ANSI function benchmarks
Gábor Csárdi
2023-11-03
Source:vignettes/ansi-benchmark.Rmd
ansi-benchmark.Rmd$output function (x, options) { hook.t(x, options[[paste0(“attr.”, class)]], options[[paste0(“class.”, class)]]) } <bytecode: 0x55b382f1d8d8> <environment: 0x55b37dfb84a0>
Introduction
Often we can use the corresponding base R function as a baseline. We also compare to the fansi package, where it is possible.
Data
In cli the typical use case is short string scalars, but we run some benchmarks longer strings and string vectors as well.
ansi <- format_inline(
"{col_green(symbol$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 52.3µs 55.8µs 17750. 97.7KB 19.0
#> 2 plain 51.7µs 55.7µs 17699. 0B 19.6
#> 3 base 14.3µs 15.5µs 63586. 48.4KB 19.1
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 54.1µs 58µs 17054. 0B 21.3
#> 2 plain 54.4µs 58.1µs 16997. 0B 21.5
#> 3 base 16.8µs 18.1µs 54418. 0B 21.8
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 125µs 132.5µs 7459. 75.06KB 14.7
#> 2 plain 96.9µs 103.1µs 9581. 8.73KB 16.9
#> 3 base 2.5µs 2.6µs 367624. 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 378µs 395µs 2508. 33.19KB 21.5
#> 2 plain 377µs 395µs 2509. 1.09KB 19.3
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 7.2µs 8µs 121149. 8.02KB 24.2
#> 2 fansi_ansi 37µs 40.2µs 24485. 4.18KB 24.5
#> 3 cli_plain 7.2µs 8µs 122211. 0B 24.4
#> 4 fansi_plain 36.5µs 38.4µs 25038. 688B 12.5
#> 5 cli_vec_ansi 8.8µs 9.4µs 103791. 448B 10.4
#> 6 fansi_vec_ansi 48.6µs 51.1µs 19250. 5.02KB 10.5
#> 7 cli_vec_plain 9.5µs 10.2µs 96475. 448B 9.65
#> 8 fansi_vec_plain 47.4µs 49.6µs 19929. 5.02KB 10.5
#> 9 cli_txt_ansi 7.3µs 7.7µs 126306. 0B 12.6
#> 10 fansi_txt_ansi 36.5µs 38.6µs 25400. 688B 12.7
#> 11 cli_txt_plain 8.3µs 8.8µs 111159. 0B 11.1
#> 12 fansi_txt_plain 47.5µs 50µs 19804. 5.02KB 10.5
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 75.2µs 77.2µs 12888. 28.8KB 6.13
#> 2 fansi 149.9µs 154.3µs 6406. 55.4KB 4.06
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 8.8µs 9.4µs 103692. 0B 10.4
#> 2 fansi_ansi 98.5µs 104.2µs 9525. 31.85KB 10.3
#> 3 base_ansi 900ns 1µs 919653. 0B 0
#> 4 cli_plain 8.9µs 9.4µs 103836. 0B 10.4
#> 5 fansi_plain 98µs 103.6µs 9562. 688B 10.3
#> 6 base_plain 899ns 1µs 992322. 0B 0
#> 7 cli_vec_ansi 35.1µs 36.7µs 27081. 448B 2.71
#> 8 fansi_vec_ansi 125.5µs 133µs 7414. 5.02KB 8.26
#> 9 base_vec_ansi 12.4µs 12.6µs 79046. 448B 0
#> 10 cli_vec_plain 33.9µs 35.3µs 28135. 448B 2.81
#> 11 fansi_vec_plain 113.6µs 120.4µs 8235. 5.02KB 8.26
#> 12 base_vec_plain 7.6µs 7.8µs 126188. 448B 0
