ANSI function benchmarks
Gábor Csárdi
2026-06-05
Source:vignettes/ansi-benchmark.Rmd
ansi-benchmark.Rmd$output function (x, options) { if (class == “output” && output_asis(x, options)) return(x) hook.t(x, options[[paste0(“attr.”, class)]], options[[paste0(“class.”, class)]]) } <bytecode: 0x557e2be806a0> <environment: 0x557e2c924f78>
Introduction
Often we can use the corresponding base R function as a baseline. We also compare to the fansi package, where it is possible.
Data
In cli the typical use case is short string scalars, but we run some benchmarks longer strings and string vectors as well.
ansi <- format_inline(
"{col_green(symbol$tick)} {.code print(x)} {.emph emphasised}"
)
plain <- ansi_strip(ansi)ANSI functions
ansi_align()
bench::mark(
ansi = ansi_align(ansi, width = 20),
plain = ansi_align(plain, width = 20),
base = format(plain, width = 20),
check = FALSE
)#> # A tibble: 3 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 ansi 46.1µs 50.3µs 19283. 99.6KB 21.0
#> 2 plain 46.1µs 49.6µs 19476. 0B 19.5
#> 3 base 11.6µs 12.7µs 76370. 48.6KB 22.9
bench::mark(
ansi = ansi_align(ansi, width = 20, align = "right"),
plain = ansi_align(plain, width = 20, align = "right"),
base = format(plain, width = 20, justify = "right"),
check = FALSE
)#> # A tibble: 3 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 ansi 47.5µs 51.8µs 18653. 0B 21.2
#> 2 plain 47.5µs 51.2µs 18865. 0B 23.2
#> 3 base 13.3µs 14.4µs 66974. 0B 20.1
ansi_chartr()
bench::mark(
ansi = ansi_chartr("abc", "XYZ", ansi),
plain = ansi_chartr("abc", "XYZ", plain),
base = chartr("abc", "XYZ", plain),
check = FALSE
)#> # A tibble: 3 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 ansi 115.95µs 123.78µs 7799. 77.03KB 14.6
#> 2 plain 93.81µs 98.83µs 9755. 8.91KB 14.6
#> 3 base 1.86µs 1.97µs 484151. 0B 0
ansi_columns()
bench::mark(
ansi = ansi_columns(vec_ansi6, width = 120),
plain = ansi_columns(vec_plain6, width = 120),
check = FALSE
)#> # A tibble: 2 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 ansi 345µs 368µs 2672. 33.23KB 19.0
#> 2 plain 339µs 365µs 2711. 1.09KB 19.0
ansi_has_any()
bench::mark(
cli_ansi = ansi_has_any(ansi),
fansi_ansi = has_sgr(ansi),
cli_plain = ansi_has_any(plain),
fansi_plain = has_sgr(plain),
cli_vec_ansi = ansi_has_any(vec_ansi),
fansi_vec_ansi = has_sgr(vec_ansi),
cli_vec_plain = ansi_has_any(vec_plain),
fansi_vec_plain = has_sgr(vec_plain),
cli_txt_ansi = ansi_has_any(txt_ansi),
fansi_txt_ansi = has_sgr(txt_ansi),
cli_txt_plain = ansi_has_any(txt_plain),
fansi_txt_plain = has_sgr(vec_plain),
check = FALSE
)#> # A tibble: 12 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 5.86µs 6.38µs 150682. 9.27KB 30.1
#> 2 fansi_ansi 31.7µs 34.39µs 28079. 4.18KB 25.3
#> 3 cli_plain 5.8µs 6.33µs 152867. 0B 15.3
#> 4 fansi_plain 31.06µs 33.23µs 28410. 688B 14.2
#> 5 cli_vec_ansi 7.24µs 7.66µs 126687. 448B 12.7
#> 6 fansi_vec_ansi 41.23µs 43.58µs 22008. 5.02KB 11.0
#> 7 cli_vec_plain 7.88µs 8.31µs 117394. 448B 11.7
#> 8 fansi_vec_plain 39.28µs 41.39µs 23385. 5.02KB 9.36
#> 9 cli_txt_ansi 5.76µs 6.15µs 158248. 0B 15.8
#> 10 fansi_txt_ansi 31.46µs 33.44µs 29051. 688B 11.6
#> 11 cli_txt_plain 6.58µs 6.97µs 139609. 0B 14.0
#> 12 fansi_txt_plain 39.35µs 41.85µs 23192. 5.02KB 11.6
ansi_html()
This is typically used with longer text.
