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              0     10ns    1.20e8        0B        0
#> 2 fun()                  130.04ns  151.1ns    4.67e6        0B        0
#> 3 .Call(ccli_tick_reset)    100ns    120ns    8.21e6        0B        0
#> 4 interactive()            8.96ns   10.1ns    6.61e7        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> <bch:>     <dbl> <bch:byt>    <dbl>
#> 1 if (`__cli_update_due`) fo…  40ns 50.1ns 20358045.        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]]      110ns    130ns  7061974.        0B        0
#> 2 ta[[1]]       130ns    150ns  6176402.        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()           22ms     22ms      45.4    21.6KB     272.
#> 2 fp()         24.7ms   24.9ms      38.0    82.3KB     142.
(ben_taf$median[2] - ben_taf$median[1]) / 1e5
#> [1] 29.1ns

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)     235ms    238ms      4.20        0B     35.0
#> 2 fp(1e+06)     266ms    293ms      3.41    1.87KB     29.0
(ben_taf2$median[2] - ben_taf2$median[1]) / 1e6
#> [1] 54.6ns

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)     2.49s    2.49s     0.402        0B     33.8
#> 2 fp(1e+07)     2.58s    2.58s     0.388    1.87KB     32.2
(ben_taf3$median[2] - ben_taf3$median[1]) / 1e7
#> [1] 9.28ns

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)     23.2s    23.2s    0.0432        0B     21.1
#> 2 fp(1e+08)     25.3s    25.3s    0.0396    1.87KB     19.3
(ben_taf4$median[2] - ben_taf4$median[1]) / 1e8
#> [1] 21.1ns

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()         84.1ms   89.6ms     10.9      781KB     14.6
#> 2 f01()         105ms  122.7ms      7.90     781KB     13.8
#> 3 fp()        111.1ms  118.2ms      7.84     783KB     13.7
(ben_tam$median[3] - ben_tam$median[1]) / 1e5
#> [1] 285ns

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)  998.48ms 998.48ms     1.00     7.63MB     4.01
#> 2 f01(1e+06)    1.14s    1.14s     0.880    7.63MB     5.28
#> 3 fp(1e+06)     1.49s    1.49s     0.674    7.63MB     4.72
(ben_tam2$median[3] - ben_tam2$median[1]) / 1e6
#> [1] 486ns
(ben_tam2$median[3] - ben_tam2$median[2]) / 1e6
#> [1] 348ns

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()         80.2ms   81.4ms      12.3     1.4MB     6.14
#> 2 f01()        98.6ms   99.5ms      10.1   781.3KB     6.72
#> 3 fp()         98.7ms     99ms      10.1   783.2KB    15.2
(ben_pur$median[3] - ben_pur$median[1]) / 1e5
#> [1] 176ns
(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)     900ms    900ms     1.11     7.63MB     2.22
#> 2 f01(1e+06)    2.25s    2.25s     0.445    7.63MB     1.34
#> 3 fp(1e+06)     1.17s    1.17s     0.858    7.63MB     2.57
(ben_pur2$median[3] - ben_pur2$median[1]) / 1e6
#> [1] 265ns
(ben_pur2$median[3] - ben_pur2$median[2]) / 1e6
#> [1] 1ns

`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()        25.23ms     30ms    33.3      39.3KB     1.96
#> 2 fp()          4.25s    4.25s     0.235   100.4KB     2.35
(ben_tk$median[2] - ben_tk$median[1]) / 1e5
#> [1] 42.2µs

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()        22.09ms  42.35ms    25.7      18.7KB     3.96
#> 2 ff()        31.13ms  50.62ms    21.1      27.6KB     1.92
#> 3 fp()          2.38s    2.38s     0.419    25.1KB     2.10
(ben_api$median[3] - ben_api$median[1]) / 1e5
#> [1] 23.4µs
(ben_api$median[2] - ben_api$median[1]) / 1e5
#> [1] 82.7ns

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)     373ms  391.2ms    2.56          0B     2.56
#> 2 ff(1e+06)   462.1ms  465.5ms    2.15      1.88KB     2.15
#> 3 fp(1e+06)     23.3s    23.3s    0.0430    1.88KB     2.28
(ben_api2$median[3] - ben_api2$median[1]) / 1e6
#> [1] 22.9µs
(ben_api2$median[2] - ben_api2$median[1]) / 1e6
#> [1] 74.3ns

