Thank you very much for the reply Henrik, you gave great pointers for me to look at.
I am now curious about R.cache (although I am not sure it will help in my case, I'll need to look at it further). Also, I was debating if to use R-help or R-devel for this, since I was not sure from the description text <http://www.r-project.org/mail.html>if it is intended for developing R (as in "R base"), or R package development in general (well, now I know). With regards, Tal ----------------Contact Details:------------------------------------------------------- Contact me: tal.gal...@gmail.com | Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com (English) ---------------------------------------------------------------------------------------------- On Wed, Apr 9, 2014 at 7:41 PM, Henrik Bengtsson <h...@biostat.ucsf.edu>wrote: > [Sounds like a question for R-devel] > > On Wed, Apr 9, 2014 at 5:02 AM, Tal Galili <tal.gal...@gmail.com> wrote: > > Hello all, > > > > > > I wish to add to the > > installr<http://cran.r-project.org/web/packages/installr/>package the > > ability to check for new versions of R once every X units of > > time (maybe once every two weeks). > > > > I would like to keep a time stamp somewhere, that would stay persistent > > across R sessions (i.e.: that if I turn R off and then back on, it would > > keep track of the last time it checked for a new R version). > > It would be best if I could save some file, maybe in the installr package > > folder, that would keep track of that. > > > > Any suggestions or "best practice" on how to implement something like > that? > > I'm not aware of any standards for where to store site- and/or > user-specific R settings that are persistent across session. It would > certainly nice to have a standard, instead of everyone inventing their > own. > > Either way, before starting it is useful (even if you don't distribute > via CRAN) if you're aware of the following passage from > http://cran.r-project.org/web/packages/policies.html provides a fair > guideline: > > "- Packages should not write in the usersâ home filespace, nor > anywhere else on the file system apart from the R sessionâs temporary > directory (or during installation in the location pointed to by > TMPDIR: and such usage should be cleaned up). Installing into the > systemâs R installation (e.g., scripts to its bin directory) is not > allowed. > Limited exceptions may be allowed in interactive sessions if the > package obtains confirmation from the user." > > Then have a look the R.cache package. It is used for caching objects > to file, e.g. memoization of computational expensive results. It > addresses the above policy in the following way: > > 1. It checks whether ~/.Rcache/ exists or not. If it exists, it is > assumed that it already has the user's permission. > > 2 Otherwise, if in an interactive R session, it asks the user for > permission to create that directory. If successful it is created (and > it drops an informative README.txt file in there too), otherwise it > uses a temporary directory. > > Here is what it looks like to first time you load R.cache: > > > library(R.cache) > The R.cache package needs to create a directory that will hold cache > files. It is convenient to use one in the user's home directory, > because it remains also after restarting R. Do you wish to create the > '~/.Rcache/' directory? If not, a temporary directory > (C:\Users\hb\AppData\Local\Temp\Rtmp61upx7/.Rcache) that is specific > to this R session will be used. [Y/n]: > > You can use a similar strategy. You could also use R.cache for you > own purposes, e.g. > > readURL <- function(url, maxAge=10*24*3600, force=FALSE, ...) { > library("R.cache") > dirs <- "installr" # => Caching to ~/.Rcache/installr/ > key <- list(method="readURL", url=url) > > # Check for cached results > bfr <- loadCache(key=key, dirs=dirs) > when <- attr(bfr, "when") > > # Recent enough results already available? > if (!force && !is.null(when) && (Sys.time()-maxAge <= when)) > return(bfr); > > # Download and memoize > bfr <- readLines(url) > attr(bfr, "when") <- Sys.time() > saveCache(bfr, key=key, dirs=dirs) > > bfr > } # readURL() > > That would memoize the results from CRAN (for 10 days by default); you > can of course cache the parsed R version etc, but I leave that to you. > > /Henrik > (author of R.cache) > > > > > Thanks, > > Tal > > > > > > > > > > > > ----------------Contact > > Details:------------------------------------------------------- > > Contact me: tal.gal...@gmail.com | > > Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | > > www.r-statistics.com (English) > > > ---------------------------------------------------------------------------------------------- > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > 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. > [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list 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.
