The `R`

package `wrapr`

supplies a few neat new coding notations.

An Abacus, which gives us the term “calculus.”

The first notation is an operator called the “named map builder”. This is a cute notation that essentially does the job of `stats::setNames()`

. It allows for code such as the following:

library("wrapr") names <- c('a', 'b') names := c('x', 'y') #> a b #> "x" "y"

This can be *very* useful when programming in `R`

, as it allows indirection or abstraction on the left-hand side of inline name assignments (unlike `c(a = 'x', b = 'y')`

, where all left-hand-sides are concrete values even if not quoted).

A nifty property of the named map builder is it commutes (in the sense of algebra or category theory) with `R`

‘s “`c()`

” combine/concatenate function. That is: `c('a' := 'x', 'b' := 'y')`

is the same as `c('a', 'b') := c('x', 'y')`

. Roughly this means the two operations play well with each other.

The second notation is an operator called “anonymous function builder“. For technical reasons we use the same “`:=`

” notation for this (and, as is common in `R`

, pick the correct behavior based on runtime types).

The function construction is written as: “`variables := { code }`

” (the braces are required) and the semantics are roughly the same as “`function(variables) { code }`

“. This is derived from some of the work of Konrad Rudolph who noted that most functional languages have a more concise “lambda syntax” than “function(){}” (please see here and here for some details, and be aware the `wrapr`

notation is not as concise as is possible).

This notation allows us to write the squares of `1`

through `4`

as:

sapply(1:4, x:={x^2})

instead of writing:

sapply(1:4, function(x) x^2)

It is only a few characters of savings, but being able to choose notation can be a big deal. A real victory would be able to directly use lambda-calculus notation such as “`(λx.x^2)`

“. We are also experimenting with the following additional notation:

sapply(1:4, λ(x, x^2))

Edit 2017-08-24: the above functions (including `λ`

), have all been moved from `seplyr`

to `wrapr`

and released on CRAN!

Categories: Programming Statistics Tutorials

### jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.

Don’t know what that is, but it is not a usable abacus. Seems to be missing some beads. Ought to have 4 on bottom and one on top in each column.

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I think it is supposed to be a copy of an ancient Roman abacus. Those tended to have untethered markers, so it isn’t too surprising it isn’t configured correctly.

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I have improved the

`λ`

documentation a bit: link.And, the

`lambda(x)(x^2)`

form is pretty useless (same form as`function(x) x^2`

, and without the`R`

-language hooks). Mostly I put it in as a place holder so the`λ(x, x^2)`

form has something to cross-link its help to (to prevent generating a help file with complicated character encoding in the help file name). I’ve also changed its syntax to`lambda(x, x^2)`

to make it closer the`λ(x, x^2)`

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Are you familiar with the magrittr syntactic sugar . %>% … and . %>% { … }?

They supply the same functionality as your lamba example above. The only downside being you cannot pass more than one argument. If you expanded := to support multiple arguments on the LHS, similar to the fat-arrow operator (“=>”) in EMACSscript6, that would be a significant improvement.

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I have used the

`magrittr`

“`. %>% f`

” notation from time to time.The

`wrapr`

function builders can conveniently take multiple arguments:Or even the original formula interface version of arguments:

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Nice to learn about another approach to anonymous functions. You might be interesting in the [nofrills](https://cran.r-project.org/package=nofrills) package. Compared to wrapr, it is far more specialized—it only concerns anonymous functions—but has some noteworthy differences: uses essentially the same syntax as the normal function declaration (but shorter), supports quasiquotation (the README explains why), and includes an operator that enables higher-order functions to interpret an even shorter function syntax (in the GitHub version).

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