bench::mark(
cli = ansi_html(txt_ansi),
fansi = sgr_to_html(txt_ansi, classes = TRUE),
check = FALSE
)#> # A tibble: 2 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli 60µs 61.8µs 15796. 22.7KB 4.05
#> 2 fansi 119µs 126µs 7801. 55.3KB 4.05
ansi_nchar()
bench::mark(
cli_ansi = ansi_nchar(ansi),
fansi_ansi = nchar_sgr(ansi),
base_ansi = nchar(ansi),
cli_plain = ansi_nchar(plain),
fansi_plain = nchar_sgr(plain),
base_plain = nchar(plain),
cli_vec_ansi = ansi_nchar(vec_ansi),
fansi_vec_ansi = nchar_sgr(vec_ansi),
base_vec_ansi = nchar(vec_ansi),
cli_vec_plain = ansi_nchar(vec_plain),
fansi_vec_plain = nchar_sgr(vec_plain),
base_vec_plain = nchar(vec_plain),
cli_txt_ansi = ansi_nchar(txt_ansi),
fansi_txt_ansi = nchar_sgr(txt_ansi),
base_txt_ansi = nchar(txt_ansi),
cli_txt_plain = ansi_nchar(txt_plain),
fansi_txt_plain = nchar_sgr(txt_plain),
base_txt_plain = nchar(txt_plain),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 7.1µs 7.79µs 124353. 0B 12.4
#> 2 fansi_ansi 91.8µs 97.49µs 9915. 38.84KB 8.19
#> 3 base_ansi 911.07ns 971.02ns 959052. 0B 0
#> 4 cli_plain 7.05µs 7.62µs 127213. 0B 12.7
#> 5 fansi_plain 91.4µs 96.31µs 10050. 688B 8.18
#> 6 base_plain 831.09ns 891.97ns 1046774. 0B 0
#> 7 cli_vec_ansi 28.35µs 29.16µs 33538. 448B 3.35
#> 8 fansi_vec_ansi 113µs 118.35µs 8167. 5.02KB 8.25
#> 9 base_vec_ansi 17.22µs 17.3µs 56903. 448B 0
#> 10 cli_vec_plain 27.01µs 27.81µs 35158. 448B 3.52
#> 11 fansi_vec_plain 103.17µs 108.58µs 8876. 5.02KB 8.25
#> 12 base_vec_plain 10.16µs 10.25µs 95761. 448B 0
#> 13 cli_txt_ansi 28.22µs 28.95µs 33632. 0B 3.36
#> 14 fansi_txt_ansi 104.47µs 109.58µs 8800. 688B 8.19
#> 15 base_txt_ansi 16.9µs 16.96µs 58051. 0B 0
#> 16 cli_txt_plain 26.47µs 27.24µs 35973. 0B 3.60
#> 17 fansi_txt_plain 94.21µs 99.48µs 9715. 688B 8.19
#> 18 base_txt_plain 9.85µs 9.92µs 98390. 0B 0
bench::mark(
cli_ansi = ansi_nchar(ansi, type = "width"),
fansi_ansi = nchar_sgr(ansi, type = "width"),
base_ansi = nchar(ansi, "width"),
cli_plain = ansi_nchar(plain, type = "width"),
fansi_plain = nchar_sgr(plain, type = "width"),
base_plain = nchar(plain, "width"),
cli_vec_ansi = ansi_nchar(vec_ansi, type = "width"),
fansi_vec_ansi = nchar_sgr(vec_ansi, type = "width"),
base_vec_ansi = nchar(vec_ansi, "width"),
cli_vec_plain = ansi_nchar(vec_plain, type = "width"),
fansi_vec_plain = nchar_sgr(vec_plain, type = "width"),
base_vec_plain = nchar(vec_plain, "width"),
cli_txt_ansi = ansi_nchar(txt_ansi, type = "width"),
fansi_txt_ansi = nchar_sgr(txt_ansi, type = "width"),
base_txt_ansi = nchar(txt_ansi, "width"),
cli_txt_plain = ansi_nchar(txt_plain, type = "width"),
fansi_txt_plain = nchar_sgr(txt_plain, type = "width"),
base_txt_plain = nchar(txt_plain, type = "width"),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 8.67µs 9.44µs 102269. 0B 20.5
