The deepdep package provides tools for exploration of package
dependencies. The main deepdep() function allows to acquire deep
dependencies of any package and plot them in an elegant way. It also
adds some popularity measures for the packages e.g. in the form of
download count through the cranlogs package. Uses the CRAN metadata
database and Bioconductor
metadata.
Exploration tools:
deepdep()get_dependencies()get_downloads()get_description()
Visualisation tools:
plot_dependencies()plot_downloads()-
deepdep_shiny()runs shiny application that helps to produce a nice deepdep plot
# Install from CRAN:
install.packages("deepdep")
# Install the development version from GitHub:
devtools::install_github("DominikRafacz/deepdep")Examples introduction to the deepdep package
library(deepdep)
dd <- deepdep("ggplot2", depth = 2)
head(dd)## origin name version type origin_level dest_level
## 1 ggplot2 cli <NA> Imports 0 1
## 2 ggplot2 glue <NA> Imports 0 1
## 3 ggplot2 gtable >= 0.1.1 Imports 0 1
## 4 ggplot2 isoband <NA> Imports 0 1
## 5 ggplot2 lifecycle > 1.0.1 Imports 0 1
## 6 ggplot2 MASS <NA> Imports 0 1
plot_dependencies(dd, "circular")
plot_dependencies("bayes4psy", show_version = TRUE,
dependency_type = c("Depends", "Imports", "Suggests", "LinkingTo"))
dd_xgboost <- deepdep("xgboost", dependency_type = "Imports", downloads = TRUE)
head(dd_xgboost)## origin name version type last_day last_week last_month last_quarter last_half grand_total origin_level dest_level
## 1 xgboost Matrix >= 1.1-0 Imports 5669 78043 317730 1030313 2307023 10546730 0 1
## 2 xgboost data.table >= 1.9.6 Imports 21766 196875 768217 2494588 5294010 43848884 0 1
## 3 xgboost jsonlite >= 1.0 Imports 19405 249759 1048356 3110597 7056167 68812509 0 1
plot_downloads(dd_xgboost)
plot_dependencies(dd_xgboost, "tree", show_version = TRUE)
