R devel - Feb 2022 - model.weights and model.offset: request for adjustment

The model.weights() and model.offset() functions from the 'stats' 
package index possibly-missing elements of a data frame via $, e.g.

x$"(offset)"
x$"(weights)"

This returns NULL without comment when x is a data frame:

x <- data.frame(a=1)
x$"(offset)"  ## NULL
x$"(weights)"  ## NULL

However, when x is a tibble we get a warning as well:

x <- tibble::as_tibble(x)
x$"(offset)"
## NULL
## Warning message:
## Unknown or uninitialised column: `(offset)`.

    I know it's not R-core's responsibility to manage forward 
compatibility with tibbles, but in this case [[-indexing would seem to 
be better practice in any case.

   Might a patch be accepted ... ?

   cheers
    Ben Bolker

>>>>> Ben Bolker 
>>>>>     on Tue, 1 Feb 2022 21:21:46 -0500 writes:
    > The model.weights() and model.offset() functions from the
'stats'
    > package index possibly-missing elements of a data frame via $, e.g.

    > x$"(offset)"
    > x$"(weights)"

    > This returns NULL without comment when x is a data frame:

    > x <- data.frame(a=1)
    > x$"(offset)"  ## NULL
    > x$"(weights)"  ## NULL

    > However, when x is a tibble we get a warning as well:

    > x <- tibble::as_tibble(x)
    > x$"(offset)"
    > ## NULL
    > ## Warning message:
    > ## Unknown or uninitialised column: `(offset)`.

    > I know it's not R-core's responsibility to manage forward 
    > compatibility with tibbles, but in this case [[-indexing would seem to 
    > be better practice in any case.

Yes, I would agree:  we should use  [[ instead of $ here
in order to force exact matching just as principle

Importantly, because  also  mf[["(weights)"]]
will return  NULL without a warning for a model/data frame, and
it seems it does so also for tibbles.

    > Might a patch be accepted ... ?

That would not be necessary.

There's one remaining problem however:
`$` access is clearly faster than `[[` for small data frames
(because `$` is a primitive function doing everything in C, 
 whereas `[[` calls the R level data frame method ).

Faster in both cases, i.e., when there *is* a column and when there
is none (and NULL is returned), e.g., for the first case
> system.time(for(i in 1:20000) df[["a"]])
   user  system elapsed 
  0.064   0.000   0.065 
> system.time(for(i in 1:20000) df$a)
   user  system elapsed 
  0.009   0.000   0.009 

So that's probably been the reason why  `$`  has been prefered?


Martin

    > cheers
    > Ben Bolker