#> 2 fansi_ansi 92.48µs 97.62µs 9872. 688B 8.30
#> 3 base_ansi 1.22µs 1.28µs 730336. 0B 0
#> 4 cli_plain 8.72µs 9.43µs 102669. 0B 10.3
#> 5 fansi_plain 92.63µs 97.65µs 9876. 688B 8.19
#> 6 base_plain 1.01µs 1.08µs 872565. 0B 87.3
#> 7 cli_vec_ansi 34.62µs 35.53µs 27511. 448B 2.75
#> 8 fansi_vec_ansi 115.94µs 121.12µs 7991. 5.02KB 6.14
#> 9 base_vec_ansi 40.86µs 41.28µs 23878. 448B 0
#> 10 cli_vec_plain 33.62µs 34.53µs 28319. 448B 5.66
#> 11 fansi_vec_plain 105.92µs 110.97µs 8714. 5.02KB 6.14
#> 12 base_vec_plain 21.61µs 21.88µs 44935. 448B 4.49
#> 13 cli_txt_ansi 35.06µs 35.88µs 27278. 0B 2.73
#> 14 fansi_txt_ansi 107.62µs 112.45µs 8618. 688B 8.17
#> 15 base_txt_ansi 43.16µs 44.07µs 22438. 0B 0
#> 16 cli_txt_plain 33.22µs 34.05µs 28736. 0B 2.87
#> 17 fansi_txt_plain 97.21µs 102.34µs 9449. 688B 8.20
#> 18 base_txt_plain 23.59µs 23.85µs 41283. 0B 0
ansi_simplify()
Nothing to compare here.
bench::mark(
cli_ansi = ansi_simplify(ansi),
cli_plain = ansi_simplify(plain),
cli_vec_ansi = ansi_simplify(vec_ansi),
cli_vec_plain = ansi_simplify(vec_plain),
cli_txt_ansi = ansi_simplify(txt_ansi),
cli_txt_plain = ansi_simplify(txt_plain),
check = FALSE
)#> # A tibble: 6 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 6.97µs 7.58µs 127707. 0B 12.8
#> 2 cli_plain 6.6µs 7.17µs 134463. 0B 13.4
#> 3 cli_vec_ansi 33.27µs 34.27µs 28559. 848B 2.86
#> 4 cli_vec_plain 10.58µs 11.3µs 85864. 848B 8.59
#> 5 cli_txt_ansi 32.63µs 33.7µs 29023. 0B 2.90
#> 6 cli_txt_plain 7.49µs 8.14µs 118485. 0B 11.8
ansi_strip()
bench::mark(
cli_ansi = ansi_strip(ansi),
fansi_ansi = strip_sgr(ansi),
cli_plain = ansi_strip(plain),
fansi_plain = strip_sgr(plain),
cli_vec_ansi = ansi_strip(vec_ansi),
fansi_vec_ansi = strip_sgr(vec_ansi),
cli_vec_plain = ansi_strip(vec_plain),
fansi_vec_plain = strip_sgr(vec_plain),
cli_txt_ansi = ansi_strip(txt_ansi),
fansi_txt_ansi = strip_sgr(txt_ansi),
cli_txt_plain = ansi_strip(txt_plain),
fansi_txt_plain = strip_sgr(txt_plain),
check = FALSE
)#> # A tibble: 12 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 25.9µs 27.7µs 34425. 0B 13.8
#> 2 fansi_ansi 29.5µs 31.8µs 30383. 7.24KB 12.2
#> 3 cli_plain 25.7µs 27.5µs 35196. 0B 17.6
#> 4 fansi_plain 28.4µs 31µs 31200. 688B 12.5
#> 5 cli_vec_ansi 35.5µs 37.2µs 26149. 848B 10.5
#> 6 fansi_vec_ansi 56.1µs 58.6µs 16567. 5.41KB 6.16
#> 7 cli_vec_plain 28.5µs 30µs 32252. 848B 16.1
#> 8 fansi_vec_plain 37.7µs 39.5µs 24423. 4.59KB 9.77
#> 9 cli_txt_ansi 34.3µs 35.6µs 27250. 0B 10.9
#> 10 fansi_txt_ansi 44.9µs 46.4µs 20780. 5.12KB 8.32
#> 11 cli_txt_plain 26.3µs 27.5µs 35241. 0B 17.6
#> 12 fansi_txt_plain 29.5µs 31.3µs 30854. 688B 12.3
ansi_strsplit()
bench::mark(
cli_ansi = ansi_strsplit(ansi, "i"),
