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Avoiding Lazy Evaluation in a Function that Appends an Element to Each of Its Vector Arguments
In R, it's possible to define functions that accept a variable number of arguments using the ... syntax. However, this can lead to lazy evaluation, where the arguments are not evaluated until they are used. This can cause problems if you want to perform operations on the arguments before they are passed to another function.
Consider the following function, which appends the number 8 to each of its vector arguments:
append8 <- function(p1, p2, p3, ...) {
Args <- as.list(match.call())[-1]
l <- lapply(Args, eval)
lapply(l, c, 8)
}
This function uses the match.call() function to extract the arguments passed to the function. The as.list() function is then used to convert the arguments to a list, and the lapply() function is used to apply the eval() function to each element of the list. This forces the evaluation of the arguments, ensuring that they are converted to vectors before they are passed to the c() function.
However, there is a better way to achieve the same result without using eval(). The list() function can be used to collect the arguments into a list, and the lapply() function can be used to apply the c() function to each element of the list. This approach is more efficient and does not require the use of eval().
append8 <- function(...) {
args <- list(...)
lapply(args, c, 8)
}
This function will work as expected, even if the arguments are not vectors. For example, the following code will append the number 8 to each element of the list c(1, 2, 3):
append8(c(1, 2, 3))
The output of this code will be:
[[1]]
[1] 1 2 3 8
Using this approach, you can avoid lazy evaluation and ensure that the arguments are evaluated before they are passed to the c() function.