[R-pkg-devel] Absent variables and tibble

Duncan Murdoch murdoch.duncan at gmail.com
Mon Jun 27 16:03:35 CEST 2016

On 27/06/2016 9:22 AM, Lenth, Russell V wrote:
> My package 'lsmeans' is now suddenly broken because of a new provision in the 'tibble' package (loaded by 'dplyr' 0.5.0), whereby the "[[" and "$" methods for 'tbl_df' objects - as documented - throw an error if a variable is not found.
> The problem is that my code uses tests like this:
> 	if (is.null (x$var)) {...}
> to see whether 'x' has a variable 'var'. Obviously, I can work around this using
> 	if (!("var" %in% names(x))) {...}
> but (a) I like the first version better, in terms of the code being understandable; and (b) isn't there a long history whereby we can expect a NULL result when accessing an absent member of a list (and hence a data.frame)? (c) the code base for 'lsmeans' has about 50 instances of such tests.
> Anyway, I wonder if a lot of other package developers test for absent variables in that first way; if so, they too are in for a rude awakening if their users provide a tbl_df instead of a data.frame. And what is considered the best practice for testing absence of a list member? Apparently, not either of the above; and because of (c), I want to do these many tedious corrections only once.
> Thanks for any light you can shed.

This is why CRAN asks that people test reverse dependencies.

I think the most defensive thing you can do is to write a small function

name_missing <- function(x, name)
     !(name %in% names(x))

and use name_missing(x, "var") in your tests.  (Pick your own name to 
make your code understandable if you don't like my choice.)

You could suggest to the tibble maintainers that they add a function 
like this.

Duncan Murdoch

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