util_expect_scalar: check, if a scalar/vector function argument matches...

In dataquieR: Data Quality in Epidemiological Research

check, if a scalar/vector function argument matches expectations

Description

check, if a scalar/vector function argument matches expectations

Usage

util_expect_scalar(
  arg_name,
  allow_more_than_one = FALSE,
  allow_null = FALSE,
  allow_na = FALSE,
  min_length = -Inf,
  max_length = Inf,
  check_type,
  convert_if_possible,
  conversion_may_replace_NA = FALSE,
  dont_assign = FALSE,
  error_message
)

Arguments

arg_name	the argument
allow_more_than_one	allow vectors
allow_null	allow NULL
allow_na	allow NAs
min_length	minimum length of the argument's value
max_length	maximum length of the argument's value
check_type	a predicate function, that must return TRUE on the argument's value.
convert_if_possible	if given, a lambda can be given similar to check_type This lambda would be used to try a conversion. If a conversion fails (returns NA, where the input was not ‘util_empty’), an error is still thrown, the data is converted, otherwise
conversion_may_replace_NA	if set to TRUE, we can define a function in convert_if_possible that replaces NA values without causing a warning, but this option is set to FALSE by default to catch possible conversion problems (use it with caution).
dont_assign	set TRUE to keep x in the caller environment untouched
error_message	if check_type() returned FALSE, show this instead of a default error message.

Value

the value of arg_name – but this is updated in the calling frame anyway.

See Also

Other robustness_functions: util_as_valid_missing_codes(), util_check_one_unique_value(), util_correct_variable_use(), util_empty(), util_ensure_character(), util_ensure_in(), util_ensure_suggested(), util_fix_rstudio_bugs(), util_is_integer(), util_is_numeric_in(), util_is_valid_missing_codes(), util_match_arg(), util_observations_in_subgroups(), util_only_NAs(), util_stop_if_not(), util_warn_unordered()

Examples

## Not run: 
f <- function(x) {
  util_expect_scalar(x, check_type = is.integer)
}
f(42L)
try(f(42))
g <- function(x) {
  util_expect_scalar(x, check_type = is.integer, convert_if_possible =
          as.integer)
}
g(42L)
g(42)

## End(Not run)

dataquieR documentation built on May 29, 2024, 7:18 a.m.