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         8.96ns     20ns 62519221.        0B        0
#> 2 fun()                  129.92ns  160.1ns  4422941.        0B        0
#> 3 .Call(ccli_tick_reset) 120.02ns  131.1ns  7230596.        0B        0
#> 4 interactive()            8.96ns   11.1ns 66493333.        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`) fooba…  40ns 51.1ns 17321472.        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]]      140ns    151ns  5912968.        0B        0
#> 2 ta[[1]]       140ns    161ns  5400302.        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()         13.9ms   13.9ms      71.8    25.2KB    2010.
#> 2 fp()         16.4ms   16.4ms      61.0    83.3KB    1525.
(ben_taf$median[2] - ben_taf$median[1]) / 1e5
#> [1] 24.6ns

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)     152ms    167ms      5.48        0B     53.0
#> 2 fp(1e+06)     179ms    181ms      5.50    1.88KB     53.2
(ben_taf2$median[2] - ben_taf2$median[1]) / 1e6
#> [1] 13.6ns

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)     1.54s    1.54s     0.650        0B     39.0
#> 2 fp(1e+07)     1.69s    1.69s     0.593    1.88KB     32.0
(ben_taf3$median[2] - ben_taf3$median[1]) / 1e7
#> [1] 14.6ns

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)     15.4s    15.4s    0.0651        0B     40.7
#> 2 fp(1e+08)     17.4s    17.4s    0.0575    1.88KB     34.6
(ben_taf4$median[2] - ben_taf4$median[1]) / 1e8
#> [1] 20.3ns

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()         70.1ms     78ms      9.46     781KB    15.1 
#> 2 f01()        88.8ms    105ms      9.87     781KB    16.4 
#> 3 fp()          100ms    130ms      7.35     783KB     9.18
(ben_tam$median[3] - ben_tam$median[1]) / 1e5
#> [1] 523ns

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)   845.1ms  845.1ms     1.18     7.63MB     8.28
#> 2 f01(1e+06)    1.24s    1.24s     0.809    7.63MB     6.48
#> 3 fp(1e+06)     1.39s    1.39s     0.718    7.63MB     5.74
(ben_tam2$median[3] - ben_tam2$median[1]) / 1e6
#> [1] 548ns
(ben_tam2$median[3] - ben_tam2$median[2]) / 1e6
#> [1] 158ns

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())
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
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()         69.8ms   74.5ms     13.1      884KB     7.51
#> 2 f01()       100.1ms  110.7ms      8.14     781KB     8.14
#> 3 fp()        116.6ms  124.7ms      7.99     783KB     5.99
(ben_pur$median[3] - ben_pur$median[1]) / 1e5
#> [1] 501ns
(ben_pur$median[3] - ben_pur$median[2]) / 1e5
#> [1] 139ns

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)  802.98ms 802.98ms     1.25     7.63MB     2.49
#> 2 f01(1e+06) 903.29ms 903.29ms     1.11     7.63MB     2.21
#> 3 fp(1e+06)     1.03s    1.03s     0.973    7.63MB     2.92
(ben_pur2$median[3] - ben_pur2$median[1]) / 1e6
#> [1] 225ns
(ben_pur2$median[3] - ben_pur2$median[2]) / 1e6
#> [1] 124ns

`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()        14.74ms  14.93ms    65.3      40.3KB     1.98
#> 2 fp()          4.07s    4.07s     0.246   100.8KB     1.96
(ben_tk$median[2] - ben_tk$median[1]) / 1e5
#> [1] 40.6µs

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()        12.48ms  12.59ms    71.5      19.9KB     5.96
#> 2 ff()        19.19ms   19.5ms    47.2      28.6KB     1.97
#> 3 fp()          2.22s    2.22s     0.451    26.1KB     2.25
(ben_api$median[3] - ben_api$median[1]) / 1e5
#> [1] 22.1µs
(ben_api$median[2] - ben_api$median[1]) / 1e5
#> [1] 69.1ns

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)   130.9ms  142.6ms    6.96          0B     5.22
#> 2 ff(1e+06)   206.5ms  209.6ms    4.78      1.88KB     4.78
#> 3 fp(1e+06)     23.3s    23.3s    0.0430    1.88KB     1.85
(ben_api2$median[3] - ben_api2$median[1]) / 1e6
#> [1] 23.1µs
(ben_api2$median[2] - ben_api2$median[1]) / 1e6
#> [1] 67ns