#> 13 cli_txt_ansi 35.5µs 36.9µs 26911. 0B 2.69
#> 14 fansi_txt_ansi 114.3µs 120.4µs 8248. 688B 8.22
#> 15 base_txt_ansi 11.6µs 11.7µs 83474. 0B 0
#> 16 cli_txt_plain 32.8µs 34.1µs 29066. 0B 2.91
#> 17 fansi_txt_plain 102.4µs 107.7µs 9178. 688B 10.5
#> 18 base_txt_plain 7µs 7.1µs 139365. 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 10.9µs 11.5µs 84855. 0B 17.0
#> 2 fansi_ansi 99.8µs 105.2µs 9412. 688B 8.22
#> 3 base_ansi 1.3µs 1.5µs 641654. 0B 64.2
#> 4 cli_plain 10.9µs 11.7µs 83752. 0B 8.38
#> 5 fansi_plain 98.8µs 104.6µs 9485. 688B 10.3
#> 6 base_plain 1.1µs 1.3µs 733037. 0B 0
#> 7 cli_vec_ansi 43.4µs 44.7µs 22260. 448B 2.23
#> 8 fansi_vec_ansi 135µs 142.4µs 6976. 5.02KB 8.27
#> 9 base_vec_ansi 41.8µs 42.6µs 23174. 448B 0
#> 10 cli_vec_plain 42.5µs 43.7µs 22747. 448B 2.27
#> 11 fansi_vec_plain 122.2µs 129.1µs 7678. 5.02KB 8.26
#> 12 base_vec_plain 22.8µs 24µs 41365. 448B 0
#> 13 cli_txt_ansi 43.8µs 45µs 22086. 0B 4.42
#> 14 fansi_txt_ansi 122.1µs 128.8µs 7700. 688B 8.22
#> 15 base_txt_ansi 44.7µs 45.6µs 21771. 0B 0
#> 16 cli_txt_plain 41.6µs 42.8µs 23199. 0B 2.32
#> 17 fansi_txt_plain 109.6µs 115.6µs 8577. 688B 8.21
#> 18 base_txt_plain 25µs 25.9µs 38351. 0B 3.84
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 8.5µs 9.1µs 107564. 0B 10.8
#> 2 cli_plain 8.1µs 8.6µs 113254. 0B 11.3
#> 3 cli_vec_ansi 43µs 44.4µs 22392. 848B 2.24
#> 4 cli_vec_plain 13.1µs 13.8µs 71003. 848B 7.10
#> 5 cli_txt_ansi 40.8µs 42.3µs 23463. 0B 2.35
#> 6 cli_txt_plain 9.2µs 9.7µs 100485. 0B 10.0
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 14.4µs 15.4µs 63938. 0B 12.8
#> 2 fansi_ansi 34.6µs 36.6µs 26931. 688B 13.5
#> 3 cli_plain 14.4µs 15.3µs 64396. 0B 12.9
#> 4 fansi_plain 33.8µs 36µs 27411. 688B 13.7
#> 5 cli_vec_ansi 25.4µs 29.3µs 34357. 848B 6.87
#> 6 fansi_vec_ansi 67.5µs 70.2µs 14108. 5.41KB 7.08
#> 7 cli_vec_plain 17.5µs 18.4µs 53417. 848B 10.7
#> 8 fansi_vec_plain 45.9µs 47.6µs 20807. 4.59KB 10.4
#> 9 cli_txt_ansi 25.1µs 25.9µs 38099. 0B 7.62
#> 10 fansi_txt_ansi 55.4µs 57.1µs 17341. 5.12KB 8.23
#> 11 cli_txt_plain 15.4µs 16µs 62039. 0B 12.4
#> 12 fansi_txt_plain 35.5µs 36.8µs 26899. 688B 13.5
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 162.4µs 169µs 5839. 103.35KB 10.3
#> 2 fansi_ansi 145.1µs 153.3µs 6485. 102.16KB 10.4
#> 3 base_ansi 5.3µs 5.6µs 175314. 224B 17.5
#> 4 cli_plain 158µs 166.2µs 5948. 8.09KB 10.3
#> 5 fansi_plain 143.8µs 151.7µs 6553. 9.62KB 10.4
#> 6 base_plain 4.7µs 4.9µs 196263. 0B 19.6
#> 7 cli_vec_ansi 8.52ms 8.79ms 114. 823.77KB 13.7
#> 8 fansi_vec_ansi 1.36ms 1.4ms 696. 846.81KB 12.9
#> 9 base_vec_ansi 205µs 211.4µs 4667. 22.7KB 2.05
