Difference between applying a function() to list() and to new.env()?-CodePudding

Why do I get two different results if I print x$val? I get that the first one is a list and the second is an environment, but I do not understand what makes the result of x$val from the second chunk = NA

x <- list()
x$val <- 1
myfun <- function(x) {x$val <- x$val   NA} 
myfun(x)

x <- new.env()
x$val <- 18
myfun <- function(x) {x$val <- x$val   NA} 
myfun(x)

CodePudding user response：

Environments are "reference objects" in R. That means that if you assign one to a new variable, changes to either copy will affect both copies. Lists are like most other objects and get copied on assignment.

So in your first example, myfun(x) makes a separate copy of the list x, and works on that in the function. It has no effect on the global variable x.

In your second example, myfun(x) makes a new reference to the environment x, and works on that in the function. That affects the original variable as well.

CodePudding user response：

Ok, based on the legit comment of the risk of using <<- some examples.

risky solution

x <- list("val" = 1L)
myfun <- function(x) {x$val <<- x$val   NA} 
myfun(x)
x
# $val
# [1] NA

risky solution going terribly wrong

x <- list("val" = "Please do not alter me at all")
y <- list("val" = 1L)
myfun <- function(x) {x$val <<- x$val   NA} 
myfun(y)
x
# $val
# [1] NA
y
# $val
# [1] 1