Making "Deduplicated" Functions

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.

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    0.00    6.73


system.time({  x2 <- deduped(slow_tolower)(duplicated_vec)  })
#>    user  system elapsed 
#>    0.08    0.00    0.17
all.equal(x1, x2)
#> [1] TRUE

# As of version 0.3.0, you can use `with_deduped()`.
all.equal(x1, slow_tolower(duplicated_vec) |> with_deduped())
#> [1] TRUE

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 
#>    0.03    0.00    3.90
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 
#>    6.16    0.05    6.35
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

When to use with_deduped()

with_deduped() is a convenience wrapper for interactive or one-off use. Because it reconstructs the wrapper function on every call, prefer deduped() directly when calling inside a loop:

# Good: wrapper is built once
deduped_slow_tolower <- deduped(slow_tolower)
for (x in list_of_vecs) deduped_slow_tolower(x)

# Avoid: wrapper is rebuilt on every iteration
for (x in list_of_vecs) slow_tolower(x) |> with_deduped()

deduped(..., verbose = TRUE)

For benchmarking or debugging, pass verbose = TRUE to see the reduction achieved.

head(
  deduped(slow_tolower, verbose = TRUE)(duplicated_vec)
)
#> deduped: 500 value(s) reduced to 5 unique (99.0% reduction).
#> [1] "y" "a" "b" "y" "d" "d"

# Also available in `with_deduped()`:
head(
  slow_tolower(duplicated_vec) |> with_deduped(verbose = TRUE)
)
#> deduped: 500 value(s) reduced to 5 unique (99.0% reduction).
#> [1] "y" "a" "b" "y" "d" "d"

# Use `options(deduped.verbose)` to enable for the entire session.
options(deduped.verbose = TRUE)
head(
  deduped(slow_tolower)(duplicated_vec)
)
#> deduped: 500 value(s) reduced to 5 unique (99.0% reduction).
#> [1] "y" "a" "b" "y" "d" "d"