Progress updates by progressr is designed to work out of the box
for any iterator framework in R, e.g. lapply()
, foreach,
purrr, and plyr. Below you will a set of examples that
illustrate how to use progressr in common use cases.
library(progressr)
handlers(global = TRUE)
my_fcn <- function(xs) {
p <- progressor(along = xs)
lapply(xs, function(x) {
Sys.sleep(0.1)
p(sprintf("x=%g", x))
sqrt(x)
})
}
y <- my_fcn(1:10)
# |==================== | 40%
library(foreach)
library(progressr)
handlers(global = TRUE)
my_fcn <- function(xs) {
p <- progressor(along = xs)
foreach(x = xs) %do% {
Sys.sleep(0.1)
p(sprintf("x=%g", x))
sqrt(x)
}
}
y <- my_fcn(1:10)
# |==================== | 40%
library(purrr)
library(progressr)
handlers(global = TRUE)
my_fcn <- function(xs) {
p <- progressor(along = xs)
map(xs, function(x) {
Sys.sleep(0.1)
p(sprintf("x=%g", x))
sqrt(x)
})
}
y <- my_fcn(1:10)
# |==================== | 40%
library(plyr)
library(progressr)
handlers(global = TRUE)
my_fcn <- function(xs) {
p <- progressor(along = xs)
llply(xs, function(x, ...) {
Sys.sleep(0.1)
p(sprintf("x=%g", x))
sqrt(x)
})
}
y <- my_fcn(1:10)
# |==================== | 40%
Note how this solution does not make use of plyr's .progress
argument, because the above solution is more powerful and more
flexible, e.g. we have more control on progress updates and their
messages. However, if you prefer the traditional plyr approach,
you can use .progress = "progressr"
, e.g. y <- llply(..., .progress = "progressr")
.