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Validate that a field is a number that is integer-like — sv_integer • shinyvalidate

The sv_integer() function validates that a field is 'integer-like' with the {value} %% 1 == 0 test. Very large values (generally with absolute exponent values greater than 15) won't be validated correctly due to floating point imprecision. By default, only a single, finite, not-missing, valid numbers are allowed, but each of those criteria can be controlled via arguments.

sv_integer(
  message = "An integer is required",
  allow_multiple = FALSE,
  allow_na = FALSE,
  allow_nan = FALSE
)

message

The validation error message to use if a value is not an integer.

allow_multiple

If FALSE (the default), then the length of the input vector must be exactly one; if TRUE, then any length is allowed (including a length of zero; use sv_required() if one or more values should be required).

allow_na, allow_nan

If FALSE (the default for both options), then any NA or NaN element will cause validation to fail.

The sv_numeric() function, which tests whether a field value is simply numeric.

Other rule functions: compose_rules(), sv_between(), sv_email(), sv_equal(), sv_gte(), sv_gt(), sv_in_set(), sv_lte(), sv_lt(), sv_not_equal(), sv_numeric(), sv_optional(), sv_regex(), sv_required(), sv_url()

## Only run examples in interactive R sessions
if (interactive()) {

library(shiny)
library(shinyvalidate)

ui <- fluidPage(
  textInput("count", "Count")
)

server <- function(input, output, session) {
  
  # Validation rules are set in the server, start by
  # making a new instance of an `InputValidator()`
  iv <- InputValidator$new()

  # Basic usage: `sv_integer()` works well with its
  # defaults; a message will be displayed if the
  # validation of `input$count` fails
  iv$add_rule("count", sv_integer())

  # Finally, `enable()` the validation rules
  iv$enable()
}

shinyApp(ui, server)

}

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