cli progress bar benchmark

Introduction

We make sure that the timer is not TRUE, by setting it to ten hours.

library(cli)
# 10 hours
cli:::cli_tick_set(10 * 60 * 60 * 1000)
cli_tick_reset()
#> NULL
`__cli_update_due`
#> [1] FALSE

R benchmarks

The timer

fun <- function() NULL
ben_st <- bench::mark(
  `__cli_update_due`,
  fun(),
  .Call(ccli_tick_reset),
  interactive(),
  check = FALSE
)
ben_st
#> # A tibble: 4 × 6
#>   expression                  min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>             <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 __cli_update_due         6.87ns   10.9ns 76026607.        0B        0
#> 2 fun()                   96.04ns    105ns  5760871.        0B        0
#> 3 .Call(ccli_tick_reset)  91.04ns    100ns  9104102.        0B        0
#> 4 interactive()           10.94ns   15.9ns 55495445.        0B        0

ben_st2 <- bench::mark(
  if (`__cli_update_due`) foobar()
)
ben_st2
#> # A tibble: 1 × 6
#>   expression                            min  median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                       <bch:tm> <bch:t>     <dbl> <bch:byt>    <dbl>
#> 1 if (`__cli_update_due`) foobar()   38.9ns  44.9ns 21420071.        0B        0

`cli_progress_along()`

seq <- 1:100000
ta <- cli_progress_along(seq)
bench::mark(seq[[1]], ta[[1]])
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 seq[[1]]     95.9ns    102ns  7856876.        0B        0
#> 2 ta[[1]]     105.1ns    113ns  7191032.        0B        0

`for` loop

This is the baseline:

f0 <- function(n = 1e5) {
  x <- 0
  seq <- 1:n
  for (i in seq) {
    x <- x + i %% 2
  }
  x
}

With progress bars:

fp <- function(n = 1e5) {
  x <- 0
  seq <- 1:n
  for (i in cli_progress_along(seq)) {
    x <- x + seq[[i]] %% 2
  }
  x
}

Overhead per iteration:

ben_taf <- bench::mark(f0(), fp())
ben_taf
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0()         8.88ms   9.64ms     103.     21.6KB     427.
#> 2 fp()         9.98ms   10.2ms      97.3    82.3KB     445.
(ben_taf$median[2] - ben_taf$median[1]) / 1e5
#> [1] 5.54ns

ben_taf2 <- bench::mark(f0(1e6), fp(1e6))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_taf2
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+06)     105ms    106ms      7.63        0B     63.0
#> 2 fp(1e+06)     107ms    116ms      8.71    1.88KB     69.6
(ben_taf2$median[2] - ben_taf2$median[1]) / 1e6
#> [1] 9.53ns

ben_taf3 <- bench::mark(f0(1e7), fp(1e7))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_taf3
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+07)     1.15s    1.15s     0.868        0B     72.1
#> 2 fp(1e+07)     1.22s    1.22s     0.818    1.88KB     67.1
(ben_taf3$median[2] - ben_taf3$median[1]) / 1e7
#> [1] 7.04ns

ben_taf4 <- bench::mark(f0(1e8), fp(1e8))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_taf4
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+08)     11.2s    11.2s    0.0897        0B     46.8
#> 2 fp(1e+08)     13.5s    13.5s    0.0740    1.88KB     36.5
(ben_taf4$median[2] - ben_taf4$median[1]) / 1e8
#> [1] 23.6ns

Mapping with `lapply()`

This is the baseline:

f0 <- function(n = 1e5) {
  seq <- 1:n
  ret <- lapply(seq, function(x) {
    x %% 2
  })
  invisible(ret)
}

With an index vector:

f01 <- function(n = 1e5) {
  seq <- 1:n
  ret <- lapply(seq_along(seq), function(i) {
    seq[[i]] %% 2
  })
  invisible(ret)
}

With progress bars:

fp <- function(n = 1e5) {
  seq <- 1:n
  ret <- lapply(cli_progress_along(seq), function(i) {
    seq[[i]] %% 2
  })
  invisible(ret)
}

