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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   10.1ns 86551801.        0B        0
#> 2 fun()                  121.07ns    151ns  4413386.        0B        0
#> 3 .Call(ccli_tick_reset) 110.01ns  121.1ns  7829544.        0B        0
#> 4 interactive()            8.96ns   10.1ns 72387008.        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 18027364.        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  7107282.        0B        0
#> 2 ta[[1]]       121ns    141ns  6243105.        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()         22.2ms   22.2ms      45.0    21.6KB     255.
#> 2 fp()         24.9ms   25.1ms      39.9    82.3KB     200.
(ben_taf$median[2] - ben_taf$median[1]) / 1e5
#> [1] 28.8ns
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)     242ms    244ms      4.09        0B     32.7
#> 2 fp(1e+06)     273ms    275ms      3.64    1.87KB     30.9
(ben_taf2$median[2] - ben_taf2$median[1]) / 1e6
#> [1] 30.8ns
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)     2.54s    2.54s     0.394        0B     33.1
#> 2 fp(1e+07)     2.63s    2.63s     0.380    1.87KB     31.5
(ben_taf3$median[2] - ben_taf3$median[1]) / 1e7
#> [1] 9.9ns
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)     23.7s    23.7s    0.0422        0B     20.7
#> 2 fp(1e+08)     25.7s    25.7s    0.0389    1.87KB     18.9
(ben_taf4$median[2] - ben_taf4$median[1]) / 1e8
#> [1] 19.9ns

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()         83.7ms   91.1ms     10.8      781KB     14.4
#> 2 f01()       112.1ms  127.1ms      7.55     781KB     13.2
#> 3 fp()        119.4ms  124.1ms      7.35     783KB     12.9
(ben_tam$median[3] - ben_tam$median[1]) / 1e5
#> [1] 330ns
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)     1.02s    1.02s     0.979    7.63MB     3.92
#> 2 f01(1e+06)    1.14s    1.14s     0.880    7.63MB     5.28
#> 3 fp(1e+06)      1.5s     1.5s     0.666    7.63MB     4.66
(ben_tam2$median[3] - ben_tam2$median[1]) / 1e6
#> [1] 480ns
(ben_tam2$median[3] - ben_tam2$median[2]) / 1e6
#> [1] 365ns

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()         77.7ms   78.1ms      12.7     1.4MB     9.54
#> 2 f01()        93.3ms   94.3ms      10.6   781.3KB     5.28
#> 3 fp()         96.1ms   96.4ms      10.4   783.2KB    15.6
(ben_pur$median[3] - ben_pur$median[1]) / 1e5
#> [1] 183ns
(ben_pur$median[3] - ben_pur$median[2]) / 1e5
#> [1] 20.4ns
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)     2.05s    2.05s     0.487    7.63MB     1.46
#> 2 f01(1e+06)    1.11s    1.11s     0.903    7.63MB     2.71
#> 3 fp(1e+06)     1.61s    1.61s     0.619    7.63MB     3.10
(ben_pur2$median[3] - ben_pur2$median[1]) / 1e6
#> [1] 1ns
(ben_pur2$median[3] - ben_pur2$median[2]) / 1e6
#> [1] 508ns

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()        23.75ms  30.38ms    33.5      39.3KB     1.97
#> 2 fp()          4.42s    4.42s     0.226   100.4KB     2.94
(ben_tk$median[2] - ben_tk$median[1]) / 1e5
#> [1] 43.8µs

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()        32.99ms  39.15ms    24.6      18.7KB     3.79
#> 2 ff()        44.86ms   50.6ms    19.8      27.6KB     1.80
#> 3 fp()          2.49s    2.49s     0.402    25.1KB     2.81
(ben_api$median[3] - ben_api$median[1]) / 1e5
#> [1] 24.5µs
(ben_api$median[2] - ben_api$median[1]) / 1e5
#> [1] 114ns
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)     224ms  225.4ms    4.43          0B     5.91
#> 2 ff(1e+06)     314ms    314ms    3.18      1.88KB     3.18
#> 3 fp(1e+06)     22.2s    22.2s    0.0451    1.88KB     2.62
(ben_api2$median[3] - ben_api2$median[1]) / 1e6
#> [1] 22µs
(ben_api2$median[2] - ben_api2$median[1]) / 1e6
#> [1] 88.6ns

