Benchmark

This small benchmark compares the performance of the base64 encoding/decoding in package base64url with the implementations in the packages base64enc and openssl.

Encoding of a single string

library(base64url)
library(base64enc)
library(openssl)

## Linking to: OpenSSL 3.0.2 15 Mar 2022

library(microbenchmark)

x = "plain text"
microbenchmark(
  base64url = base64_urlencode(x),
  base64enc = base64encode(charToRaw(x)),
  openssl = base64_encode(x)
)

## Unit: nanoseconds
##       expr  min     lq     mean median      uq     max neval
##  base64url  407  452.5   736.04    497   633.0   18739   100
##  base64enc 1091 1191.5 14667.54   1299  1807.5 1318455   100
##    openssl 9532 9866.5 13068.85  10216 12426.5  158697   100

Decoding of a single string

x = "N0JBLlRaUTp1bi5KOW4xWStNWEJoLHRQaDZ3"
microbenchmark(
  base64url = base64_urldecode(x),
  base64enc = rawToChar(base64decode(x)),
  openssl = rawToChar(base64_decode(x))
)

## Unit: nanoseconds
##       expr   min      lq     mean  median      uq    max neval
##  base64url   421   460.0   757.28   511.5   580.0  19746   100
##  base64enc  1429  1567.5  2984.18  1685.0  2311.0 106994   100
##    openssl 13683 14212.0 17712.23 14891.0 16359.5 132994   100

Encoding and decoding of character vectors

Here, the task has changed from encoding/decoding a single string to processing multiple strings stored inside a character vector. First, we create a small utility function which returns n random strings with a random number of characters (between 1 and 32) each.

rand = function(n, min = 1, max = 32) {
  chars = c(letters, LETTERS, as.character(0:9), c(".", ":", ",", "+", "-", "*", "/"))
  replicate(n, paste0(sample(chars, sample(min:max, 1), replace = TRUE), collapse = ""))
}
set.seed(1)
rand(10)

##  [1] "*MaHQn6Yu1gKKHRGIPLtBtRNR"       "MYPfxFnbSrv,mNVwCmvBVGSuE"      
##  [3] "qV:7YH"                          "aQ6zo5CxPV"                     
##  [5] "Mx0NIQaCvBK8T-YRW73WX"           "gtxY0pbV,R+sqHEITspNiXx"        
##  [7] "FMKlnpob,-"                      "qeOEJWOC:a040XDbJNK3AOo4"       
##  [9] "9fdI4y"                          "KB9tCP7,BElRzGd0xKon03XtbcLoB2/"

Only base64url is vectorized for string input, the alternative implementations need wrappers to process character vectors:

base64enc_encode = function(x) {
  vapply(x, function(x) base64encode(charToRaw(x)), NA_character_, USE.NAMES = FALSE)
}

openssl_encode = function(x) {
  vapply(x, function(x) base64_encode(x), NA_character_, USE.NAMES = FALSE)
}

base64enc_decode = function(x) {
  vapply(x, function(x) rawToChar(base64decode(x)), NA_character_, USE.NAMES = FALSE)
}

openssl_decode = function(x) {
  vapply(x, function(x) rawToChar(base64_decode(x)), NA_character_, USE.NAMES = FALSE)
}

The following benchmark measures the runtime to encode 1000 random strings and then decode them again:

set.seed(1)
x = rand(1000)
microbenchmark(
  base64url = base64_urldecode(base64_urlencode(x)),
  base64enc = base64enc_decode(base64enc_encode(x)),
  openssl = openssl_decode(openssl_encode(x))
)

## Unit: microseconds
##       expr       min        lq       mean     median        uq        max neval
##  base64url   147.796   218.037   283.8289   264.4835   335.215    700.736   100
##  base64enc  3980.447  4664.704  6045.3518  5166.6955  7465.249  13997.749   100
##    openssl 29300.675 33013.969 41965.0264 37026.5725 49688.875 132286.086   100

Michel Lang

2025-10-14

Encoding of a single string

Decoding of a single string

Encoding and decoding of character vectors