[R] Making objects global in a package

R. Mark Sharp rm@h@rp @end|ng |rom me@com
Sat Jul 14 03:13:23 CEST 2018


I would usually use a function for this. It may not be more R like, but it is more readable to me. If you want, to keep the columns in a file, you could have the function initialize itself on the first call. 

Mark
R. Mark Sharp, Ph.D.
Data Scientist and Biomedical Statistical Consultant
7526 Meadow Green St.
San Antonio, TX 78251
mobile: 210-218-2868
rmsharp using me.com











> On Jul 13, 2018, at 7:51 PM, Michael Hannon <jmhannon.ucdavis using gmail.com> wrote:
> 
> Greetings.  I'm putting together a small package in which I use
> `dplyr::read_csv()` to read CSV files from several different sources.  I do
> this in several different files, but with various kinds of subsequent
> processing, depending on the file.
> 
> I find it useful to specify column types, as the apparent data type of a given
> column sometimes changes unexpectedly deep into the file.  I.e., a field that
> consistently looks like an integer, suddenly becomes a fraction:
> 
>    1, 1, ..., 1, 1/2, 1, ...
> 
> Hence, the column type has to be treated as a character, rather than as an
> integer (with the possibility of later conversion to double, if necessary).
> (This is just an example.)
> 
> Therefore I use the `col_types` argument in all of the calls to `read_csv()`.
> 
> These calls are spread over several files, but I want the keep all of the
> column types in a single place, yet have them available in each of the several
> files.  This is just for the sake of maintainability.
> 
> At the moment I do this by putting the column-type definitions into a single,
> file:
> 
>    000_define_data_attributes.R
> 
> that:
> 
>    (1) is named so that it's parsed first by `devtools::build()`
>    (2) sets up an environment and stuffs the column types into it:
> 
>            data_env <- new.env(parent=emptyenv())
>            data_env$col_types_alpha <- list(
>                Date = col_date(),
>                var1 = col_double(),
>                ...
>            )
> 
> There are a few other things that go into the file as well.
> 
> Then I pick off the appropriate stuff from the environment in the other files:
> 
>    foo_alpha <- read_csv("alpha.csv", col_types = data_env$col_types_alpha)
> 
> This seems to work, but it doesn't "feel" right to me.  (If this were Python,
> people would accuse me of being "non-pythonic").
> 
> Hence, I'm seeking suggestions for the best practice for this kind of thing.
> 
> BTW, I note that both the sources of data ("alpha", etc.) and the column types
> are more or less guaranteed to be static for the foreseeable future.  Hence,
> there really isn't much danger in just replicating the column-type definitions
> in each of the various files, which would obviate the need for the "000..."
> file.  In other words, this is mostly a style thing.
> 
> Thanks for any advice you can provide.
> 
> -- Mike
> 
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