R S3 Classes

How it works

S3 dispatch selects methods from an object’s class. Adding a class attribute alone does not validate the object’s fields. This small constructor checks parallel room labels and known visit totals, then provides a print method. It intentionally cannot represent an unknown total; the reporting project uses an explicit data-frame coverage contract instead.

Run this R example

These examples run locally with R, not PHP, Python or JavaScript. The reviewed baseline is R 4.5.2 on Windows x64/UCRT, using only packages shipped with R. This is a tested version, not a newest-release claim. Install your own R from the official R project; an IDE is optional. Save the complete source as s3-classes.R in a separate learning folder and run Rscript --vanilla s3-classes.R. Keep code and fictional fixtures separate from a real project.

Bhylu has no R browser runner. There is no Try in playground link because the existing Python and JavaScript editors do not execute R. No package installation, account, network dataset, Apache, MySQL or PHP setting is needed to run these base-R sources.

The complete download uses a local scope, restores its temporary options and treats unexpected warnings as errors. Examples that handle an expected warning do so narrowly. Random examples change only their R process’s RNG state. File examples own their temporary output; figure examples leave their named PNG in the current learning folder and refuse to overwrite it. Use a new empty folder to rerun a figure.

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Example

local({
  previous_options <- options(warn = 2, digits = 8, stringsAsFactors = FALSE)
  on.exit(options(previous_options), add = TRUE)
  check_counts <- function(x, allow_missing = FALSE, allow_empty = FALSE) {
    if (!(is.integer(x) || is.double(x)) || is.object(x) || !is.null(dim(x))) {
      stop("Use a plain numeric vector")
    }
    if (length(x) > 256L || (!allow_empty && length(x) == 0L)) {
      stop("Use 1..256 counts unless empty input is explicitly allowed")
    }
    if (any(is.nan(x)) || (!allow_missing && anyNA(x))) {
      stop("Missing or undefined counts are not allowed here")
    }
    observed <- x[!is.na(x)]
    if (any(!is.finite(observed)) || any(observed < 0) ||
        any(observed > 1000000) || any(observed != floor(observed))) {
      stop("Counts must be finite whole numbers from 0 to 1000000")
    }
    invisible(x)
  }

  new_room_report <- function(rooms, totals) {
    check_counts(totals, allow_empty = TRUE)
    if (!is.character(rooms) || anyNA(rooms) ||
        any(!nzchar(trimws(rooms))) || anyDuplicated(rooms) ||
        length(rooms) != length(totals)) {
      stop("Use one unique non-empty room name per total")
    }
    structure(list(room = rooms, total = as.numeric(totals)), class = "room_report")
  }

  print.room_report <- function(x, ...) {
    cat("rooms:", length(x$room), "total visits:", sum(x$total), "\n")
    invisible(x)
  }

  report <- new_room_report(c("East", "West"), c(18, 26))
  print(report)
  invisible(NULL)
})

check_counts <- function(x, allow_missing = FALSE, allow_empty = FALSE) {
  if (!(is.integer(x) || is.double(x)) || is.object(x) || !is.null(dim(x))) {
    stop("Use a plain numeric vector")
  }
  if (length(x) > 256L || (!allow_empty && length(x) == 0L)) {
    stop("Use 1..256 counts unless empty input is explicitly allowed")
  }
  if (any(is.nan(x)) || (!allow_missing && anyNA(x))) {
    stop("Missing or undefined counts are not allowed here")
  }
  observed <- x[!is.na(x)]
  if (any(!is.finite(observed)) || any(observed < 0) ||
      any(observed > 1000000) || any(observed != floor(observed))) {
    stop("Counts must be finite whole numbers from 0 to 1000000")
  }
  invisible(x)
}

new_room_report <- function(rooms, totals) {
  check_counts(totals, allow_empty = TRUE)
  if (!is.character(rooms) || anyNA(rooms) ||
      any(!nzchar(trimws(rooms))) || anyDuplicated(rooms) ||
      length(rooms) != length(totals)) {
    stop("Use one unique non-empty room name per total")
  }
  structure(list(room = rooms, total = as.numeric(totals)), class = "room_report")
}

print.room_report <- function(x, ...) {
  cat("rooms:", length(x$room), "total visits:", sum(x$total), "\n")
  invisible(x)
}

report <- new_room_report(c("East", "West"), c(18, 26))
print(report)

Expected result

rooms: 2 total visits: 44

The validator accepts an explicitly empty report but rejects duplicated room names, negative totals, wrong shapes and missing totals. The method controls display and returns the object invisibly for normal R composition. This is one small S3 example, not a complete object-oriented framework.