Overhead per iteration:

ben_tam <- bench::mark(f0(), f01(), fp())
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_tam
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0()         70.5ms   76.8ms      9.67     781KB     19.3
#> 2 f01()        78.9ms   87.4ms     11.5      781KB     19.1
#> 3 fp()          102ms  122.4ms      7.55     783KB     10.6
(ben_tam$median[3] - ben_tam$median[1]) / 1e5
#> [1] 456ns

ben_tam2 <- bench::mark(f0(1e6), f01(1e6), fp(1e6))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_tam2
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+06)  680.45ms 680.45ms     1.47     7.63MB     4.41
#> 2 f01(1e+06) 964.99ms 964.99ms     1.04     7.63MB     6.22
#> 3 fp(1e+06)     1.26s    1.26s     0.793    7.63MB     3.96
(ben_tam2$median[3] - ben_tam2$median[1]) / 1e6
#> [1] 581ns
(ben_tam2$median[3] - ben_tam2$median[2]) / 1e6
#> [1] 296ns

Mapping with purrr

This is the baseline:

f0 <- function(n = 1e5) {
  seq <- 1:n
  ret <- purrr::map(seq, function(x) {
    x %% 2
  })
  invisible(ret)
}

With index vector:

f01 <- function(n = 1e5) {
  seq <- 1:n
  ret <- purrr::map(seq_along(seq), function(i) {
    seq[[i]] %% 2
  })
  invisible(ret)
}

With progress bars:

fp <- function(n = 1e5) {
  seq <- 1:n
  ret <- purrr::map(cli_progress_along(seq), function(i) {
    seq[[i]] %% 2
  })
  invisible(ret)
}

Overhead per iteration:

ben_pur <- bench::mark(f0(), f01(), fp())
ben_pur
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0()         53.9ms   56.1ms      17.4    1.39MB    10.4 
#> 2 f01()        66.6ms   76.1ms      13.3   781.3KB     9.98
#> 3 fp()         65.7ms   66.3ms      14.2  783.24KB    14.2
(ben_pur$median[3] - ben_pur$median[1]) / 1e5
#> [1] 102ns
(ben_pur$median[3] - ben_pur$median[2]) / 1e5
#> [1] 1ns

ben_pur2 <- bench::mark(f0(1e6), f01(1e6), fp(1e6))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_pur2
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+06)   692.4ms  692.4ms     1.44     7.63MB     2.89
#> 2 f01(1e+06) 895.01ms 895.01ms     1.12     7.63MB     2.23
#> 3 fp(1e+06)     1.04s    1.04s     0.958    7.63MB     3.83
(ben_pur2$median[3] - ben_pur2$median[1]) / 1e6
#> [1] 351ns
(ben_pur2$median[3] - ben_pur2$median[2]) / 1e6
#> [1] 149ns

`ticking()`

f0 <- function(n = 1e5) {
  i <- 0
  x <- 0 
  while (i < n) {
    x <- x + i %% 2
    i <- i + 1
  }
  x
}

fp <- function(n = 1e5) {
  i <- 0
  x <- 0 
  while (ticking(i < n)) {
    x <- x + i %% 2
    i <- i + 1
  }
  x
}

ben_tk <- bench::mark(f0(), fp())
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_tk
#> # A tibble: 2 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0()         8.48ms   8.84ms   107.       39.3KB     5.96
#> 2 fp()          3.44s    3.44s     0.290   100.4KB     2.32
(ben_tk$median[2] - ben_tk$median[1]) / 1e5
#> [1] 34.3µs

Traditional API

f0 <- function(n = 1e5) {
  x <- 0
  for (i in 1:n) {
    x <- x + i %% 2
  }
  x
}

fp <- function(n = 1e5) {
  cli_progress_bar(total = n)
  x <- 0
  for (i in 1:n) {
    x <- x + i %% 2
    cli_progress_update()
  }
  x
}

ff <- function(n = 1e5) {
  cli_progress_bar(total = n)
  x <- 0
  for (i in 1:n) {
    x <- x + i %% 2
    if (`__cli_update_due`) cli_progress_update()
  }
  x
}

ben_api <- bench::mark(f0(), ff(), fp())
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_api
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0()         8.67ms   9.17ms    83.6      18.7KB     7.96
#> 2 ff()        15.41ms  16.37ms    53.2      27.6KB     3.94
#> 3 fp()          2.01s    2.01s     0.498    25.1KB     1.99
(ben_api$median[3] - ben_api$median[1]) / 1e5
#> [1] 20µs
(ben_api$median[2] - ben_api$median[1]) / 1e5
#> [1] 72.1ns

