assertthat

迈不过友情╰ 2022-07-16 06:23 130阅读 0赞

assertthat provides a drop in replacement for `stopifnot()` that makes it easy to check the pre- and post-conditions of a function, while producing useful error messages.

x <- 1:10
    stopifnot(is.character(x))
    # Error: is.character(x) is not TRUE
    
    assert_that(is.character(x))
    # Error: x is not a character vector
    
    assert_that(length(x) == 5)
    # Error: length(x) not equal to 5
    
    assert_that(is.numeric(x))
    # [1] TRUE

This is a good defensive programming technique, and is useful as source-code documentation: you can see exactly what your function expects when you come back to it in the future. It is partly a response to the lack of static typing in R, but it allow you to test for general conditions (like `length(x) == length(y)`) that are difficult to express in a type system.

`assertthat` can be installed either from CRAN:

install.packages('assertthat')

or with devtools:

devtools::install_github("hadley/assertthat")

## New assertions ##

As well as all the functions provided by R, assertthat provides a few more that I use a lot:

*  `is.flag(x)`: is x `TRUE` or `FALSE`? (a boolean flag)
 *  `is.string(x)`: is x a length 1 character vector?
 *  `has_name(x, nm)`, `x %has_name% nm`: does `x` have component `nm`?
 *  `has_attr(x, attr)`, `x %has_attr% attr`: does `x` have attribute `attr`?
 *  `is.count(x)`: is x a single positive integer?
 *  `are_equal(x, y)`: are `x` and `y` equal?
 *  `not_empty(x)`: are all dimensions of `x` greater than 0?
 *  `noNA(x)`: is `x` free from missing values?
 *  `is.dir(path)`: is `path` a directory?
 *  `is.writeable(path)`/`is.readable(path)`: is `path` writeable/readable?
 *  `has_extension(path, extension)`: does `file` have given `extension`?

## `assert_that`, `see_if` and `validate_that` ##

There are three main functions in assertthat:

*  `assert_that()` signal an error
 *  `see_if()` returns a logical value, with the error message as an attribute.
 *  `validate_that()` returns `TRUE` on success, otherwise returns the error as a string.

You'll use `assert_that()` in your own code, but you'll mostly see `see_if()` in the examples (because `R CMD check`requires that examples run without errors). Use `validate_that()` for S4 validate methods.

## Writing your own assertions ##

If you're writing your own assertions, you can provide custom error messages using the `on_failure()` helper:

is_odd <- function(x) {
      assert_that(is.numeric(x), length(x) == 1)
      x %% 2 == 1
    }
    assert_that(is_odd(2))
    # Error: is_odd(x = 2) is not TRUE
    
    on_failure(is_odd) <- function(call, env) {
      paste0(deparse(call$x), " is even")
    }
    assert_that(is_odd(2))
    # Error: 2 is even

The `on_failure` callback is called with two arguments, the unevaluated function `call` (which has already been standardised with `match.call()`), and `env`, and the environment in which the assertion was executed. This allows you to choose between displaying values or names in your error messages. Read the [advanced R book][] to learn more about working with calls.

Also note the use of `assert_that()` in our new function: assertions flow through function calls ensuring that you get a useful error message at the top level:

assert_that(is_odd("b"))
    # Error: x is not a numeric or integer vector
    assert_that(is_odd(1:2))
    # Error: length(x) not equal to 1

[advanced R book]: http://adv-r.had.co.nz/Expressions.html