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         5.94ns     10ns 73214059.        0B       0 
#> 2 fun()                   92.08ns    101ns  5166993.        0B     517.
#> 3 .Call(ccli_tick_reset)  93.02ns    105ns  8374424.        0B       0 
#> 4 interactive()           13.97ns     19ns 41034412.        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()   36.9ns    44ns 19674948.        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]]       95ns    103ns  7505948.        0B        0
#> 2 ta[[1]]       109ns    121ns  6044900.        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()         9.66ms   11.1ms      86.0    21.6KB     402.
#> 2 fp()        10.88ms   12.9ms      73.2    82.3KB     305.
(ben_taf$median[2] - ben_taf$median[1]) / 1e5
#> [1] 17.5ns

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)     121ms    160ms      6.05        0B     48.4
#> 2 fp(1e+06)     207ms    210ms      4.75    1.88KB     38.0
(ben_taf2$median[2] - ben_taf2$median[1]) / 1e6
#> [1] 50.4ns

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)      1.2s     1.2s     0.834        0B     68.4
#> 2 fp(1e+07)     1.21s    1.21s     0.826    1.88KB     67.7
(ben_taf3$median[2] - ben_taf3$median[1]) / 1e7
#> [1] 1.15ns

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)     11.6s    11.6s    0.0859        0B     45.5
#> 2 fp(1e+08)     13.2s    13.2s    0.0756    1.88KB     37.6
(ben_taf4$median[2] - ben_taf4$median[1]) / 1e8
#> [1] 15.9ns

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()         69.2ms   85.5ms      9.34     781KB    18.7 
#> 2 f01()          74ms   89.8ms     11.1      781KB    18.5 
#> 3 fp()         94.4ms  125.2ms      8.26     783KB     9.91
(ben_tam$median[3] - ben_tam$median[1]) / 1e5
#> [1] 397ns

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)  832.69ms 832.69ms     1.20     7.63MB     8.41
#> 2 f01(1e+06)    1.83s    1.83s     0.547    7.63MB     2.74
#> 3 fp(1e+06)  968.48ms 968.48ms     1.03     7.63MB     5.16
(ben_tam2$median[3] - ben_tam2$median[1]) / 1e6
#> [1] 136ns
(ben_tam2$median[3] - ben_tam2$median[2]) / 1e6
#> [1] 1ns

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()         51.2ms   52.1ms      18.9    1.39MB     9.45
#> 2 f01()        60.5ms   64.3ms      15.6   781.3KB    11.7 
#> 3 fp()         64.3ms   66.2ms      15.1  783.24KB    15.1
(ben_pur$median[3] - ben_pur$median[1]) / 1e5
#> [1] 141ns
(ben_pur$median[3] - ben_pur$median[2]) / 1e5
#> [1] 19.1ns

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)  664.71ms 664.71ms     1.50     7.63MB     3.01
#> 2 f01(1e+06) 972.68ms 972.68ms     1.03     7.63MB     4.11
#> 3 fp(1e+06)     1.41s    1.41s     0.710    7.63MB     2.84
(ben_pur2$median[3] - ben_pur2$median[1]) / 1e6
#> [1] 745ns
(ben_pur2$median[3] - ben_pur2$median[2]) / 1e6
#> [1] 437ns

`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()         8.57ms   8.91ms   104.       39.3KB     5.99
#> 2 fp()          3.43s    3.43s     0.292    99.9KB     3.21
(ben_tk$median[2] - ben_tk$median[1]) / 1e5
#> [1] 34.2µs

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()         8.97ms   9.56ms    85.2      18.7KB     9.91
#> 2 ff()        15.76ms  16.32ms    53.6      27.6KB     5.74
#> 3 fp()          1.88s    1.88s     0.532    25.1KB     2.66
(ben_api$median[3] - ben_api$median[1]) / 1e5
#> [1] 18.7µs
(ben_api$median[2] - ben_api$median[1]) / 1e5
#> [1] 67.6ns

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)   110.4ms  112.6ms    8.32          0B     8.32
#> 2 ff(1e+06)   173.6ms  174.4ms    5.41       1.9KB     5.41
#> 3 fp(1e+06)     18.9s    18.9s    0.0528     1.9KB     3.01
(ben_api2$median[3] - ben_api2$median[1]) / 1e6
#> [1] 18.8µs
(ben_api2$median[2] - ben_api2$median[1]) / 1e6
#> [1] 61.8ns

