaf Gordon wrote: Hello, I have a setup similar to Rweb ( http://www.math.montana.edu/Rweb/ ): I get R scripts from users and need to execute them in in a safe manner (they are executed automatically, without human inspection). I would like to limit the user's script to reading from STDIN and writing to STDOUT/ERR. Specifically, preventing any kind of interaction with the underlying operating system (files, sockets, system(), etc.). I've found this old thread: http://r.789695.n4.nabble.com/R-in-a-sandbox-jail-td921991.html But for technical reasons I'd prefer not to setup a chroot jail. I have written a patch that adds a --sandbox parameter. When this parameter is used, the user's script can't create any kind of connection object or run system(). That sounds too restrictive. R uses connections internally in various places, with no reference to the file system. It also uses them when reading its own files. So if you stop a user from creating connections, you'll somehow need to distinguish between user-created ones and internally necessary ones: not easy. My plan is to run R like this: cat INPUT | R --vanila --slave --sandbox --file SCRIPT.R OUTPUT Where 'INPUT' is my chosen input and 'SCRIPT.R' is the script submitted by the user. If the script tries to create a conncetion or run a disabled function, an error is printed. This is the patch: http://cancan.cshl.edu/labmembers/gordon/files/R_2.11.0_sandbox.patch So my questions are: 1. Would you be willing to consider this feature for inclusion ? 2. Are there any other 'dangerous' functions I need to intercept ( .Internal perhaps ?) .Internal is needed by tons of base functions. So again, you'll need to distinguish where the call is coming from, and that's not easy. Duncan Murdoch All comments and suggestions are welcomed, thanks, -gordon __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
