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Progress updates for 'purrr' functions

The progressify package allows you to easily add progress reporting to sequential and parallel map-reduce code by piping to the progressify() function. Easy!

TL;DR

library(progressify)
handlers(global = TRUE)
library(purrr)

slow_fcn <- function(x) {
  Sys.sleep(0.1)  # emulate work
  x^2
}

xs <- 1:100
ys <- xs |> map(slow_fcn) |> progressify()

Introduction

This vignette demonstrates how to use this approach to add progress reporting to purrr functions such as map(), map_dbl(), and walk().

The purrr map() function is commonly used to apply a function to the elements of a vector or a list. For example,

library(purrr)
xs <- 1:100
ys <- map(xs, slow_fcn)

or equivalently using pipe syntax

xs <- 1:100
ys <- xs |> map(slow_fcn)

Here map() provides no feedback on how far it has progressed, but we can easily add progress reporting by using:

library(purrr)

library(progressify)
handlers(global = TRUE)

xs <- 1:100
ys <- xs |> map(slow_fcn) |> progressify()

Using the default progress handler, the progress reporting will appear as:

  |=====                    |  20%

Supported Functions

The progressify() function supports the following purrr functions:

• map(), map_chr(), map_dbl(), map_int(), map_lgl(), map_vec(), walk()
• map2(), map2_chr(), map2_dbl(), map2_int(), map2_lgl(), map2_vec(), walk2()
• pmap(), pmap_chr(), pmap_dbl(), pmap_int(), pmap_lgl(), pmap_vec(), pwalk()
• imap(), imap_chr(), imap_dbl(), imap_int(), imap_lgl()
• modify(), modify2(), imodify()

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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