A dependency graph for all GitHub repos that use the
rworkflows
GitHub Action.
Here is the code for creating the plot.
Hover over each node to show additional metadata.
Identify the CRAN/Bioc R packages with the most number of downloads.
This guides which packages would be the most useful to focus on
implementing rworkflows
in.
This demonstrates the need for using rworkflows
, as
there are 25,000 R packages that are exclusively distributes via GitHub
(which may or may not have code/documentation checks).
## R version 4.4.1 (2024-06-14)
## Platform: aarch64-apple-darwin20
## Running under: macOS Sonoma 14.6.1
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
##
## locale:
## [1] C/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
##
## time zone: Europe/London
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] data.table_1.16.0 rworkflows_1.0.2
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.5 jsonlite_1.8.9 renv_1.0.8
## [4] dplyr_1.1.4 compiler_4.4.1 BiocManager_1.30.25
## [7] tidyselect_1.2.1 jquerylib_0.1.4 rvcheck_0.2.1
## [10] scales_1.3.0 yaml_2.3.10 fastmap_1.2.0
## [13] here_1.0.1 ggplot2_3.5.1 R6_2.5.1
## [16] generics_0.1.3 knitr_1.48 yulab.utils_0.1.7
## [19] tibble_3.2.1 desc_1.4.3 dlstats_0.1.7
## [22] rprojroot_2.0.4 munsell_0.5.1 bslib_0.8.0
## [25] pillar_1.9.0 RColorBrewer_1.1-3 rlang_1.1.4
## [28] utf8_1.2.4 cachem_1.1.0 badger_0.2.4
## [31] xfun_0.47 fs_1.6.4 sass_0.4.9
## [34] cli_3.6.3 magrittr_2.0.3 digest_0.6.37
## [37] grid_4.4.1 lifecycle_1.0.4 vctrs_0.6.5
## [40] evaluate_1.0.0 glue_1.7.0 fansi_1.0.6
## [43] colorspace_2.1-1 rmarkdown_2.28 tools_4.4.1
## [46] pkgconfig_2.0.3 htmltools_0.5.8.1