High Precise Measurement of R Expressions Execution Time

Provides infrastructure to accurately measure and compare the execution time of R expressions.

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Package benchr provides an infrastructure (framework) for precise measurement of R expressions execution time.

Key features:

  • Cross-platform implementation of the timer (the same code for all supported platforms);
  • High precision measurement of time intervals: usually nano or microseconds;
  • The reliability of the results due to a preliminary estimation of the timer error and subsequent correction of measurement results;
  • The stability of the results due to multiple repetitions of the measurements and the use of robust (resistant to outliers) statistics (quantile);
  • Informative output, including measurement accuracy, execution regime and descriptive statistics for each expression;
  • Various graphical representation of measurement results, including box plots, scatter plots and violin plots.


To install the package from the CRAN run the following command:

install.packages("benchr", repos = "https://cloud.r-project.org/")

To install the development version from git repository the install_git() function from devtools package can be used:


This package contains the compiled code, so to install it on Windows you will also need Rtools.


To measure execution time of arbitrary R code, benchr provides function benchmark(), as well as a number of additional methods for analysis and representation of results. Here's an example of time measurement for several expressions.

benchmark(rep(1:10, each = 10), rep.int(1:10, rep.int(10, 10)))
#> Time units : microseconds
#>                            expr n.eval  min lw.qu median mean up.qu  max total relative
#>            rep(1:10, each = 10)    100 2.28  2.44   2.50 2.52  2.56 4.32   252     1.32
#>  rep.int(1:10, rep.int(10, 10))    100 1.63  1.80   1.89 1.92  1.99 4.34   192     1.00

The resulting object can be saved as a variable and reused later in further methods:

res <- benchmark(NULL, {NULL}, {{{NULL}}})
#> Time units : nanoseconds
#>              expr n.eval min lw.qu median  mean up.qu max total relative
#>              NULL    100   8    14     16  16.4    19  31  1640     1.00
#>          { NULL }    100  97   109    115 116.0   120 197 11600     7.19
#>  { { { NULL } } }    100 159   178    181 190.0   187 871 19000    11.30

To present the results of measurements implemented additional methods for the class benchmark object:

  • mean -- means and confidence intervals for each R expression;
  • summary -- statistics (quantiles, means) for each R expression;
  • print -- text representation of results based on method summary;
  • plot -- scatter plot the execution time of each expression measure;
  • boxplot -- box plot the execution time of each expression.

For further details refer to the manual pages and vignettes:

help(package = "benchr")

Bug reports

Use the following command to go to the page for bug report submissions:

bug.report(package = "benchr")

Before reporting a bug or submitting an issue, please do the following:

  • Make sure that no error was found and corrected previously identified. You can use the search by the bug tracker;
  • Check the news list for the current version of the package. An error it might have been caused by changes in the package. This can be done with news(package = "benchr", Version == packageVersion("benchr")) command;
  • Make a minimal reproducible example of the code that consistently causes the error;
  • Make sure that the error triggered in the function from the benchr package, rather than in the code that you pass, that is other functions or packages;
  • Try to reproduce the error with the last development version of the package from the git repository.

When submitting a bug report please include the output produced by functions traceback() and sessionInfo(). This may save a lot of time.


The benchr package is distributed under GPLv2 license.


benchr 0.2.0

  • Added progress bar (using RcppProgress) (#14).
  • Fixed limits when plotting with the log trnasformation (#19).
  • Some fixes related with R 3.3.4

benchr 0.1.0

  • Initial release.

Reference manual

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0.2.0 by Artem Klevtsov, a year ago


Report a bug at https://gitlab.com/artemklevtsov/benchr/issues

Browse source code at https://github.com/cran/benchr

Authors: Artem Klevtsov [aut, cre], Anton Antonov [ctb], Philipp Upravitelev [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, RcppProgress, stats, graphics

Suggests testthat, ggplot2

Linking to Rcpp, RcppProgress

System requirements: C++11

Suggested by cubature.

See at CRAN