fansi_ansi = strsplit_sgr(ansi, "i"),
base_ansi = strsplit(ansi, "i"),
cli_plain = ansi_strsplit(plain, "i"),
fansi_plain = strsplit_sgr(plain, "i"),
base_plain = strsplit(plain, "i"),
cli_vec_ansi = ansi_strsplit(vec_ansi, "i"),
fansi_vec_ansi = strsplit_sgr(vec_ansi, "i"),
base_vec_ansi = strsplit(vec_ansi, "i"),
cli_vec_plain = ansi_strsplit(vec_plain, "i"),
fansi_vec_plain = strsplit_sgr(vec_plain, "i"),
base_vec_plain = strsplit(vec_plain, "i"),
cli_txt_ansi = ansi_strsplit(txt_ansi, "i"),
fansi_txt_ansi = strsplit_sgr(txt_ansi, "i"),
base_txt_ansi = strsplit(txt_ansi, "i"),
cli_txt_plain = ansi_strsplit(txt_plain, "i"),
fansi_txt_plain = strsplit_sgr(txt_plain, "i"),
base_txt_plain = strsplit(txt_plain, "i"),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 163.71µs 171.27µs 5656. 104.86KB 10.3
#> 2 fansi_ansi 131µs 137.9µs 7015. 106.35KB 10.3
#> 3 base_ansi 4.12µs 4.44µs 219206. 224B 0
#> 4 cli_plain 161.18µs 168.97µs 5742. 8.09KB 10.3
#> 5 fansi_plain 128.82µs 135.67µs 7168. 9.62KB 10.4
#> 6 base_plain 3.59µs 3.82µs 253552. 0B 0
#> 7 cli_vec_ansi 7.63ms 7.78ms 128. 823.77KB 13.7
#> 8 fansi_vec_ansi 1.06ms 1.09ms 902. 846.81KB 17.2
#> 9 base_vec_ansi 156.01µs 162.67µs 6055. 22.7KB 2.04
#> 10 cli_vec_plain 7.6ms 7.75ms 129. 823.77KB 11.3
#> 11 fansi_vec_plain 999.76µs 1.03ms 968. 845.98KB 19.5
#> 12 base_vec_plain 107.04µs 113.56µs 8571. 848B 4.05
#> 13 cli_txt_ansi 3.18ms 3.21ms 311. 63.6KB 0
#> 14 fansi_txt_ansi 1.57ms 1.59ms 627. 35.05KB 0
#> 15 base_txt_ansi 137.46µs 145.97µs 6793. 18.47KB 2.02
#> 16 cli_txt_plain 2.35ms 2.38ms 419. 63.6KB 2.01
#> 17 fansi_txt_plain 515.89µs 535.35µs 1861. 30.6KB 2.02
#> 18 base_txt_plain 88.27µs 90.77µs 10829. 11.05KB 2.02
ansi_strtrim()
bench::mark(
cli_ansi = ansi_strtrim(ansi, 10),
fansi_ansi = strtrim_sgr(ansi, 10),
base_ansi = strtrim(ansi, 10),
cli_plain = ansi_strtrim(plain, 10),
fansi_plain = strtrim_sgr(plain, 10),
base_plain = strtrim(plain, 10),
cli_vec_ansi = ansi_strtrim(vec_ansi, 10),
fansi_vec_ansi = strtrim_sgr(vec_ansi, 10),
base_vec_ansi = strtrim(vec_ansi, 10),
cli_vec_plain = ansi_strtrim(vec_plain, 10),
fansi_vec_plain = strtrim_sgr(vec_plain, 10),
base_vec_plain = strtrim(vec_plain, 10),
cli_txt_ansi = ansi_strtrim(txt_ansi, 10),
fansi_txt_ansi = strtrim_sgr(txt_ansi, 10),
base_txt_ansi = strtrim(txt_ansi, 10),
cli_txt_plain = ansi_strtrim(txt_plain, 10),
fansi_txt_plain = strtrim_sgr(txt_plain, 10),
base_txt_plain = strtrim(txt_plain, 10),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 148.89µs 155.31µs 6259. 33.84KB 12.4
#> 2 fansi_ansi 55.17µs 58.55µs 16520. 31.42KB 12.4
#> 3 base_ansi 1.06µs 1.11µs 866330. 4.2KB 0
#> 4 cli_plain 147.31µs 153.22µs 6332. 0B 12.4
#> 5 fansi_plain 55.23µs 58.5µs 16565. 872B 12.4
