How to Create Robust Argument Checking in R Functions

Create a function that checks the arguments of another function
R programming
Best practices
Author

R.Andres Castaneda

Published

March 25, 2025

Intro

When developing functions in R, it’s essential to ensure that inputs meet specific criteria. One common and effective practice is creating an auxiliary function dedicated exclusively to validating arguments passed to another function. This approach helps to maintain clean, readable, and robust code.

Why Create a Separate Argument Checking Function?

Separating argument checking from your primary function logic provides several benefits:

  • Code readability: Separating validation logic keeps your main functions concise and easy to understand.
  • Reusability: Validation logic can often be reused across multiple functions.
  • Maintainability: Updating validation rules in one place is simpler and reduces the risk of inconsistencies.

How It Works

Here’s a straightforward and effective way to implement argument checking using an auxiliary function.

Practical Example

Below is an example demonstrating how one function (goo()) can validate the arguments of another function (foo()):

foo <- function(x, y = 2, z = "a", ...) {
  # Capture explicitly defined arguments
  args <- as.list(environment())

  # Capture additional arguments from ...
  args <- c(args, list(...))

  # Pass args list to goo
  goo(args)
}

# Argument checking function
goo <- function(args) {
  # Expand arguments directly into goo's environment
  list2env(args, envir = environment())

  # Perform validation
  stopifnot(
    is.numeric(x),
    is.numeric(y),
    is.character(z)
  )

  # Additional checks for extra arguments in ...
  if (exists("w")) {
    stopifnot(is.logical(w))
  }

  cat("All checks passed!\n")
}

How Does This Work?

Let’s break down the logic:

  1. Capture arguments: The primary function (foo()) captures explicitly defined arguments and the additional arguments passed via the ellipsis (...) into a list.

  2. Pass arguments for checking: The argument list (args) is passed to the auxiliary checking function (goo()).

  3. Expand and validate arguments: Inside goo(), we expand this list of arguments into its own environment using list2env(). This allows direct reference by their original names.

  4. Argument checks: We perform validation checks using stopifnot() to ensure each argument meets our criteria.

Examples of Usage

Let’s demonstrate with some examples:

# Example: correct arguments
foo(x = 1, y = 3, z = "test") # passes validation

# Example: extra argument 'w' correctly specified as logical
foo(x = 1, w = TRUE) # passes validation

# Example: incorrect 'x' argument type
foo(x = "wrong") # triggers error, x is not numeric
Error in goo(args): is.numeric(x) is not TRUE
# Example: incorrect additional argument 'w'
foo(x = 1, w = "wrong") # triggers error, w is not logical
Error in goo(args): is.logical(w) is not TRUE

Benefits and Best Practices

  • Always clearly define your argument types and validations.
  • Centralize your argument checking logic for consistency.
  • Consider reusing or extending your argument checking function (goo()) for similar functions.

Adopting this pattern greatly enhances your R programming practice by ensuring robustness, clarity, and efficiency.