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()      854ms    854ms     1.17     2.08KB        0
#> 2 test_modulo()        1.21s    1.21s     0.828    2.23KB        0
#> 3 test_cli()           1.22s    1.22s     0.820   23.89KB        0
#> 4 test_cli_unroll() 844.88ms 844.88ms     1.18     3.58KB        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)   5.23ms 5.83ms      160.    1.35MB     2.05
cli_progress_done()

Iterator without a bar

cli_progress_bar(total = NA)
bench::mark(cli_progress_update(force = TRUE), max_iterations = 10000)
#> ⠙ 1 done (347/s) | 4ms
#> ⠹ 2 done (56/s) | 36ms
#> ⠸ 3 done (70/s) | 43ms
#> ⠼ 4 done (81/s) | 50ms
#> ⠴ 5 done (89/s) | 57ms
#> ⠦ 6 done (95/s) | 63ms
#> ⠧ 7 done (101/s) | 70ms
#> ⠇ 8 done (104/s) | 78ms
#> ⠏ 9 done (103/s) | 88ms
#> ⠋ 10 done (107/s) | 94ms
#> ⠙ 11 done (110/s) | 101ms
#> ⠹ 12 done (112/s) | 107ms
#> ⠸ 13 done (115/s) | 114ms
#> ⠼ 14 done (117/s) | 120ms
#> ⠴ 15 done (118/s) | 128ms
#> ⠦ 16 done (120/s) | 134ms
#> ⠧ 17 done (122/s) | 141ms
#> ⠇ 18 done (123/s) | 147ms
#> ⠏ 19 done (124/s) | 154ms
#> ⠋ 20 done (125/s) | 160ms
#> ⠙ 21 done (126/s) | 167ms
#> ⠹ 22 done (127/s) | 173ms
#> ⠸ 23 done (128/s) | 180ms
#> ⠼ 24 done (125/s) | 192ms
#> ⠴ 25 done (126/s) | 200ms
#> ⠦ 26 done (126/s) | 207ms
#> ⠧ 27 done (126/s) | 214ms
#> ⠇ 28 done (127/s) | 222ms
#> ⠏ 29 done (127/s) | 229ms
#> ⠋ 30 done (127/s) | 237ms
#> ⠙ 31 done (127/s) | 245ms
#> ⠹ 32 done (127/s) | 252ms
#> ⠸ 33 done (127/s) | 260ms
#> ⠼ 34 done (128/s) | 267ms
#> ⠴ 35 done (128/s) | 274ms
#> ⠦ 36 done (129/s) | 281ms
#> ⠧ 37 done (129/s) | 287ms
#> ⠇ 38 done (130/s) | 294ms
#> ⠏ 39 done (130/s) | 300ms
#> ⠋ 40 done (131/s) | 307ms
#> ⠙ 41 done (131/s) | 313ms
#> ⠹ 42 done (132/s) | 320ms
#> ⠸ 43 done (132/s) | 326ms
#> ⠼ 44 done (132/s) | 333ms
#> ⠴ 45 done (133/s) | 340ms
#> ⠦ 46 done (133/s) | 346ms
#> ⠧ 47 done (134/s) | 352ms
#> ⠇ 48 done (134/s) | 359ms
#> ⠏ 49 done (134/s) | 365ms
#> ⠋ 50 done (135/s) | 372ms
#> ⠙ 51 done (135/s) | 378ms
#> ⠹ 52 done (135/s) | 385ms
#> ⠸ 53 done (136/s) | 391ms
#> ⠼ 54 done (136/s) | 398ms
#> ⠴ 55 done (136/s) | 404ms
#> ⠦ 56 done (136/s) | 411ms
#> ⠧ 57 done (137/s) | 418ms
#> ⠇ 58 done (137/s) | 424ms
#> ⠏ 59 done (137/s) | 431ms
#> ⠋ 60 done (137/s) | 438ms
#> ⠙ 61 done (138/s) | 444ms
#> ⠹ 62 done (138/s) | 451ms
#> ⠸ 63 done (138/s) | 457ms
#> ⠼ 64 done (138/s) | 464ms
#> ⠴ 65 done (138/s) | 470ms
#> ⠦ 66 done (139/s) | 477ms
#> ⠧ 67 done (139/s) | 483ms
#> ⠇ 68 done (136/s) | 502ms
#> ⠏ 69 done (135/s) | 511ms
#> ⠋ 70 done (135/s) | 517ms
#> ⠙ 71 done (136/s) | 524ms
#> ⠹ 72 done (136/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)   6.31ms 6.59ms      143.     278KB     2.05
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()`