ben_api2 <- bench::mark(f0(1e6), ff(1e6), fp(1e6))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
ben_api2
#> # A tibble: 3 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f0(1e+06)     102ms  119.4ms    8.69          0B     6.95
#> 2 ff(1e+06)   159.3ms  185.1ms    5.65       1.9KB     5.65
#> 3 fp(1e+06)     18.1s    18.1s    0.0551     1.9KB     2.53
(ben_api2$median[3] - ben_api2$median[1]) / 1e6
#> [1] 18µs
(ben_api2$median[2] - ben_api2$median[1]) / 1e6
#> [1] 65.7ns

C benchmarks

Baseline function:

SEXP test_baseline() {
  int i;
  int res = 0;
  for (i = 0; i < 2000000000; i++) {
    res += i % 2;
  }
  return ScalarInteger(res);
}

Switch + modulo check:

SEXP test_modulo(SEXP progress) {
  int i;
  int res = 0;
  int progress_ = LOGICAL(progress)[0];
  for (i = 0; i < 2000000000; i++) {
    if (i % 10000 == 0 && progress_) cli_progress_set(R_NilValue, i);
    res += i % 2;
  }
  return ScalarInteger(res);
}

cli progress bar API:

SEXP test_cli() {
  int i;
  int res = 0;
  SEXP bar = PROTECT(cli_progress_bar(2000000000, NULL));
  for (i = 0; i < 2000000000; i++) {
    if (CLI_SHOULD_TICK) cli_progress_set(bar, i);
    res += i % 2;
  }
  cli_progress_done(bar);
  UNPROTECT(1);
  return ScalarInteger(res);
}

SEXP test_cli_unroll() {
  int i = 0;
  int res = 0;
  SEXP bar = PROTECT(cli_progress_bar(2000000000, NULL));
  int s, final, step = 2000000000 / 100000;
  for (s = 0; s < 100000; s++) {
    if (CLI_SHOULD_TICK) cli_progress_set(bar, i);
    final = (s + 1) * step;
    for (i = s * step; i < final; i++) {
      res += i % 2;
    }
  }
  cli_progress_done(bar);
  UNPROTECT(1);
  return ScalarInteger(res);
}

library(progresstest)
ben_c <- bench::mark(
  test_baseline(),
  test_modulo(),
  test_cli(),
  test_cli_unroll()
)
ben_c
#> # A tibble: 4 × 6
#>   expression             min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>        <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 test_baseline()   832.74ms 832.74ms     1.20     2.08KB        0
#> 2 test_modulo()        1.22s    1.22s     0.819    2.23KB        0
#> 3 test_cli()           1.18s    1.18s     0.849  174.97KB        0
#> 4 test_cli_unroll() 824.26ms 824.26ms     1.21     3.48KB        0
(ben_c$median[3] - ben_c$median[1]) / 2000000000
#> [1] 1ns

Display update

We only update the display a fixed number of times per second. (Currently maximum five times per second.)

Let’s measure how long a single update takes.

Iterator with a bar

cli_progress_bar(total = 100000)
bench::mark(cli_progress_update(force = TRUE), max_iterations = 10000)
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#> # A tibble: 1 × 6
#>   expression                             min median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                        <bch:tm> <bch:>     <dbl> <bch:byt>    <dbl>
#> 1 cli_progress_update(force = TRUE)   5.42ms 5.89ms      168.    1.43MB     24.7
cli_progress_done()

