Add compatibility with dplyr programming data masking

[Daveyr]

With dplyr verbs it is possible to redirect environment variables as data variables, for instance:

var_summary <- function(data, var) {
  data %>%
    summarise(n = n(), min = min({{ var }}), max = max({{ var }}))
}

It would be very helpful if tidyjson verbs could do the same, e.g.

jsonDF <- function(data, object){
  data %>%
    enter_object({{object}}) %>%
    spread_all()
}

[ramiromagno]

I second this.

[colearendt]

PR that implements this is up! Please give it a try and LMK if any issues! #132

[ramiromagno]

Thank you for your lightning response!

Just a question: in your PR you use rlang::quo, should it not be rlang::enquo?

Suggestion: perhaps add a test too with the embrace operator (as opposed to having only the !!! operator).

[colearendt]

I thought I did add a test with the embrace operator? Also, I think quos vs. enquos is the choice, and I don’t think enquos is needed (isn’t it for names?). I have to admit that I often forget the distinctions haha - you might be right. I’ll take a look later!

…

Sent from my iPhone On Jan 2, 2021, at 11:10 AM, Ramiro Magno <notifications@github.com> wrote:  Thank you for your lightning response! Just a question: in your PR you use rlang::quo, should it not be rlang::enquo? Suggestion: perhaps add a test too with the embrace operator (as opposed to having only the !!! operator). — You are receiving this because you commented. Reply to this email directly, view it on GitHub<#129 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AFQBVVSXUF2JTYFVQ3AMCFDSX5ARFANCNFSM4PDR7GWA>.