#> 6 base_plain 991.04ns 1.03µs 893382. 0B 0
#> 7 cli_vec_ansi 273.48µs 285.08µs 3440. 16.73KB 6.27
#> 8 fansi_vec_ansi 116.72µs 121.08µs 7996. 5.59KB 6.15
#> 9 base_vec_ansi 35.5µs 35.86µs 27480. 848B 0
#> 10 cli_vec_plain 229.79µs 240.41µs 4057. 16.73KB 8.27
#> 11 fansi_vec_plain 109.68µs 113.68µs 8551. 5.59KB 8.27
#> 12 base_vec_plain 29.95µs 31.12µs 31841. 848B 0
#> 13 cli_txt_ansi 156.36µs 163.68µs 5911. 0B 10.3
#> 14 fansi_txt_ansi 54.99µs 58.37µs 16565. 872B 11.9
#> 15 base_txt_ansi 1.09µs 1.15µs 823192. 0B 0
#> 16 cli_txt_plain 146.84µs 151.89µs 6383. 0B 14.5
#> 17 fansi_txt_plain 54µs 56.26µs 17069. 872B 10.3
#> 18 base_txt_plain 1.01µs 1.05µs 914582. 0B 91.5
ansi_strwrap()
This function is most useful for longer text, but it is often called for short text in cli, so it makes sense to benchmark that as well.
bench::mark(
cli_ansi = ansi_strwrap(ansi, 30),
fansi_ansi = strwrap_sgr(ansi, 30),
base_ansi = strwrap(ansi, 30),
cli_plain = ansi_strwrap(plain, 30),
fansi_plain = strwrap_sgr(plain, 30),
base_plain = strwrap(plain, 30),
cli_vec_ansi = ansi_strwrap(vec_ansi, 30),
fansi_vec_ansi = strwrap_sgr(vec_ansi, 30),
base_vec_ansi = strwrap(vec_ansi, 30),
cli_vec_plain = ansi_strwrap(vec_plain, 30),
fansi_vec_plain = strwrap_sgr(vec_plain, 30),
base_vec_plain = strwrap(vec_plain, 30),
cli_txt_ansi = ansi_strwrap(txt_ansi, 30),
fansi_txt_ansi = strwrap_sgr(txt_ansi, 30),
base_txt_ansi = strwrap(txt_ansi, 30),
cli_txt_plain = ansi_strwrap(txt_plain, 30),
fansi_txt_plain = strwrap_sgr(txt_plain, 30),
base_txt_plain = strwrap(txt_plain, 30),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 415.81µs 443.25µs 2243. 6.18KB 10.5
#> 2 fansi_ansi 100.5µs 106.13µs 9104. 97.33KB 10.3
#> 3 base_ansi 38.86µs 41.03µs 23389. 0B 11.7
#> 4 cli_plain 274.15µs 286.58µs 3395. 0B 10.3
#> 5 fansi_plain 99.19µs 105.57µs 9135. 872B 10.3
#> 6 base_plain 31.72µs 33.51µs 28700. 0B 11.5
#> 7 cli_vec_ansi 44.65ms 44.94ms 22.3 94.67KB 18.5
#> 8 fansi_vec_ansi 240.22µs 248.86µs 3937. 7.25KB 6.13
#> 9 base_vec_ansi 2.31ms 2.36ms 422. 48.18KB 12.8
#> 10 cli_vec_plain 29.03ms 29.28ms 33.9 2.48KB 14.1
#> 11 fansi_vec_plain 192.65µs 200.76µs 4863. 6.42KB 8.22
#> 12 base_vec_plain 1.67ms 1.73ms 575. 47.4KB 12.8
#> 13 cli_txt_ansi 26.77ms 26.97ms 36.9 4.27MB 4.35
#> 14 fansi_txt_ansi 227.32µs 236.33µs 4150. 6.77KB 6.13
#> 15 base_txt_ansi 1.26ms 1.29ms 767. 582.06KB 11.1
#> 16 cli_txt_plain 1.28ms 1.33ms 749. 369.84KB 9.00
#> 17 fansi_txt_plain 178.54µs 186.05µs 5263. 2.51KB 6.10
#> 18 base_txt_plain 842.4µs 875.56µs 1135. 367.31KB 10.9
ansi_substr()
bench::mark(
cli_ansi = ansi_substr(ansi, 2, 10),
fansi_ansi = substr_sgr(ansi, 2, 10),
base_ansi = substr(ansi, 2, 10),
cli_plain = ansi_substr(plain, 2, 10),