#> 10 cli_vec_plain 8.43ms 8.69ms 115. 823.77KB 13.9
#> 11 fansi_vec_plain 1.28ms 1.33ms 752. 845.98KB 13.2
#> 12 base_vec_plain 147.6µs 151µs 6583. 848B 2.02
#> 13 cli_txt_ansi 4.14ms 4.24ms 236. 63.6KB 0
#> 14 fansi_txt_ansi 1.92ms 1.94ms 514. 35.05KB 2.02
#> 15 base_txt_ansi 168.3µs 179.9µs 5558. 18.47KB 2.02
#> 16 cli_txt_plain 2.9ms 2.95ms 337. 63.6KB 0
#> 17 fansi_txt_plain 660.8µs 674.7µs 1453. 30.6KB 2.02
#> 18 base_txt_plain 113.8µs 118.9µs 8309. 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 112.5µs 117.3µs 8432. 32.23KB 12.5
#> 2 fansi_ansi 63.4µs 66.8µs 14766. 31.45KB 10.4
#> 3 base_ansi 1.3µs 1.4µs 680655. 4.2KB 68.1
#> 4 cli_plain 111.6µs 116µs 8523. 0B 10.3
#> 5 fansi_plain 63.2µs 66.8µs 14726. 872B 12.5
#> 6 base_plain 1.2µs 1.3µs 713411. 0B 0
#> 7 cli_vec_ansi 274µs 282µs 3516. 16.73KB 6.18
#> 8 fansi_vec_ansi 148.7µs 153.5µs 6451. 5.59KB 6.16
#> 9 base_vec_ansi 42.3µs 43.7µs 22805. 848B 0
#> 10 cli_vec_plain 215µs 221.1µs 4486. 16.73KB 6.31
#> 11 fansi_vec_plain 142.3µs 147.7µs 6701. 5.59KB 6.16
#> 12 base_vec_plain 36.8µs 38.8µs 25693. 848B 0
#> 13 cli_txt_ansi 123.4µs 128.6µs 7699. 0B 10.3
#> 14 fansi_txt_ansi 63.1µs 66.7µs 14799. 872B 12.5
#> 15 base_txt_ansi 1.3µs 1.4µs 673184. 0B 0
#> 16 cli_txt_plain 113.1µs 118.3µs 8375. 0B 12.5
#> 17 fansi_txt_plain 62.5µs 64.7µs 15238. 872B 12.0
#> 18 base_txt_plain 1.2µs 1.3µs 742370. 0B 0
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 380µs 392.3µs 2528. 266.69KB 10.4
#> 2 fansi_ansi 111.9µs 115.7µs 8551. 10.3KB 12.5
#> 3 base_ansi 45µs 46.6µs 21027. 0B 10.5
#> 4 cli_plain 222.6µs 232µs 4278. 0B 10.3
#> 5 fansi_plain 110.9µs 117.7µs 8416. 872B 12.5
#> 6 base_plain 37µs 38.9µs 25441. 0B 10.2
#> 7 cli_vec_ansi 39.06ms 39.71ms 25.3 2.48KB 21.7
#> 8 fansi_vec_ansi 290.7µs 298.1µs 3276. 7.25KB 6.14
#> 9 base_vec_ansi 2.82ms 2.94ms 341. 48.18KB 10.7
#> 10 cli_vec_plain 22.5ms 23.04ms 43.6 2.48KB 16.3
#> 11 fansi_vec_plain 240.1µs 246.7µs 4017. 6.42KB 6.14
#> 12 base_vec_plain 2.05ms 2.13ms 466. 47.4KB 10.7
#> 13 cli_txt_ansi 25.47ms 25.73ms 38.9 507.59KB 7.29
#> 14 fansi_txt_ansi 273.3µs 280.6µs 3535. 6.77KB 6.14
#> 15 base_txt_ansi 2.76ms 2.83ms 353. 582.06KB 4.15
#> 16 cli_txt_plain 2.13ms 2.18ms 455. 369.84KB 6.32
#> 17 fansi_txt_plain 215.8µs 221.8µs 4472. 2.51KB 6.15
#> 18 base_txt_plain 1.75ms 1.8ms 553. 367.31KB 6.28
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 8.5µs 9.4µs 102888. 23.82KB 20.6
#> 2 fansi_ansi 89.6µs 94.7µs 10422. 28.48KB 10.4
#> 3 base_ansi 1.2µs 1.3µs 726640. 0B 0
#> 4 cli_plain 8.4µs 9.1µs 106847. 0B 21.4