Iterator without a bar

cli_progress_bar(total = NA)
bench::mark(cli_progress_update(force = TRUE), max_iterations = 10000)
#> ⠙ 1 done (484/s) | 3ms
#> ⠹ 2 done (67/s) | 31ms
#> ⠸ 3 done (81/s) | 38ms
#> ⠼ 4 done (53/s) | 76ms
#> ⠴ 5 done (61/s) | 83ms
#> ⠦ 6 done (67/s) | 90ms
#> ⠧ 7 done (73/s) | 96ms
#> ⠇ 8 done (78/s) | 103ms
#> ⠏ 9 done (82/s) | 110ms
#> ⠋ 10 done (86/s) | 117ms
#> ⠙ 11 done (90/s) | 123ms
#> ⠹ 12 done (90/s) | 133ms
#> ⠸ 13 done (93/s) | 140ms
#> ⠼ 14 done (96/s) | 147ms
#> ⠴ 15 done (97/s) | 155ms
#> ⠦ 16 done (99/s) | 162ms
#> ⠧ 17 done (101/s) | 168ms
#> ⠇ 18 done (103/s) | 175ms
#> ⠏ 19 done (103/s) | 186ms
#> ⠋ 20 done (104/s) | 192ms
#> ⠙ 21 done (105/s) | 200ms
#> ⠹ 22 done (107/s) | 207ms
#> ⠸ 23 done (108/s) | 214ms
#> ⠼ 24 done (109/s) | 220ms
#> ⠴ 25 done (111/s) | 227ms
#> ⠦ 26 done (112/s) | 233ms
#> ⠧ 27 done (111/s) | 243ms
#> ⠇ 28 done (112/s) | 250ms
#> ⠏ 29 done (113/s) | 257ms
#> ⠋ 30 done (114/s) | 264ms
#> ⠙ 31 done (115/s) | 271ms
#> ⠹ 32 done (116/s) | 277ms
#> ⠸ 33 done (117/s) | 284ms
#> ⠼ 34 done (116/s) | 294ms
#> ⠴ 35 done (117/s) | 300ms
#> ⠦ 36 done (118/s) | 307ms
#> ⠧ 37 done (118/s) | 313ms
#> ⠇ 38 done (119/s) | 320ms
#> ⠏ 39 done (120/s) | 327ms
#> ⠋ 40 done (120/s) | 333ms
#> ⠙ 41 done (121/s) | 340ms
#> ⠹ 42 done (120/s) | 350ms
#> ⠸ 43 done (121/s) | 356ms
#> ⠼ 44 done (121/s) | 363ms
#> ⠴ 45 done (122/s) | 369ms
#> ⠦ 46 done (123/s) | 376ms
#> ⠧ 47 done (123/s) | 383ms
#> ⠇ 48 done (123/s) | 389ms
#> ⠏ 49 done (123/s) | 400ms
#> ⠋ 50 done (123/s) | 406ms
#> ⠙ 51 done (124/s) | 413ms
#> ⠹ 52 done (124/s) | 419ms
#> ⠸ 53 done (125/s) | 426ms
#> ⠼ 54 done (125/s) | 433ms
#> ⠴ 55 done (125/s) | 439ms
#> ⠦ 56 done (125/s) | 453ms
#> ⠧ 57 done (124/s) | 460ms
#> ⠇ 58 done (124/s) | 467ms
#> ⠏ 59 done (125/s) | 474ms
#> ⠋ 60 done (125/s) | 480ms
#> ⠙ 61 done (125/s) | 487ms
#> ⠹ 62 done (126/s) | 494ms
#> ⠸ 63 done (126/s) | 501ms
#> ⠼ 64 done (125/s) | 511ms
#> ⠴ 65 done (126/s) | 518ms
#> ⠦ 66 done (126/s) | 524ms
#> ⠧ 67 done (126/s) | 531ms
#> # A tibble: 1 × 6
#>   expression                             min median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                        <bch:tm> <bch:>     <dbl> <bch:byt>    <dbl>
#> 1 cli_progress_update(force = TRUE)   6.23ms 6.65ms      148.     278KB     23.4
cli_progress_done()

Gábor Csárdi

2025-05-23

Introduction

R benchmarks

The timer

`cli_progress_along()`

`for` loop

Mapping with `lapply()`

Mapping with purrr

`ticking()`

Traditional API

C benchmarks

Display update

Iterator with a bar

Iterator without a bar

cli progress bar benchmark

Gábor Csárdi

2025-05-23

Introduction

R benchmarks

The timer

cli_progress_along()

for loop

Mapping with lapply()

Mapping with purrr

ticking()

Traditional API

C benchmarks

Display update

Iterator with a bar

Iterator without a bar

`cli_progress_along()`

`for` loop

Mapping with `lapply()`

`ticking()`