gt() can affect results of operations that are based on random number generation #1915
Description
Hi, I recently experienced unexpected behavior of {gt} regarding operations that are based on random number generation. When I added a gt to an Rmd, I noticed a slight change of results of a machine learning model, indicating that gt() changes the seed of the random number generator.
library(gt)
set.seed(123)
sample(1:6, size = 1)
#> [1] 3
set.seed(123)
mtcars |> head(1) |> gt()| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb |
|---|---|---|---|---|---|---|---|---|---|---|
| 21 | 6 | 160 | 110 | 3.9 | 2.62 | 16.46 | 0 | 1 | 4 | 4 |
sample(1:6, size = 1)
#> [1] 6Created on 2024-11-03 with reprex v2.1.1
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.4.1 (2024-06-14)
#> os macOS Sonoma 14.7
#> system aarch64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Berlin
#> date 2024-11-03
#> pandoc 3.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/aarch64/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)
#> digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.1)
#> dplyr 1.1.4 2023-11-17 [1] CRAN (R 4.4.0)
#> evaluate 1.0.1 2024-10-10 [1] CRAN (R 4.4.1)
#> fansi 1.0.6 2023-12-08 [1] CRAN (R 4.4.0)
#> fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)
#> fs 1.6.5 2024-10-30 [1] CRAN (R 4.4.1)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)
#> glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.1)
#> gt * 0.11.1 2024-10-04 [1] CRAN (R 4.4.1)
#> htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)
#> knitr 1.48 2024-07-07 [1] CRAN (R 4.4.0)
#> lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)
#> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.4.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)
#> reprex 2.1.1 2024-07-06 [1] CRAN (R 4.4.0)
#> rlang 1.1.4 2024-06-04 [1] CRAN (R 4.4.0)
#> rmarkdown 2.28 2024-08-17 [1] CRAN (R 4.4.0)
#> rstudioapi 0.17.1 2024-10-22 [1] CRAN (R 4.4.1)
#> sass 0.4.9 2024-03-15 [1] CRAN (R 4.4.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.4.0)
#> tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)
#> tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)
#> utf8 1.2.4 2023-10-22 [1] CRAN (R 4.4.0)
#> vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)
#> withr 3.0.2 2024-10-28 [1] CRAN (R 4.4.1)
#> xfun 0.48 2024-10-03 [1] CRAN (R 4.4.1)
#> xml2 1.3.6 2023-12-04 [1] CRAN (R 4.4.0)
#> yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.0)
#>
#> [1] /Users/<xxx>/Library/R/arm64/4.4/library
#> [2] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────This seems to be induced by the random_id() function.
I'd suggest to use withr::with_seed() together with a seed that is e.g. derived from the last digits of the users system time to avoid touching the system settings and potentially messing with the seeds that are set by the user.
(Thanks, @maike2011, for the idea)