fansi_plain = substr_sgr(plain, 2, 10),
base_plain = substr(plain, 2, 10),
cli_vec_ansi = ansi_substr(vec_ansi, 2, 10),
fansi_vec_ansi = substr_sgr(vec_ansi, 2, 10),
base_vec_ansi = substr(vec_ansi, 2, 10),
cli_vec_plain = ansi_substr(vec_plain, 2, 10),
fansi_vec_plain = substr_sgr(vec_plain, 2, 10),
base_vec_plain = substr(vec_plain, 2, 10),
cli_txt_ansi = ansi_substr(txt_ansi, 2, 10),
fansi_txt_ansi = substr_sgr(txt_ansi, 2, 10),
base_txt_ansi = substr(txt_ansi, 2, 10),
cli_txt_plain = ansi_substr(txt_plain, 2, 10),
fansi_txt_plain = substr_sgr(txt_plain, 2, 10),
base_txt_plain = substr(txt_plain, 2, 10),
check = FALSE
)#> # A tibble: 18 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 6.68µs 7.17µs 130243. 25.09KB 13.0
#> 2 fansi_ansi 79.97µs 84.09µs 11540. 28.48KB 10.3
#> 3 base_ansi 1.04µs 1.1µs 855644. 0B 85.6
#> 4 cli_plain 6.68µs 7.18µs 135325. 0B 13.5
#> 5 fansi_plain 79.51µs 84.32µs 11532. 1.98KB 10.4
#> 6 base_plain 1µs 1.06µs 887576. 0B 0
#> 7 cli_vec_ansi 26.34µs 27.2µs 36013. 1.7KB 3.60
#> 8 fansi_vec_ansi 118.43µs 123.01µs 7911. 8.86KB 8.31
#> 9 base_vec_ansi 6.1µs 6.37µs 153521. 848B 0
#> 10 cli_vec_plain 22.76µs 23.59µs 41446. 1.7KB 4.14
#> 11 fansi_vec_plain 112.67µs 117.31µs 8294. 8.86KB 8.31
#> 12 base_vec_plain 5.65µs 5.94µs 164460. 848B 0
#> 13 cli_txt_ansi 6.69µs 7.24µs 133301. 0B 26.7
#> 14 fansi_txt_ansi 80.61µs 84.75µs 11426. 1.98KB 10.3
#> 15 base_txt_ansi 6.47µs 6.54µs 149657. 0B 0
#> 16 cli_txt_plain 7.52µs 8.11µs 119568. 0B 12.0
#> 17 fansi_txt_plain 80.18µs 84.66µs 11428. 1.98KB 12.5
#> 18 base_txt_plain 4.1µs 4.17µs 232162. 0B 0
ansi_tolower() , ansi_toupper()
bench::mark(
cli_ansi = ansi_tolower(ansi),
base_ansi = tolower(ansi),
cli_plain = ansi_tolower(plain),
base_plain = tolower(plain),
cli_vec_ansi = ansi_tolower(vec_ansi),
base_vec_ansi = tolower(vec_ansi),
cli_vec_plain = ansi_tolower(vec_plain),
base_vec_plain = tolower(vec_plain),
cli_txt_ansi = ansi_tolower(txt_ansi),
base_txt_ansi = tolower(txt_ansi),
cli_txt_plain = ansi_tolower(txt_plain),
base_txt_plain = tolower(txt_plain),
check = FALSE
)#> # A tibble: 12 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 111.86µs 117.2µs 8236. 12.1KB 8.20
#> 2 base_ansi 1.32µs 1.37µs 706044. 0B 0
#> 3 cli_plain 90.26µs 94.28µs 10202. 8.91KB 8.20
#> 4 base_plain 1.02µs 1.07µs 885850. 0B 0
#> 5 cli_vec_ansi 4.31ms 4.39ms 227. 838.95KB 15.6
#> 6 base_vec_ansi 71.88µs 72.19µs 13670. 848B 0
#> 7 cli_vec_plain 2.38ms 2.46ms 403. 817.08KB 13.0
#> 8 base_vec_plain 42.57µs 43.11µs 22888. 848B 0
#> 9 cli_txt_ansi 14.44ms 14.54ms 68.7 114.6KB 4.29
#> 10 base_txt_ansi 73.62µs 73.83µs 13354. 0B 0
#> 11 cli_txt_plain 307.01µs 316.87µs 3080. 18.34KB 2.01
#> 12 base_txt_plain 41µs 41.9µs 23674. 0B 0
ansi_trimws()
