# [How to] Write a purrr-like adverb

**Colin Fay**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Create your own `safely`

, `compose`

and friends!

## What is an adverb

If you read carefully the purrr documentation, you’ll find this simple explanation :

Adverbs modify the action of a function; taking a function as input and returning a function with modified action as output.

In other words, adverbs take a function, and return this function modified. Yes, just as an adverb modifies a verb. So if you do :

library(purrr) safe_log <- safely(log)

The returned object is another function that you can use just as a regular one.

class(safe_log) ## [1] "function" safe_log("a") ## $result ## NULL ## ## $error ## <simpleError in log(x = x, base = base): argument non numérique pour une fonction mathématique>

In computer science, these adverbs are what is called “high-order functions”.

## How to write your own?

I’ve been playing with adverbs in {attempt}, notably through these adverbs :

library(attempt) # Silently only return the errors, and nothing if the function succeeds silent_log <- silently(log) silent_log(1) # Surely make a function always work, without stopping the process sure_log <- surely(log) sure_log(1) ## [1] 0 sure_log("a") # with_message and with_warning as_num_msg <- with_message(as.numeric, msg = "We're performing a numeric conversion") as_num_warn <- with_warning(as.numeric, msg = "We're performing a numeric conversion") as_num_msg("1") ## We're performing a numeric conversion ## [1] 1 as_num_warn("1") ## Warning in as_num_warn("1"): We're performing a numeric conversion ## [1] 1

So, how to implement this kind of behavior? Let’s take a simple example with `sleepy`

, also shared on Twitter.

sleepy <- function(fun, sleep){ function(...){ Sys.sleep(sleep) fun(...) } } sleep_print <- sleepy(Sys.time, 5) class(sleep_print) ## [1] "function" # Let's try Sys.time() ## [1] "2018-04-19 10:20:58 CEST" sleep_print() ## [1] "2018-04-19 10:21:03 CEST"

Let’s decompose what we’ve got here.

First of all, the function should return another function, so we need to start with :

talky <- function(){ function(){ } }

What this function will take as a first argument is another function, that will be executed when our future new function is called.

So let’s do this:

talky <- function(fun){ function(){ fun() } }

Because you know, with R referential transparency, you can create a variable that is a function:

plop <- mean plop(1:10) ## [1] 5.5

This simple skeleton will work if we take a function without any args:

sys_time <- talky(Sys.time) sys_time() ## [1] "2018-04-19 10:21:03 CEST"

But hey, this is not what we want: we need this new function to be able to take arguments. So let’s use our friend `...`

.

talky <- function(fun){ function(...){ fun(...) } }

Now, our new adverb creates a function that can take arguments. But as you’ve notice, this is still not really an adverb: we need to **modify** something. Now you’re only limited by your imagination 😉

# Print the time talky <- function(fun){ function(...){ print(Sys.time()) fun(...) } } talky_sqrt <- talky(sqrt) talky_sqrt(10) ## [1] "2018-04-19 10:21:03 CEST" ## [1] 3.162278 # Or with a kind message ? talky <- function(fun, mess){ function(...){ message(mess) fun(...) } } talky_sqrt<- talky(fun = sqrt, mess = "Hey there! You Rock!") talky_sqrt(1) ## Hey there! You Rock! ## [1] 1 # Run it or not ? maybe <- function(fun){ function(...){ num <- sample(1:100, 1) if (num > 50) { fun(...) } } } maybe_sqrt <- maybe(fun = sqrt) maybe_sqrt(1) maybe_sqrt(1) ## [1] 1 maybe_sqrt(1) ## [1] 1 # Create a log file of a function log_calls <- function(fun, file){ function(...){ write(as.character(Sys.time()), file, append = TRUE, sep = "\n") fun(...) } } log_sqrt <- log_calls(sqrt, file = "logs") log_sqrt(10) ## [1] 3.162278 log_sqrt(13) ## [1] 3.605551 readLines("logs") ## [1] "2018-04-19 10:21:03" "2018-04-19 10:21:03"

**leave a comment**for the author, please follow the link and comment on their blog:

**Colin Fay**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.