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 ```r library(progressify) handlers(global = TRUE) library(fwb) # Run fractional weighted bootstrap with progress signaling my_stat <- function(data, w) coef(lm(mpg ~ cyl, data = data, weights = w)) res <- fwb(data = mtcars, statistic = my_stat, R = 1000) |> progressify() ``` # Introduction This vignette demonstrates how to use this approach to add progress reporting to the **[fwb]** package's main function `fwb()`. The **fwb** package provides functions for generating fractional weighted bootstrap replicates. For example, `fwb()` runs a statistic function `R` times: ```r library(fwb) my_stat <- function(data, w) coef(lm(mpg ~ cyl, data = data, weights = w)) res <- fwb(data = mtcars, statistic = my_stat, R = 1000) ``` By default, `fwb()` uses `verbose = TRUE`, which provides progress feedback via the **[pbapply]** package, where the style can be controlled via `pbapply::pboptions()`. As an alternative, we can use the `progressify()` function to report on progress via any combination of **progressr** reporters. To do this, use: ```r library(fwb) library(progressify) handlers(global = TRUE) my_stat <- function(data, w) coef(lm(mpg ~ cyl, data = data, weights = w)) res <- fwb(data = mtcars, statistic = my_stat, R = 1000) |> progressify() ``` Comment: This will disable the built-in progress feedback by setting `verbose = FALSE` in order to avoid dual reporting. # Supported Functions The `progressify()` function supports the following **fwb** functions: * `fwb()` [fwb]: https://cran.r-project.org/package=fwb [pbapply]: https://cran.r-project.org/package=pbapply