bench::mark(
cli_ansi = ansi_trimws(ansi),
base_ansi = trimws(ansi),
cli_plain = ansi_trimws(plain),
base_plain = trimws(plain),
cli_vec_ansi = ansi_trimws(vec_ansi),
base_vec_ansi = trimws(vec_ansi),
cli_vec_plain = ansi_trimws(vec_plain),
base_vec_plain = trimws(vec_plain),
cli_txt_ansi = ansi_trimws(txt_ansi),
base_txt_ansi = trimws(txt_ansi),
cli_txt_plain = ansi_trimws(txt_plain),
base_txt_plain = trimws(txt_plain),
check = FALSE
)#> # A tibble: 12 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli_ansi 108.8µs 114.3µs 8395. 0B 12.4
#> 2 base_ansi 16.7µs 17.8µs 54293. 0B 10.9
#> 3 cli_plain 108.1µs 113.4µs 8525. 0B 12.4
#> 4 base_plain 16.8µs 17.7µs 54592. 0B 10.9
#> 5 cli_vec_ansi 207.7µs 217.9µs 4473. 7.2KB 6.12
#> 6 base_vec_ansi 60µs 65.2µs 14898. 1.66KB 4.06
#> 7 cli_vec_plain 189.1µs 202.3µs 4817. 7.2KB 6.13
#> 8 base_vec_plain 52.8µs 58µs 16754. 1.66KB 4.05
#> 9 cli_txt_ansi 182.1µs 188.5µs 5155. 0B 6.10
#> 10 base_txt_ansi 41.5µs 42.6µs 22755. 0B 4.55
#> 11 cli_txt_plain 165.7µs 172.5µs 5642. 0B 8.26
#> 12 base_txt_plain 35.9µs 37.3µs 26193. 0B 5.24UTF-8 functions
utf8_nchar()
bench::mark(
cli = utf8_nchar(uni, type = "chars"),
base = nchar(uni, "chars"),
cli_vec = utf8_nchar(vec_uni, type = "chars"),
base_vec = nchar(vec_uni, "chars"),
cli_txt = utf8_nchar(txt_uni, type = "chars"),
base_txt = nchar(txt_uni, "chars"),
check = FALSE
)#> # A tibble: 6 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli 8.41µs 9.06µs 106005. 0B 21.2
#> 2 base 881.03ns 922.13ns 1015089. 0B 0
#> 3 cli_vec 23.43µs 24.2µs 40395. 448B 4.04
#> 4 base_vec 11.63µs 11.9µs 82636. 448B 0
#> 5 cli_txt 23.48µs 24.26µs 39851. 0B 3.99
#> 6 base_txt 12.63µs 12.73µs 77328. 0B 0
bench::mark(
cli = utf8_nchar(uni, type = "width"),
base = nchar(uni, "width"),
cli_vec = utf8_nchar(vec_uni, type = "width"),
base_vec = nchar(vec_uni, "width"),
cli_txt = utf8_nchar(txt_uni, type = "width"),
base_txt = nchar(txt_uni, "width"),
check = FALSE
)#> # A tibble: 6 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli 8.48µs 9.1µs 106104. 0B 10.6
#> 2 base 1.3µs 1.37µs 696096. 0B 0
#> 3 cli_vec 29.16µs 30.07µs 32552. 448B 3.26
#> 4 base_vec 50.08µs 50.99µs 19423. 448B 0
#> 5 cli_txt 29.59µs 30.38µs 32160. 0B 6.43
#> 6 base_txt 86.99µs 87.73µs 11269. 0B 0
bench::mark(
cli = utf8_nchar(uni, type = "codepoints"),
base = nchar(uni, "chars"),
cli_vec = utf8_nchar(vec_uni, type = "codepoints"),
base_vec = nchar(vec_uni, "chars"),
cli_txt = utf8_nchar(txt_uni, type = "codepoints"),
base_txt = nchar(txt_uni, "chars"),
check = FALSE
)#> # A tibble: 6 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli 8.92µs 9.62µs 100272. 0B 10.0
#> 2 base 881.03ns 931.09ns 991152. 0B 0
#> 3 cli_vec 19.97µs 20.84µs 46816. 448B 9.37