#> 5 fansi_plain 89.7µs 94.4µs 10444. 1.98KB 10.4
#> 6 base_plain 1.1µs 1.3µs 721982. 0B 72.2
#> 7 cli_vec_ansi 34.4µs 36.6µs 27199. 1.7KB 2.72
#> 8 fansi_vec_ansi 136.3µs 141.2µs 6979. 8.86KB 8.31
#> 9 base_vec_ansi 6.9µs 7.3µs 135542. 848B 0
#> 10 cli_vec_plain 28.7µs 30µs 33091. 1.7KB 3.31
#> 11 fansi_vec_plain 128µs 133.2µs 7371. 8.86KB 8.44
#> 12 base_vec_plain 6.2µs 6.7µs 146746. 848B 0
#> 13 cli_txt_ansi 8.4µs 9.2µs 105012. 0B 21.0
#> 14 fansi_txt_ansi 90.4µs 95µs 10376. 1.98KB 10.4
#> 15 base_txt_ansi 4.9µs 5µs 195597. 0B 0
#> 16 cli_txt_plain 9.4µs 10.2µs 95650. 0B 19.1
#> 17 fansi_txt_plain 90.5µs 94.6µs 10438. 1.98KB 10.4
#> 18 base_txt_plain 3.3µs 3.5µs 281591. 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 117.1µs 125.7µs 7900. 11.85KB 9.51
#> 2 base_ansi 1.5µs 1.5µs 642031. 0B 0
#> 3 cli_plain 93.6µs 97.1µs 10196. 8.73KB 8.22
#> 4 base_plain 1.1µs 1.2µs 823001. 0B 0
#> 5 cli_vec_ansi 5.18ms 5.25ms 190. 838.77KB 15.6
#> 6 base_vec_ansi 86.5µs 87.3µs 11415. 848B 0
#> 7 cli_vec_plain 2.94ms 3.01ms 332. 816.9KB 12.9
#> 8 base_vec_plain 50.9µs 51.4µs 19397. 848B 0
#> 9 cli_txt_ansi 13.63ms 14.29ms 70.2 114.42KB 4.26
#> 10 base_txt_ansi 91.5µs 92.9µs 10753. 0B 0
#> 11 cli_txt_plain 286.1µs 293.8µs 3374. 18.16KB 2.04
#> 12 base_txt_plain 49.4µs 49.9µs 19990. 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 85.7µs 89.6µs 11047. 0B 10.3
#> 2 base_ansi 21.7µs 22.9µs 42982. 0B 12.9
#> 3 cli_plain 85.9µs 89.6µs 11046. 0B 10.3
#> 4 base_plain 21.6µs 22.7µs 43464. 0B 13.0
#> 5 cli_vec_ansi 183.2µs 191.6µs 5136. 7.2KB 4.07
#> 6 base_vec_ansi 67.6µs 75µs 13178. 1.66KB 4.07
#> 7 cli_vec_plain 166.7µs 174.5µs 5667. 7.2KB 6.16
#> 8 base_vec_plain 62.8µs 69.9µs 14136. 1.66KB 4.07
#> 9 cli_txt_ansi 150.9µs 155.1µs 6398. 0B 6.11
#> 10 base_txt_ansi 44.8µs 46.1µs 21503. 0B 4.30
#> 11 cli_txt_plain 131.4µs 135.4µs 7319. 0B 8.19
#> 12 base_txt_plain 40.3µs 41.7µs 23794. 0B 4.76UTF-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 10.6µs 11.4µs 85969. 12.3KB 8.60
#> 2 base 999ns 1.1µs 837144. 0B 0
#> 3 cli_vec 32.1µs 33.1µs 29918. 448B 5.98
#> 4 base_vec 15.2µs 15.5µs 64027. 448B 0
#> 5 cli_txt 31.7µs 32.8µs 30178. 0B 3.02
#> 6 base_txt 16.8µs 16.9µs 58353. 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 10.6µs 11.3µs 86849. 0B 8.69
#> 2 base 1.5µs 1.6µs 574169. 0B 0
#> 3 cli_vec 34.3µs 35.7µs 27796. 448B 5.56
#> 4 base_vec 56.5µs 56.9µs 17528. 448B 0
#> 5 cli_txt 34.7µs 35.6µs 27904. 0B 2.79
#> 6 base_txt 103.8µs 105µs 9507. 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 11.6µs 12.3µs 79624. 0B 15.9
