In poissonconsulting/checkr: Check the Properties of Common R Objects

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checkr

checkr has been superseded by the chk package.

checkr is a light-weight R package of expressive, assertive, pipe-friendly functions to check the properties of common R objects.

In the case of failure the functions, which are designed to be used in scripts and packages, issue informative error messages.

For an overview of the functions see the checkr-naming vignette and for a comparison with similar packages see the assertive-programming vignette.

Demonstration

The following code demonstrates the check_data() function

library(checkr)

# the starwars data frame in the dplyr package fails many of these checks
check_data(dplyr::starwars, values = list(
  height = c(66L, 264L),
  name = "",
  mass = c(20,1358, NA),
  hair_color = c("blond", "brown", "black", NA),
  gender = c("male", "female", "hermaphrodite", "none", NA)), 
    order = TRUE, nrow = c(81, 84), key = "hair_color", error = FALSE)

Syntax

checkr uses objects to check the values of other objects using an elegant and expressive syntax.

Class

To check the class simply pass an object of the desired class.

y <- c(2,1,0,1,NA)
check_vector(y, values = numeric(0))
check_vector(y, values = integer(0))

Missing Values

To check that a vector does not include missing values pass a single non-missing value (of the correct class).

check_vector(y, 1)

To allow it to include missing values include a missing value.

check_vector(y, c(1, NA))

And to check that it only includes missing values only pass a missing value (of the correct class)

check_vector(y, NA_real_)

Range

To check the range of a vector pass two non-missing values (as well as the missing value if required).

check_vector(y, c(0, 2, NA))
check_vector(y, c(-1, -10, NA))

Specific Values

To check the vector only includes specific values pass three or more non-missing values or set only = TRUE.

check_vector(y, c(0, 1, 2, NA))
check_vector(y, c(1, 1, 2, NA))
check_vector(y, c(1, 2, NA), only = TRUE)

Naming Objects

By default, the name of an object is determined from the function call.

check_vector(list(x = 1))

This simplifies things but results in less informative error messages when used in a pipe.

library(magrittr)
y %>% check_list()

The argument x_name can be used to override the name.

y %>% check_list(x_name = "y")

Scalars

The four wrapper functions check_lgl(), check_int(), check_dbl() and check_str() check whether an object is an attribute-less non-missing scalar logical (flag), integer, double (number) or character (string). They are really useful for checking the types of arguments in functions

fun <- function(x) { check_lgl(x)}
fun(x = NA)
fun(x = TRUE)
fun(x = 1)

Additional scalar wrappers are check_date() and check_dttm() for scalar Date and POSIXct objects. Alternatively you can roll your own using the more general check_scalar() function.

Installation

To install the latest development version from r-universe.

install.packages("checkr", repos = c("https://poissonconsulting.r-universe.dev", "https://cloud.r-project.org"))

To install the latest development version from GitHub

# install.packages("pak", repos = sprintf("https://r-lib.github.io/p/pak/stable/%s/%s/%s", .Platform$pkgType, R.Version()$os, R.Version()$arch))
pak::pak("poissonconsulting/checkr")

Citation

citation(package = "checkr")

Contribution

Please report any issues.

Pull requests are always welcome.

Code of Conduct

Please note that the checkr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms

poissonconsulting/checkr documentation built on Oct. 18, 2023, 9:39 p.m.