I hadn't thought of that tradeoff. After testing just now, if you have a column named `.data` or `.env` those constructs work as if there was no such column, and actually in that case `mutate(df, b = .data + 1)` is an error.

Personally I'll happily take not being able to use those as column names if it means I can avoid always typing : before every in-data variable, but your comment gave me a better understanding of why it would be bad for some other person or scenario, perhaps where short term ease-of-use is lower on the list of priorities.

For your second example, it doesn't come up in R because a data frame column cannot be a function. Columns must be vectors (including lists) and you could have a vector where one or all elements are functions, but the column itself cannot not be a function (functions are not vectors), so there's no ambiguity there. To call a function stored in your data frame you'd have to access an element of the column, and any access method, e.g. `[[` or `$` would make the resulting set of characters invalid as the name of an object (without backticks, which would then disambiguate the intent)

    df <- tibble(x = list(function(x) x + 1))
    df %>% 
      mutate(y = x[[1]](3))

Separate from dplyr, in R when you use `(` to call a function it searches only for functions by that name.

    log <- 3
    log(1)
    # 0

    frog <- 3
    frog(3)
    # Error in frog(3) : could not find function "frog"
    
    log <- function(x) x^2
    log(1)
    # 1