Perform interface checks on dataframe inputs using enclosing function formal parameter definitions

ivalidate(...) is intended to be used within a function to check the validity of a data frame parameter (usually the first parameter) against an ispec which is given as a default value of a formal parameter.

Usage

ivalidate(df = NULL, ..., .imap = imapper(), .prune = FALSE, .default = NULL)

Arguments

df: a dataframe - if missing then the first parameter of the calling function is assumed to be a dataframe.
...: not used but ivalidate should be included in call to inherit .imap from the caller function.
.imap: a set of mappings as an imapper object.
.prune: get rid of excess columns that are not in the spec.
.default: a default dataframe conforming to the specification. This overrides any defaults defined in the interface specification

Value

a dataframe based on df with validity checks passed and .imap

mappings applied if present

Examples

x = function(df = iface(col1 = integer ~ "an integer column" ), ...) {
  df = ivalidate(...)
  return(df)
}
input=tibble::tibble(col1 = c(1,2,3))
x(input)
#> # A tibble: 3 × 1
#>    col1
#>   <int>
#> 1     1
#> 2     2
#> 3     3

# This fails because col1 is not coercable to integer
input2=tibble::tibble(col1 = c(1.5,2,3))
try(x(input2))
#> Error : input column `col1` in function parameter `x(df = ?)` cannot be coerced to a integer: not a true integer input