Type: Package
Title: The R Code Optimizer
Version: 1.0.2
Maintainer: Juan Cruz Rodriguez <jcrodriguez@unc.edu.ar>
Description: Automatically apply different strategies to optimize R code. 'rco' functions take R code as input, and returns R code as output.
Depends: R (≥ 3.6.0)
License: GPL-3
URL: https://jcrodriguez1989.github.io/rco/
BugReports: https://github.com/jcrodriguez1989/rco/issues
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Suggests: covr, diffr, ggplot2, httr, knitr, markdown, microbenchmark, rmarkdown, rstudioapi, rvest, shiny, shinythemes, testthat, xml2
NeedsCompilation: no
Packaged: 2021-04-17 13:37:11 UTC; jcrodriguez
Author: Juan Cruz Rodriguez [aut, cre], Yihui Xie ORCID iD [ctb], Nicolás Wolovick [ctb]
Repository: CRAN
Date/Publication: 2021-04-17 14:00:02 UTC

All optimizers list.

Description

List of all the optimizer functions:

Usage

all_optimizers

Format

An object of class list of length 7.

Max optimizers list.

Description

List of all the optimizer functions, with maximum optimization techniques enabled. Note that using this optimizers could change the semantics of the program!

Usage

max_optimizers

Format

An object of class list of length 7.

Optimizer: Common Subexpression Elimination.

Description

Performs one common subexpression elimination pass. Carefully examine the results after running this function!

Usage

opt_common_subexpr(texts, n_values = 2, in_fun_call = FALSE)

Arguments

texts

A list of character vectors with the code to optimize.

n_values

A numeric indicating the minimum number of values to consider a subexpression.

in_fun_call

A logical indicating whether it should propagate in function calls. Note: this could change the semantics of the program.

Examples

code <- paste(
  "a <- b * c + g",
  "d = b * c * e",
  sep = "\n"
)
cat(opt_common_subexpr(list(code))$codes[[1]])

Optimizer: Constant Folding.

Description

Performs one constant folding pass. Carefully examine the results after running this function!

Usage

opt_constant_folding(texts, fold_floats = FALSE, in_fun_call = FALSE)

Arguments

texts

A list of character vectors with the code to optimize.

fold_floats

A logical indicating if floating-point results should be folded (will reduce precision).

in_fun_call

A logical indicating whether it should propagate in function calls. Note: this could change the semantics of the program.

Examples

code <- paste(
  "i <- 320 * 200 * 32",
  "x <- i * 20 + 100",
  sep = "\n"
)
cat(opt_constant_folding(list(code))$codes[[1]])

Optimizer: Constant Propagation.

Description

Performs one constant propagation pass. Carefully examine the results after running this function!

Usage

opt_constant_propagation(texts, in_fun_call = FALSE)

Arguments

texts

A list of character vectors with the code to optimize.

in_fun_call

A logical indicating whether it should propagate in function calls. Note: this could change the semantics of the program.

Examples

code <- paste(
  "i <- 170",
  "x <- -170",
  "y <- x + 124",
  "z <- i - 124",
  sep = "\n"
)
cat(opt_constant_propagation(list(code))$codes[[1]])

Optimizer: Dead Code Elimination.

Description

Performs one dead code elimination pass. Carefully examine the results after running this function!

Usage

opt_dead_code(texts)

Arguments

texts

A list of character vectors with the code to optimize.

Examples

code <- paste(
  "while (TRUE) {",
  "  break",
  "  dead_code()",
  "}",
  sep = "\n"
)
cat(opt_dead_code(list(code))$codes[[1]])

Optimizer: Dead Expression Elimination.

Description

Performs one dead expression elimination pass. Carefully examine the results after running this function!

Usage

opt_dead_expr(texts)

Arguments

texts

A list of character vectors with the code to optimize.

Examples

code <- paste(
  "foo <- function(x) {",
  "  x ^ 3",
  "  return(x ^ 3)",
  "}",
  sep = "\n"
)
cat(opt_dead_expr(list(code))$codes[[1]])

Optimizer: Dead Store Elimination.

Description

Performs one dead store elimination pass. Carefully examine the results after running this function!

Usage

opt_dead_store(texts)

Arguments

texts

A list of character vectors with the code to optimize.

Examples

code <- paste(
  "foo <- function() {",
  "  x <- 128 ^ 2",
  "  return(TRUE)",
  "}",
  sep = "\n"
)
cat(opt_dead_store(list(code))$codes[[1]])

Optimizer: Loop-invariant Code Motion.

Description

Performs one loop-invariant code motion pass. Carefully examine the results after running this function!

Usage

opt_loop_invariant(texts)

Arguments

texts

A list of character vectors with the code to optimize.

Examples

code <- paste(
  "i <- 0",
  "while (i < n) {",
  "  x <- y + z",
  "  a[i] <- 6 * i + x * x",
  "  i <- i + 1",
  "}",
  sep = "\n"
)
cat(opt_loop_invariant(list(code))$codes[[1]])

Optimize '.R' files.

Description

Performs the desired optimization strategies in the files specified. Carefully examine the results after running this function! If several files interact between them (functions from one file use functions from the other), then optimizing all of them together gives more information to rco.

Usage

optimize_files(
  files,
  optimizers = all_optimizers,
  overwrite = FALSE,
  iterations = Inf
)

Arguments

files

A character vector with paths to files to optimize.

optimizers

A named list of optimizer functions.

overwrite

A logical indicating if files should be overwritten, or saved into new files with "optimized_" prefix.

iterations

Numeric indicating the number of times optimizers should pass. If there was no change after current pass, it will stop.

Optimize a folder with '.R' files.

Description

Performs the desired optimization strategies in all the '.R' in a directory. Carefully examine the results after running this function! If several files interact between them (functions from one file use functions from the other), then optimizing all of them together gives more information to rco.

Usage

optimize_folder(
  folder,
  optimizers = all_optimizers,
  overwrite = FALSE,
  iterations = Inf,
  pattern = "\\.R$",
  recursive = TRUE
)

Arguments

folder

Path to a directory with files to optimize.

optimizers

A named list of optimizer functions.

overwrite

A logical indicating if files should be overwritten, or saved into new files with "optimized_" prefix.

iterations

Numeric indicating the number of times optimizers should pass. If there was no change after current pass, it will stop.

pattern

An optional regular expression. Only file names which match the regular expression will be optimized.

recursive

A logical value indicating whether or not files in subdirectories of 'folder' should be optimized as well.

Optimize text containing code.

Description

Performs the desired optimization strategies in the text. Carefully examine the results after running this function!

Usage

optimize_text(text, optimizers = all_optimizers, iterations = Inf)

Arguments

text

A character vector with the code to optimize.

optimizers

A named list of optimizer functions.

iterations

Numeric indicating the number of times optimizers should pass. If there was no change after current pass, it will stop.

rco GUI selector.

Description

Starts the selected rco Graphical User Interface (GUI).

Usage

rco_gui(option)

Arguments

option

A character indicating which GUI to open. One from:

  • "code_optimizer" for single code optimizing.

  • "pkg_optimizer" for package optimizing.

Examples

## Start the GUI
## Not run: 
rco_gui("code_optimizer")

## End(Not run)