[R] Lazy loading of CSV file

Jeff Newmiller jdnewmil at dcn.davis.CA.us
Wed Apr 16 15:39:17 CEST 2014


The standard way to put data into a package is to convert it to RDA as described in the Writing R Extensions document. This is faster and more compact than CSV.
---------------------------------------------------------------------------
Jeff Newmiller                        The     .....       .....  Go Live...
DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.       ##.#.  Live Go...
                                      Live:   OO#.. Dead: OO#..  Playing
Research Engineer (Solar/Batteries            O.O#.       #.O#.  with
/Software/Embedded Controllers)               .OO#.       .OO#.  rocks...1k
--------------------------------------------------------------------------- 
Sent from my phone. Please excuse my brevity.

On April 16, 2014 5:10:03 AM PDT, Luca Cerone <luca.cerone at gmail.com> wrote:
>Hi, in a package I am developing some functions need to use some
>external
>data.
>I have these data as a set of .csv files that I have placed in the
>inst/extdata folder.
>
>At the moment I have a file "db-internal.r" where I  load all the
>internal
>databases that could be used by the functions in my package;
>and assign them to some global (to the package) variables (all with the
>prefix db_ in front of them)
>For example (I didn't come out with a better name, sorry)
>
>db_italian_cities = read.csv(system.file("extdata/italian_cities.csv")
>
>like this I can use db_italian_cities in my functions.
>
>Some of these datasets are quite big and really slow down loading the
>package, plus for some of the task the package is meant to solve they
>might
>not even be required.
>I would like to be able to lazyload these datasets only when needed,
>how
>can I possibly achieve this without creating special databases?
>
>Some of them could change, so I intend to be able to download the most
>recent ones through a function that ensure the package is using the
>most
>recent version,
>so I would really prefer to simply use csv files.
>
>Thanks a lot in advance for the help!
>
>Cheers,
>Luca
>
>	[[alternative HTML version deleted]]
>
>______________________________________________
>R-help at 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.




More information about the R-help mailing list