Description
Making "Deduplicated" Functions.
Description
Contains one main function deduped() which speeds up slow, vectorized functions by only performing computations on the unique values of the input and expanding the results at the end.
README.md
deduped
deduped contains one main function deduped() which speeds up slow, vectorized functions by only performing computations on the unique values of the input and expanding the results at the end. A convenience wrapper, with_deduped(), was added in version 0.3.0 to allow piping an existing expression.
Note: It only works on functions that preserve length and order.
Installation
You can install the released version of deduped from CRAN with:
install.packages("deduped")
And the development version from GitHub:
if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("orgadish/deduped")
Examples
Setup
library(deduped)
set.seed(0)
slow_tolower <- function(x) {
for (i in x) {
Sys.sleep(0.0005)
}
tolower(x)
}
deduped(...)
# Create a vector with significant duplication.
set.seed(1)
unique_vec <- sample(LETTERS, 5)
print(unique_vec)
#> [1] "Y" "D" "G" "A" "B"
duplicated_vec <- sample(rep(unique_vec, 100))
length(duplicated_vec)
#> [1] 500
system.time({ x1 <- slow_tolower(duplicated_vec) })
#> user system elapsed
#> 0.02 0.02 5.97
system.time({ x2 <- deduped(slow_tolower)(duplicated_vec) })
#> user system elapsed
#> 0.04 0.00 0.15
all.equal(x1, x2)
#> [1] TRUE
Note: As of version 0.3.0, you could also useslow_tolower(duplicated_vec) |> with_deduped().
deduped(lapply)(...)
deduped() can also be combined with lapply() or purrr::map().
set.seed(2)
unique_list <- lapply(1:3, function(j) sample(LETTERS, j, replace = TRUE))
str(unique_list)
#> List of 3
#> $ : chr "U"
#> $ : chr [1:2] "O" "F"
#> $ : chr [1:3] "F" "H" "Q"
# Create a list with significant duplication.
duplicated_list <- sample(rep(unique_list, 50))
length(duplicated_list)
#> [1] 150
system.time({ y1 <- lapply(duplicated_list, slow_tolower) })
#> user system elapsed
#> 0.04 0.00 3.58
system.time({ y2 <- deduped(lapply)(duplicated_list, slow_tolower) })
#> user system elapsed
#> 0.00 0.00 0.09
all.equal(y1, y2)
#> [1] TRUE
deduped(fs::path_rel)(...)
deduped() is helpful on slow path functions like fs::path_rel().
set.seed(3)
top_path <- "x/y/z/"
unique_paths <- paste0(top_path, LETTERS, "/file.csv")
str(unique_paths)
#> chr [1:26] "x/y/z/A/file.csv" "x/y/z/B/file.csv" "x/y/z/C/file.csv" ...
# Create a list with significant duplication.
dup_paths <- sample(rep(unique_paths, 500))
length(dup_paths)
#> [1] 13000
system.time({ y1 <- fs::path_rel(dup_paths, start=top_path) })
#> user system elapsed
#> 3.96 0.03 3.99
system.time({ y2 <- deduped(fs::path_rel)(dup_paths, start=top_path) })
#> user system elapsed
#> 0.01 0.00 0.01
all.equal(y1, y2)
#> [1] TRUE