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()   619.77ms 619.77ms     1.61     2.08KB        0
#> 2 test_modulo()        1.25s    1.25s     0.801    2.24KB        0
#> 3 test_cli()           1.26s    1.26s     0.792    23.7KB        0
#> 4 test_cli_unroll() 632.02ms 632.02ms     1.58     3.35KB        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 = T… 5.7ms 5.97ms      165.    1.35MB     2.04
cli_progress_done()

Iterator without a bar

cli_progress_bar(total = NA)
bench::mark(cli_progress_update(force = TRUE), max_iterations = 10000)
#> ⠙ 1 done (400/s) | 3ms
#> ⠹ 2 done (69/s) | 29ms
#> ⠸ 3 done (83/s) | 37ms
#> ⠼ 4 done (92/s) | 44ms
#> ⠴ 5 done (99/s) | 51ms
#> ⠦ 6 done (104/s) | 58ms
#> ⠧ 7 done (108/s) | 65ms
#> ⠇ 8 done (111/s) | 73ms
#> ⠏ 9 done (114/s) | 80ms
#> ⠋ 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 (125/s) | 137ms
#> ⠇ 18 done (126/s) | 144ms
#> ⠏ 19 done (126/s) | 151ms
#> ⠋ 20 done (127/s) | 158ms
#> ⠙ 21 done (128/s) | 165ms
#> ⠹ 22 done (128/s) | 172ms
#> ⠸ 23 done (128/s) | 180ms
#> ⠼ 24 done (129/s) | 187ms
#> ⠴ 25 done (130/s) | 194ms
#> ⠦ 26 done (130/s) | 201ms
#> ⠧ 27 done (130/s) | 208ms
#> ⠇ 28 done (131/s) | 215ms
#> ⠏ 29 done (131/s) | 222ms
#> ⠋ 30 done (132/s) | 229ms
#> ⠙ 31 done (132/s) | 236ms
#> ⠹ 32 done (132/s) | 243ms
#> ⠸ 33 done (133/s) | 249ms
#> ⠼ 34 done (133/s) | 256ms
#> ⠴ 35 done (133/s) | 263ms
#> ⠦ 36 done (134/s) | 270ms
#> ⠧ 37 done (134/s) | 277ms
#> ⠇ 38 done (134/s) | 284ms
#> ⠏ 39 done (134/s) | 291ms
#> ⠋ 40 done (134/s) | 298ms
#> ⠙ 41 done (135/s) | 305ms
#> ⠹ 42 done (135/s) | 312ms
#> ⠸ 43 done (135/s) | 319ms
#> ⠼ 44 done (135/s) | 326ms
#> ⠴ 45 done (135/s) | 333ms
#> ⠦ 46 done (133/s) | 345ms
#> ⠧ 47 done (134/s) | 352ms
#> ⠇ 48 done (134/s) | 360ms
#> ⠏ 49 done (134/s) | 367ms
#> ⠋ 50 done (134/s) | 374ms
#> ⠙ 51 done (134/s) | 381ms
#> ⠹ 52 done (134/s) | 388ms
#> ⠸ 53 done (134/s) | 395ms
#> ⠼ 54 done (135/s) | 402ms
#> ⠴ 55 done (135/s) | 409ms
#> ⠦ 56 done (135/s) | 416ms
#> ⠧ 57 done (135/s) | 423ms
#> ⠇ 58 done (135/s) | 430ms
#> ⠏ 59 done (135/s) | 437ms
#> ⠋ 60 done (135/s) | 444ms
#> ⠙ 61 done (135/s) | 451ms
#> ⠹ 62 done (136/s) | 458ms
#> ⠸ 63 done (136/s) | 465ms
#> ⠼ 64 done (136/s) | 472ms
#> ⠴ 65 done (136/s) | 479ms
#> ⠦ 66 done (136/s) | 486ms
#> ⠧ 67 done (136/s) | 493ms
#> ⠇ 68 done (136/s) | 500ms
#> ⠏ 69 done (136/s) | 507ms
#> ⠋ 70 done (136/s) | 514ms
#> ⠙ 71 done (137/s) | 521ms
#> ⠹ 72 done (137/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 = … 6.81ms 7.03ms      142.     198KB     2.03
cli_progress_done()

Gábor Csárdi

2023-11-14

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

2023-11-14

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()`