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Use vetting expressions to enforce structural requirements for function
arguments. Works just like vet(), except that the formals of the
enclosing function automatically matched to the vetting expressions provided
in ....
vetr(..., .VETR_SETTINGS = NULL)vetting expressions, each will be matched to the enclosing
function formals as with match.call() and will be used to validate the
value of the matching formal.
a settings list as produced by vetr_settings(), or
NULL to use the default settings. Note that this means you cannot use
vetr with a function that takes a .VETR_SETTINGS argument
TRUE if validation succeeds, otherwise stop with error message
detailing nature of failure.
Vetting expressions can be template tokens, standard tokens, or any
combination of template and standard tokens combined with && and/or
||. Template tokens are R objects that define the required structure,
much like the FUN.VALUE argument to vapply(). Standard tokens are tokens
that contain the . symbol and are used to vet values.
See vignette('vetr', package='vetr') and examples for details on how
to craft vetting expressions.
vet(), in particular example(vet).
# NOT RUN {
fun1 <- function(x, y) {
vetr(integer(), LGL.1)
TRUE # do some work
}
fun1(1:10, TRUE)
try(fun1(1:10, 1:10))
## only vet the second argument
fun2 <- function(x, y) {
vetr(y=LGL.1)
TRUE # do some work
}
try(fun2(letters, 1:10))
## Nested templates; note, in packages you should consider
## defining templates outside of `vet` or `vetr` so that
## they are computed on load rather that at runtime
tpl <- list(numeric(1L), matrix(integer(), 3))
val.1 <- list(runif(1), rbind(1:10, 1:10, 1:10))
val.2 <- list(runif(1), cbind(1:10, 1:10, 1:10))
fun3 <- function(x, y) {
vetr(x=tpl, y=tpl && ncol(.[[2]]) == ncol(x[[2]]))
TRUE # do some work
}
fun3(val.1, val.1)
try(fun3(val.1, val.2))
val.1.a <- val.1
val.1.a[[2]] <- val.1.a[[2]][, 1:8]
try(fun3(val.1, val.1.a))
# }
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