should base R have a piping operator ?
How is your argument different to, say, "Should dplyr or data.table be part of base R as they are the most popular data science packages and they are used by a large number of users?" Kind regards
On Sat, Oct 5, 2019 at 4:34 PM Ant F <antoine.fabri at gmail.com> wrote:
Dear R-devel,
The most popular piping operator sits in the package `magrittr` and is used
by a huge amount of users, and imported /reexported by more and more
packages too.
Many workflows don't even make much sense without pipes nowadays, so the
examples in the doc will use pipes, as do the README, vignettes etc. I
believe base R could have a piping operator so packages can use a pipe in
their code or doc and stay dependency free.
I don't suggest an operator based on complex heuristics, instead I suggest
a very simple and fast one (>10 times than magrittr in my tests) :
`%.%` <- function (e1, e2) {
eval(substitute(e2), envir = list(. = e1), enclos = parent.frame())
}
iris %.% head(.) %.% dim(.)
#> [1] 6 5
The difference with magrittr is that the dots must all be explicit (which
sits with the choice of the name), and that special magrittr features such
as assignment in place and building functions with `. %>% head() %>% dim()`
are not supported.
Edge cases are not surprising:
```
x <- "a"
x %.% quote(.)
#> .
x %.% substitute(.)
#> [1] "a"
f1 <- function(y) function() eval(quote(y))
f2 <- x %.% f1(.)
f2()
#> [1] "a"
```
Looking forward for your thoughts on this,
Antoine
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