From 88c582fef71c7add75a10f3c28f39879a98b04c6 Mon Sep 17 00:00:00 2001 From: Robin Lovelace Date: Wed, 3 May 2023 15:09:58 +0100 Subject: [PATCH] Close #87 (#89) * Close #87 I think this would sort it, doesn't need long description. Just a starter for 10, other solutions may be better. * Tweak message --------- Co-authored-by: DavisVaughan --- README.Rmd | 2 ++ README.md | 43 +++++++++++++++++++++++-------------------- 2 files changed, 25 insertions(+), 20 deletions(-) diff --git a/README.Rmd b/README.Rmd index 7a7c72c..8899d9a 100644 --- a/README.Rmd +++ b/README.Rmd @@ -81,6 +81,8 @@ And to plot the benchmark times per commit bench::cb_plot_time(results) ``` +You may need to set git credentials when running this on GitHub Actions using a Linux runner. + ## Usage ### `bench::mark()` diff --git a/README.md b/README.md index b0b4ba1..50946ef 100644 --- a/README.md +++ b/README.md @@ -94,6 +94,9 @@ And to plot the benchmark times per commit bench::cb_plot_time(results) ``` +You may need to set git credentials when running this on GitHub Actions +using a Linux runner. + ## Usage ### `bench::mark()` @@ -136,9 +139,9 @@ bnch #> # A tibble: 3 × 6 #> expression min median `itr/sec` mem_alloc `gc/sec` #> -#> 1 dat[dat$x > 500, ] 329µs 440µs 2215. 377KB 14.5 -#> 2 dat[which(dat$x > 500), ] 255µs 306µs 3038. 260KB 15.3 -#> 3 subset(dat, x > 500) 447µs 525µs 1748. 510KB 19.5 +#> 1 dat[dat$x > 500, ] 277µs 383µs 2485. 377KB 16.3 +#> 2 dat[which(dat$x > 500), ] 203µs 276µs 3635. 260KB 16.9 +#> 3 subset(dat, x > 500) 361µs 487µs 1981. 510KB 16.8 ``` By default the summary uses absolute measures, however relative results @@ -150,9 +153,9 @@ summary(bnch, relative = TRUE) #> # A tibble: 3 × 6 #> expression min median `itr/sec` mem_alloc `gc/sec` #> -#> 1 dat[dat$x > 500, ] 1.29 1.44 1.27 1.45 1 -#> 2 dat[which(dat$x > 500), ] 1 1 1.74 1 1.05 -#> 3 subset(dat, x > 500) 1.75 1.71 1 1.96 1.34 +#> 1 dat[dat$x > 500, ] 1.36 1.39 1.25 1.45 1 +#> 2 dat[which(dat$x > 500), ] 1 1 1.84 1 1.03 +#> 3 subset(dat, x > 500) 1.78 1.77 1 1.96 1.03 ``` ### `bench::press()` @@ -197,18 +200,18 @@ results #> # A tibble: 12 × 8 #> expression rows cols min median `itr/sec` mem_alloc `gc/sec` #> -#> 1 bracket 1000 2 31.9µs 36.5µs 25976. 15.84KB 23.4 -#> 2 which 1000 2 30.7µs 34.6µs 28111. 7.91KB 25.3 -#> 3 subset 1000 2 54.3µs 61µs 15813. 27.7KB 24.4 -#> 4 bracket 10000 2 64.7µs 77.5µs 11807. 156.46KB 38.2 -#> 5 which 10000 2 50µs 57.4µs 16739. 78.23KB 26.5 -#> 6 subset 10000 2 126.1µs 145.3µs 6531. 273.79KB 38.0 -#> 7 bracket 1000 10 81.1µs 93.9µs 9805. 47.52KB 17.3 -#> 8 which 1000 10 71.9µs 77.9µs 12270. 7.91KB 14.7 -#> 9 subset 1000 10 105.4µs 116.5µs 7724. 59.38KB 8.46 -#> 10 bracket 10000 10 160µs 183.7µs 5248. 469.4KB 53.9 -#> 11 which 10000 10 91.8µs 104.6µs 8717. 78.23KB 14.2 -#> 12 subset 10000 10 239.5µs 272.9µs 3406. 586.73KB 41.7 +#> 1 bracket 1000 2 27µs 34µs 27964. 15.84KB 19.6 +#> 2 which 1000 2 25.7µs 33.4µs 29553. 7.91KB 17.7 +#> 3 subset 1000 2 45.9µs 58.2µs 16793. 27.7KB 17.1 +#> 4 bracket 10000 2 64.1µs 70.8µs 13447. 156.46KB 40.5 +#> 5 which 10000 2 46.7µs 54.7µs 17586. 78.23KB 23.3 +#> 6 subset 10000 2 116.2µs 132.1µs 7228. 273.79KB 40.9 +#> 7 bracket 1000 10 77.2µs 85.4µs 11335. 47.52KB 19.9 +#> 8 which 1000 10 67.8µs 75.2µs 13073. 7.91KB 23.2 +#> 9 subset 1000 10 84.7µs 107.5µs 9281. 59.38KB 18.8 +#> 10 bracket 10000 10 130.2µs 169.1µs 5799. 469.4KB 52.2 +#> 11 which 10000 10 75.1µs 96µs 10187. 78.23KB 17.4 +#> 12 subset 10000 10 222.7µs 253µs 3810. 586.73KB 43.3 ``` ## Plotting @@ -257,11 +260,11 @@ bench::system_time({ } }) #> process real -#> 257ms 261ms +#> 222ms 223ms bench::system_time(Sys.sleep(.5)) #> process real -#> 52µs 504ms +#> 88µs 502ms ``` ## Alternatives