Using miniCRAN to identify package dependencies

A worked example using the package chron

The function pkgDep() exposes not only these dependencies, but also all recursive dependencies. In other words, it answers the question which packages need to be installed to satisfy all dependencies of dependencies.

This means that the algorithm is as follows:

• First retrieve a list of Suggests and Enhances, using a non-recursive dependency search
• Next, perform a recursive search for all Imports, Depends and LinkingTo

The resulting list of packages should then contain the complete list necessary to satisfy all dependencies. In code:

library("miniCRAN")

tags <- "chron"
pkgDep(tags, availPkgs = cranJuly2014)

##  [1] "chron"        "RColorBrewer" "dichromat"    "munsell"      "plyr"        
##  [6] "labeling"     "colorspace"   "Rcpp"         "digest"       "gtable"      
## [11] "reshape2"     "scales"       "proto"        "MASS"         "stringr"     
## [16] "ggplot2"

To create an igraph plot of the dependencies, use the function makeDepGraph() and plot the results:

dg <- makeDepGraph(tags, enhances = TRUE, availPkgs = cranJuly2014)
set.seed(1)
plot(dg, legendPosition = c(-1, 1), vertex.size = 20)

Note how the dependencies expand to zoo (enhanced), scales and ggplot (suggested) and then recursively from there to get all the Imports and LinkingTo dependencies.

An example with multiple input packages

As a final example, create a dependency graph of seven very popular R packages:

tags <- c("ggplot2", "data.table", "plyr", "knitr", "shiny", "xts", "lattice")
pkgDep(tags, suggests = TRUE, enhances = FALSE, availPkgs = cranJuly2014)

##  [1] "ggplot2"      "data.table"   "plyr"         "knitr"        "shiny"       
##  [6] "xts"          "lattice"      "digest"       "gtable"       "reshape2"    
## [11] "scales"       "proto"        "MASS"         "Rcpp"         "stringr"     
## [16] "RColorBrewer" "dichromat"    "munsell"      "labeling"     "colorspace"  
## [21] "evaluate"     "formatR"      "highr"        "markdown"     "mime"        
## [26] "httpuv"       "caTools"      "RJSONIO"      "xtable"       "htmltools"   
## [31] "bitops"       "zoo"          "SparseM"      "survival"     "Formula"     
## [36] "latticeExtra" "cluster"      "maps"         "sp"           "foreign"     
## [41] "mvtnorm"      "TH.data"      "sandwich"     "nlme"         "Matrix"      
## [46] "bit"          "codetools"    "iterators"    "timeDate"     "quadprog"    
## [51] "Hmisc"        "BH"           "quantreg"     "mapproj"      "hexbin"      
## [56] "maptools"     "multcomp"     "testthat"     "mgcv"         "chron"       
## [61] "reshape"      "fastmatch"    "bit64"        "abind"        "foreach"     
## [66] "doMC"         "itertools"    "testit"       "rgl"          "XML"         
## [71] "RCurl"        "Cairo"        "timeSeries"   "tseries"      "its"         
## [76] "fts"          "tis"          "KernSmooth"

dg <- makeDepGraph(tags, enhances = TRUE, availPkgs = cranJuly2014)
set.seed(1)
plot(dg, legendPosition = c(-1, -1), vertex.size = 10, cex = 0.7)