#> 2 base 999ns 1.1µs 829603. 0B 0
#> 3 cli_vec 26.2µs 27.2µs 36316. 448B 7.26
#> 4 base_vec 15.2µs 15.5µs 64063. 448B 0
#> 5 cli_txt 27.5µs 28.4µs 34934. 0B 3.49
#> 6 base_txt 16.8µs 16.9µs 58511. 0B 5.85
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 8.2µs 9µs 108282. 21.1KB 10.8
#> 2 base 1.2µs 1.3µs 697639. 0B 0
#> 3 cli_vec 39.2µs 40.2µs 24662. 1.7KB 4.93
#> 4 base_vec 9.8µs 10.1µs 98274. 848B 0
#> 5 cli_txt 8.2µs 8.9µs 109076. 0B 10.9
#> 6 base_txt 7.2µs 7.3µs 134621. 0B 13.5Session info
sessioninfo::session_info()#> ─ Session info ─────────────────────────────────────────────────────────
#> setting value
#> version R version 4.3.2 (2023-10-31)
#> os Ubuntu 22.04.3 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate C.UTF-8
#> ctype C.UTF-8
#> tz UTC
#> date 2023-11-03
#> pandoc 2.19.2 @ /usr/bin/ (via rmarkdown)
#>
#> ─ Packages ─────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> bench 1.1.3 2023-05-04 [1] RSPM
#> bslib 0.5.1 2023-08-11 [1] RSPM
#> cachem 1.0.8 2023-05-01 [1] RSPM
#> cli * 3.6.1 2023-11-03 [1] local
#> codetools 0.2-19 2023-02-01 [3] CRAN (R 4.3.2)
#> desc 1.4.2 2022-09-08 [1] RSPM
#> digest 0.6.33 2023-07-07 [1] RSPM
#> evaluate 0.22 2023-09-29 [1] RSPM
#> fansi * 1.0.5 2023-10-08 [1] RSPM
#> fastmap 1.1.1 2023-02-24 [1] RSPM
#> fs 1.6.3 2023-07-20 [1] RSPM
#> glue 1.6.2 2022-02-24 [1] RSPM
#> htmltools 0.5.6.1 2023-10-06 [1] RSPM
#> jquerylib 0.1.4 2021-04-26 [1] RSPM
#> jsonlite 1.8.7 2023-06-29 [1] RSPM
#> knitr 1.45 2023-10-30 [1] RSPM
#> lifecycle 1.0.3 2022-10-07 [1] RSPM
#> magrittr 2.0.3 2022-03-30 [1] RSPM
#> memoise 2.0.1 2021-11-26 [1] RSPM
#> pillar 1.9.0 2023-03-22 [1] RSPM
#> pkgconfig 2.0.3 2019-09-22 [1] RSPM
#> pkgdown 2.0.7 2022-12-14 [1] any (@2.0.7)
#> profmem 0.6.0 2020-12-13 [1] RSPM
#> purrr 1.0.2 2023-08-10 [1] RSPM
#> R6 2.5.1 2021-08-19 [1] RSPM
#> ragg 1.2.6 2023-10-10 [1] RSPM
#> rlang 1.1.1 2023-04-28 [1] RSPM
#> rmarkdown 2.25 2023-09-18 [1] RSPM
#> rprojroot 2.0.3 2022-04-02 [1] RSPM
#> sass 0.4.7 2023-07-15 [1] RSPM
#> sessioninfo 1.2.2 2021-12-06 [1] RSPM
#> stringi 1.7.12 2023-01-11 [1] RSPM
#> stringr 1.5.0 2022-12-02 [1] RSPM
#> systemfonts 1.0.5 2023-10-09 [1] RSPM
#> textshaping 0.3.7 2023-10-09 [1] RSPM
#> tibble 3.2.1 2023-03-20 [1] RSPM
#> utf8 1.2.4 2023-10-22 [1] RSPM
#> vctrs 0.6.4 2023-10-12 [1] RSPM
#> xfun 0.40 2023-08-09 [1] RSPM
#> yaml 2.3.7 2023-01-23 [1] RSPM
#>
#> [1] /home/runner/work/_temp/Library
#> [2] /opt/R/4.3.2/lib/R/site-library
#> [3] /opt/R/4.3.2/lib/R/library
#>
#> ────────────────────────────────────────────────────────────────────────