[roenxi]

Function syntax is this stuff [0, 1]. Tidyverse uses it to accomplish some non-model stuff. The one that leaps to my mind is faceting [2]. I'd expect that sort of thing to be handled by macros.

And all the rest of the comment I wouldn't have typed except I'm already replying, since I know this is one of those two-types-of-people-who-don't-change-opinions situations. But...

> not only saves a few keystrokes.

R is secretly a lisp. People can define whatever they want to be whatever they want. Pipes were already implemented in a library (try doing that in Python). Make your own library or bind \ to a keyboard macro or something if your fingers are on the point of crumbling under the stress of those 7 keystrokes.

Defaults using real words to describe things is good. The function to create a function being function() is eminently reasonable. \() is meaningless and about as useful as a one-word variable

> It will also produce shorter, and clearer, lines of code.

Opinons very much divide. Code length is only a proxy for load on a reader's short term memory which is what matters. \ is going to put more burden on someone if they aren't very familiar with R. Most R coders are not full time programmers and not very good at R.

[0] https://www.rdocumentation.org/packages/base/versions/3.6.2/... [1] https://www.rdocumentation.org/packages/stats/versions/3.6.2... [2] http://www.cookbook-r.com/Graphs/Facets_(ggplot2)/

[kgwgk]

I know what formulas are, I just don’t see what’s the connection with the proposed change:

     ‘\(x) x + 1’ is parsed as ‘function(x) x + 1’

I also know that R has some vestigial scheme under the hood, but the syntax is not lisp (it was taken from S). In common lisp one could easily use a macro or reader macro but in R a change in the parser is needed so “\” can be used instead of “function”.

Note that the existing “f <- function(...) ...” syntax is not being removed. But I write a lot of code like

    state.range <- apply(state.x77, 2, function(x) c(min(x), median(x), max(x)))

and it will be an improvement to be able to condense it a bit to

    state.range <- apply(state.x77, 2, \(x) c(min(x), median(x), max(x)))