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()   621.99ms 621.99ms     1.61     2.08KB        0
#> 2 test_modulo()        1.25s    1.25s     0.803    2.24KB        0
#> 3 test_cli()           1.24s    1.24s     0.804   23.89KB        0
#> 4 test_cli_unroll() 639.62ms 639.62ms     1.56     3.56KB        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:> <bch:>     <dbl> <bch:byt>    <dbl>
#> 1 cli_progress_update(force… 6.11ms 6.24ms      158.     1.4MB     2.02
cli_progress_done()

Iterator without a bar

cli_progress_bar(total = NA)
bench::mark(cli_progress_update(force = TRUE), max_iterations = 10000)
#> ⠙ 1 done (528/s) | 3ms
#> ⠹ 2 done (71/s) | 29ms
#> ⠸ 3 done (85/s) | 36ms
#> ⠼ 4 done (94/s) | 43ms
#> ⠴ 5 done (100/s) | 51ms
#> ⠦ 6 done (105/s) | 58ms
#> ⠧ 7 done (109/s) | 65ms
#> ⠇ 8 done (112/s) | 72ms
#> ⠏ 9 done (114/s) | 79ms
#> ⠋ 10 done (116/s) | 87ms
#> ⠙ 11 done (118/s) | 94ms
#> ⠹ 12 done (119/s) | 101ms
#> ⠸ 13 done (121/s) | 108ms
#> ⠼ 14 done (122/s) | 116ms
#> ⠴ 15 done (123/s) | 123ms
#> ⠦ 16 done (124/s) | 130ms
#> ⠧ 17 done (124/s) | 137ms
#> ⠇ 18 done (125/s) | 145ms
#> ⠏ 19 done (126/s) | 152ms
#> ⠋ 20 done (126/s) | 159ms
#> ⠙ 21 done (127/s) | 167ms
#> ⠹ 22 done (127/s) | 174ms
#> ⠸ 23 done (127/s) | 181ms
#> ⠼ 24 done (128/s) | 188ms
#> ⠴ 25 done (128/s) | 196ms
#> ⠦ 26 done (129/s) | 203ms
#> ⠧ 27 done (129/s) | 210ms
#> ⠇ 28 done (129/s) | 218ms
#> ⠏ 29 done (129/s) | 225ms
#> ⠋ 30 done (130/s) | 232ms
#> ⠙ 31 done (130/s) | 239ms
#> ⠹ 32 done (130/s) | 247ms
#> ⠸ 33 done (130/s) | 254ms
#> ⠼ 34 done (131/s) | 261ms
#> ⠴ 35 done (131/s) | 268ms
#> ⠦ 36 done (131/s) | 276ms
#> ⠧ 37 done (131/s) | 283ms
#> ⠇ 38 done (131/s) | 290ms
#> ⠏ 39 done (131/s) | 298ms
#> ⠋ 40 done (131/s) | 305ms
#> ⠙ 41 done (132/s) | 312ms
#> ⠹ 42 done (132/s) | 319ms
#> ⠸ 43 done (132/s) | 327ms
#> ⠼ 44 done (132/s) | 334ms
#> ⠴ 45 done (132/s) | 341ms
#> ⠦ 46 done (132/s) | 349ms
#> ⠧ 47 done (132/s) | 356ms
#> ⠇ 48 done (132/s) | 363ms
#> ⠏ 49 done (133/s) | 370ms
#> ⠋ 50 done (132/s) | 381ms
#> ⠙ 51 done (132/s) | 388ms
#> ⠹ 52 done (132/s) | 395ms
#> ⠸ 53 done (132/s) | 402ms
#> ⠼ 54 done (132/s) | 409ms
#> ⠴ 55 done (132/s) | 417ms
#> ⠦ 56 done (132/s) | 424ms
#> ⠧ 57 done (132/s) | 431ms
#> ⠇ 58 done (133/s) | 438ms
#> ⠏ 59 done (133/s) | 445ms
#> ⠋ 60 done (133/s) | 453ms
#> ⠙ 61 done (132/s) | 462ms
#> ⠹ 62 done (132/s) | 470ms
#> ⠸ 63 done (132/s) | 477ms
#> ⠼ 64 done (132/s) | 485ms
#> ⠴ 65 done (132/s) | 492ms
#> ⠦ 66 done (132/s) | 499ms
#> ⠧ 67 done (132/s) | 507ms
#> ⠇ 68 done (132/s) | 514ms
#> ⠏ 69 done (133/s) | 521ms
#> ⠋ 70 done (133/s) | 528ms
#> # A tibble: 1 × 6
#>   expression                    min median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                 <bch:> <bch:>     <dbl> <bch:byt>    <dbl>
#> 1 cli_progress_update(force… 7.12ms 7.25ms      137.     265KB     2.02
cli_progress_done()

Gábor Csárdi

2025-06-01

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

2025-06-01

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()`