#> 4 base_vec 11.64µs 11.89µs 82734. 448B 0
#> 5 cli_txt 20.56µs 21.37µs 45663. 0B 4.57
#> 6 base_txt 12.63µs 12.73µs 77314. 0B 0
utf8_substr()
bench::mark(
cli = utf8_substr(uni, 2, 10),
base = substr(uni, 2, 10),
cli_vec = utf8_substr(vec_uni, 2, 10),
base_vec = substr(vec_uni, 2, 10),
cli_txt = utf8_substr(txt_uni, 2, 10),
base_txt = substr(txt_uni, 2, 10),
check = FALSE
)#> # A tibble: 6 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 cli 6.42µs 7.05µs 136453. 22.2KB 27.3
#> 2 base 1.05µs 1.13µs 838434. 0B 0
#> 3 cli_vec 30.61µs 31.61µs 31001. 1.7KB 3.10
#> 4 base_vec 8.34µs 8.64µs 113743. 848B 0
#> 5 cli_txt 6.31µs 6.98µs 138843. 0B 27.8
#> 6 base_txt 5.71µs 5.78µs 162600. 0B 0Session info
sessioninfo::session_info()#> ─ Session info ──────────────────────────────────────────────────────
#> setting value
#> version R version 4.6.0 (2026-04-24)
#> os Ubuntu 24.04.4 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate C.UTF-8
#> ctype C.UTF-8
#> tz UTC
#> date 2026-06-05
#> pandoc 3.8.3 @ /opt/hostedtoolcache/pandoc/3.8.3/x64/ (via rmarkdown)
#> quarto NA
#>
#> ─ Packages ──────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> bench 1.1.4 2025-01-16 [1] RSPM
#> bslib 0.11.0 2026-05-16 [1] RSPM
#> cachem 1.1.0 2024-05-16 [1] RSPM
#> cli * 3.6.6.9000 2026-06-05 [1] local
#> codetools 0.2-20 2024-03-31 [3] CRAN (R 4.6.0)
#> desc 1.4.3 2023-12-10 [1] RSPM
#> digest 0.6.39 2025-11-19 [1] RSPM
#> evaluate 1.0.5 2025-08-27 [1] RSPM
#> fansi * 1.0.7 2025-11-19 [1] RSPM
#> fastmap 1.2.0 2024-05-15 [1] RSPM
#> fs 2.1.0 2026-04-18 [1] RSPM
#> glue 1.8.1 2026-04-17 [1] RSPM
#> htmltools 0.5.9 2025-12-04 [1] RSPM
#> htmlwidgets 1.6.4 2023-12-06 [1] RSPM
#> jquerylib 0.1.4 2021-04-26 [1] RSPM
#> jsonlite 2.0.0 2025-03-27 [1] RSPM
#> knitr 1.51 2025-12-20 [1] RSPM
#> lifecycle 1.0.5 2026-01-08 [1] RSPM
#> magrittr 2.0.5 2026-04-04 [1] RSPM
#> pillar 1.11.1 2025-09-17 [1] RSPM
#> pkgconfig 2.0.3 2019-09-22 [1] RSPM
#> pkgdown 2.2.0 2025-11-06 [1] any (@2.2.0)
#> profmem 0.7.0 2025-05-02 [1] RSPM
#> R6 2.6.1 2025-02-15 [1] RSPM
#> ragg 1.5.2 2026-03-23 [1] RSPM
#> rlang 1.2.0 2026-04-06 [1] RSPM
#> rmarkdown 2.31 2026-03-26 [1] RSPM
#> sass 0.4.10 2025-04-11 [1] RSPM
#> sessioninfo 1.2.3 2025-02-05 [1] any (@1.2.3)
#> systemfonts 1.3.2 2026-03-05 [1] RSPM
#> textshaping 1.0.5 2026-03-06 [1] RSPM
#> tibble 3.3.1 2026-01-11 [1] RSPM
#> utf8 1.2.6 2025-06-08 [1] RSPM
#> vctrs 0.7.3 2026-04-11 [1] RSPM
#> xfun 0.58 2026-06-01 [1] RSPM
#> yaml 2.3.12 2025-12-10 [1] RSPM
#>
#> [1] /home/runner/work/_temp/Library
#> [2] /opt/R/4.6.0/lib/R/site-library
#> [3] /opt/R/4.6.0/lib/R/library
#> * ── Packages attached to the search path.
#>
#> ─────────────────────────────────────────────────────────────────────