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 digest <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 MASS <NA> Imports 0 1
## 6 ggplot2 mgcv <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 1861 29118 116069 314379 715420 6726824 0 1
## 2 xgboost data.table >= 1.9.6 Imports 18594 205828 890362 2556360 4586475 30727748 0 1
## 3 xgboost jsonlite >= 1.0 Imports 21610 234767 990987 3494965 6879236 50867651 0 1
plot_downloads(dd_xgboost)plot_dependencies(dd_xgboost, "tree", show_version = TRUE)