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()   630.37ms 630.37ms     1.59     2.08KB        0
#> 2 test_modulo()        1.25s    1.25s     0.802    2.24KB        0
#> 3 test_cli()           1.25s    1.25s     0.801   23.89KB        0
#> 4 test_cli_unroll() 622.89ms 622.89ms     1.61     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)
#>    0% | ETA:  4m
#>    0% | ETA:  2h
#>    0% | ETA:  1h
#>    0% | ETA:  1h
#>    0% | ETA:  1h
#>    0% | ETA: 45m
#>    0% | ETA: 40m
#>    0% | ETA: 37m
#>    0% | ETA: 34m
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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… 6.22ms 6.34ms      155.     1.4MB     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 (487/s) | 3ms
#> ⠹ 2 done (68/s) | 30ms
#> ⠸ 3 done (81/s) | 38ms
#> ⠼ 4 done (90/s) | 45ms
#> ⠴ 5 done (96/s) | 53ms
#> ⠦ 6 done (101/s) | 60ms
#> ⠧ 7 done (105/s) | 68ms
#> ⠇ 8 done (108/s) | 75ms
#> ⠏ 9 done (110/s) | 82ms
#> ⠋ 10 done (112/s) | 90ms
#> ⠙ 11 done (114/s) | 97ms
#> ⠹ 12 done (116/s) | 104ms
#> ⠸ 13 done (117/s) | 112ms
#> ⠼ 14 done (118/s) | 119ms
#> ⠴ 15 done (119/s) | 126ms
#> ⠦ 16 done (120/s) | 134ms
#> ⠧ 17 done (121/s) | 141ms
#> ⠇ 18 done (121/s) | 149ms
#> ⠏ 19 done (122/s) | 156ms
#> ⠋ 20 done (123/s) | 164ms
#> ⠙ 21 done (123/s) | 171ms
#> ⠹ 22 done (124/s) | 179ms
#> ⠸ 23 done (124/s) | 186ms
#> ⠼ 24 done (124/s) | 193ms
#> ⠴ 25 done (125/s) | 201ms
#> ⠦ 26 done (125/s) | 208ms
#> ⠧ 27 done (126/s) | 216ms
#> ⠇ 28 done (126/s) | 223ms
#> ⠏ 29 done (126/s) | 231ms
#> ⠋ 30 done (126/s) | 238ms
#> ⠙ 31 done (127/s) | 245ms
#> ⠹ 32 done (127/s) | 253ms
#> ⠸ 33 done (127/s) | 261ms
#> ⠼ 34 done (127/s) | 269ms
#> ⠴ 35 done (127/s) | 277ms
#> ⠦ 36 done (127/s) | 285ms
#> ⠧ 37 done (127/s) | 293ms
#> ⠇ 38 done (127/s) | 300ms
#> ⠏ 39 done (127/s) | 308ms
#> ⠋ 40 done (127/s) | 315ms
#> ⠙ 41 done (126/s) | 327ms
#> ⠹ 42 done (126/s) | 334ms
#> ⠸ 43 done (126/s) | 342ms
#> ⠼ 44 done (126/s) | 349ms
#> ⠴ 45 done (126/s) | 357ms
#> ⠦ 46 done (126/s) | 366ms
#> ⠧ 47 done (126/s) | 373ms
#> ⠇ 48 done (126/s) | 381ms
#> ⠏ 49 done (126/s) | 389ms
#> ⠋ 50 done (126/s) | 396ms
#> ⠙ 51 done (126/s) | 404ms
#> ⠹ 52 done (127/s) | 411ms
#> ⠸ 53 done (127/s) | 419ms
#> ⠼ 54 done (127/s) | 426ms
#> ⠴ 55 done (127/s) | 434ms
#> ⠦ 56 done (127/s) | 441ms
#> ⠧ 57 done (127/s) | 449ms
#> ⠇ 58 done (127/s) | 456ms
#> ⠏ 59 done (127/s) | 464ms
#> ⠋ 60 done (127/s) | 472ms
#> ⠙ 61 done (127/s) | 480ms
#> ⠹ 62 done (127/s) | 487ms
#> ⠸ 63 done (127/s) | 495ms
#> ⠼ 64 done (128/s) | 502ms
#> ⠴ 65 done (128/s) | 510ms
#> ⠦ 66 done (128/s) | 517ms
#> ⠧ 67 done (128/s) | 525ms
#> # 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… 7.31ms 7.44ms      133.     265KB     2.04
cli_progress_done()