readme.md

Shiny Packages

It's time for ShinyConf2024!

ShinyConf is more than just an event; it's a global gathering of diverse Shiny community, creating a shared space for learning, networking, and collaborative exploration. Connect with like-minded enthusiasts from all corners of the world!

Your TidyTuesday maintainers -- Tracy Teal and Jon Harmon -- are both speaking at ShinyConf on Thursday, 2024-04-18. We look forward to seeing you there!

What is the most popular way in which packages are connected to Shiny? Can you create a Shiny app to explore this data?

The Data

# Option 1: tidytuesdayR package 
## install.packages("tidytuesdayR")

tuesdata <- tidytuesdayR::tt_load('2024-04-16')
## OR
tuesdata <- tidytuesdayR::tt_load(2024, week = 16)

shiny_revdeps <- tuesdata$shiny_revdeps
package_details <- tuesdata$package_details

# Option 2: Read directly from GitHub

shiny_revdeps <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-04-16/shiny_revdeps.csv')
package_details <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-04-16/package_details.csv')

How to Participate

• Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. There are various moderating variables that affect all data, many of which might not have been captured in these datasets. As such, our suggestion is to use the data provided to practice your data tidying and plotting techniques, and to consider for yourself what nuances might underlie these relationships.
• Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language.
• Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.

Data Dictionary

shiny_revdeps.csv

variable	class	description
child	character	A package in the shiny reverse-dependency tree
dependency_type	character	How the package is connected to on another package
parent	character	The package that the child is connected to

package_details.csv

See Writing R Extensions for more information about the fields in this dataset.

variable	class	description
Package	character	the name of the package
Version	character	the version of the package
Priority	character	'recommended' indicates packages that are recommended to be incuded in every binary distribution of R. A handful of other packages use "optional" here.
Depends	character	a comma-separated list of package names which this package depends on
Imports	character	packages whose namespaces are imported from (as specified in the NAMESPACE file) but which do not need to be attached
LinkingTo	character	packages whose header files are used to compile this package's C/C++ code
Suggests	character	packages that are not necessarily needed
Enhances	character	packages “enhanced” by the package at hand, e.g., by providing methods for classes from these packages, or ways to handle objects from these packages
License	character	license information
License_is_FOSS	logical	whether the license is considered free, open-source software
License_restricts_use	logical	whether the license restricts use
OS_type	character	specifies the OS(es) for which the package is intended
Archs	character	Archs
MD5sum	character	MD5sum
NeedsCompilation	character	should be set to "yes" if the package contains native code which needs to be compiled, otherwise "no"
Additional_repositories	character	Additional repositories
Author	character	who wrote the package
Authors@R	character	a refined and machine-readable description of the package “authors” (in particular specifying their precise roles)
Biarch	character	used on Windows to select the INSTALL option --force-biarch for this package
BugReports	character	a single URL to which bug reports about the package should be submitted
BuildKeepEmpty	logical	BuildKeepEmpty
BuildManual	logical	BuildManual
BuildResaveData	character	BuildResaveData
BuildVignettes	character	can be set to a false value to stop R CMD build from attempting to build the vignettes, as well as preventing R CMD check from testing this
ByteCompile	character	controls if the package R code is to be byte-compiled on installation
Classification/ACM	logical	subject classifications for the content of the package Computing Classification System of the Association for Computing Machinery
Classification/ACM-2012	logical	subject classifications for the content of the package Computing Classification System of the Association for Computing Machinery
Classification/JEL	logical	subject classifications for the content of the package Journal of Economic Literature Classification System
Classification/MSC	character	subject classifications for the content of the package Mathematics Subject Classification of the American Mathematical Society
Classification/MSC-2010	logical	subject classifications for the content of the package Mathematics Subject Classification of the American Mathematical Society
Collate	character	used for controlling the collation order for the R code files in a package when these are processed for package installation
Contact	character	Contact
Copyright	character	an optional field to be used when the copyright holder(s) are not the authors
Date	character	the release date of the current version of the package
Date/Publication	character	Date/Publication
Description	character	a comprehensive description of what the package does
Encoding	character	used as the encoding of the DESCRIPTION file itself and of the R and NAMESPACE files, and as the default encoding of .Rd files
KeepSource	character	controls if the package code is sourced using keep.source = TRUE or FALSE
Language	character	used to indicate if the package documentation is not in English
LazyData	character	controls whether the R datasets use lazy-loading
LazyDataCompression	character	LazyDataCompression
LazyLoad	character	was used in versions prior to 2.14.0, but now is ignored
MailingList	character	MailingList
Maintainer	character	a single name followed by a valid (RFC 2822) email address in angle brackets
Note	character	Note
Packaged	character	added by the package management tools
RdMacros	character	used to hold a comma-separated list of packages from which the current package will import Rd macro definitions
StagedInstall	logical	controls if package installation is ‘staged’, that is done to a temporary location and moved to the final location when successfully completed
SysDataCompression	logical	SysDataCompression
SystemRequirements	character	dependencies external to the R system
Title	character	a short description of the package
Type	character	specifies the type of the package
URL	character	a list of URLs separated by commas or whitespace, for example the homepage of the author or a page where additional material describing the software can be found
UseLTO	logical	used to indicate if source code in the package is to be compiled with Link-Time Optimization
VignetteBuilder	character	names (in a comma-separated list) packages that provide an engine for building vignettes
ZipData	character	has been ignored since R 2.13.0
X-CRAN-Comment	logical	X-CRAN-Comment
Published	double	Published
Reverse depends	character	Reverse depends
Reverse imports	character	Reverse imports
Reverse linking to	character	Reverse linking to
Reverse suggests	character	Reverse suggests
Reverse enhances	character	Reverse enhances

Cleaning Script

library(tidyverse)
library(janitor)
library(here)
library(fs)

working_dir <- here::here("data", "2024", "2024-04-16")

get_revdeps <- function(pkgs) {
  dependency_types <- c("Depends", "Imports", "LinkingTo", "Suggests")
  revdeps <- purrr::map(
    dependency_types,
    \(dependency_type) {
      these_revdeps <- tools::package_dependencies(
        pkgs,
        which = dependency_type,
        reverse = TRUE
      )
      tibble::enframe(
        these_revdeps,
        name = "parent",
        value = "child"
      ) |> 
        dplyr::mutate(
          dependency_type = tolower(dependency_type),
          .before = "child"
        ) |> 
        tidyr::unnest_longer(child, indices_include = FALSE) |> 
        # Make it readable as a sentence
        dplyr::select(child, dependency_type, parent)
    }
  )
  purrr::list_rbind(revdeps)
}

get_all_revdeps <- function(pkgs) {
  new_packages <- pkgs
  known_packages <- character()
  all_revdeps <- tibble::tibble(
    child = character(),
    dependency_type = character(),
    parent = character()
  )
  while (length(new_packages)) {
    new_revdeps <- get_revdeps(new_packages)
    known_packages <- union(known_packages, new_packages)
    all_revdeps <- dplyr::bind_rows(all_revdeps, new_revdeps)
    new_packages <- setdiff(new_revdeps$child, known_packages)
  }
  all_revdeps
}

shiny_revdeps <- get_all_revdeps("shiny")
shiny_family <- sort(union(
  shiny_revdeps$parent,
  shiny_revdeps$child
))

package_details <- tools::CRAN_package_db() |> 
  tibble::as_tibble() |> 
  dplyr::distinct(Package, .keep_all = TRUE) |>
  dplyr::filter(Package %in% shiny_family) |> 
  janitor::clean_names() |> 
  janitor::remove_empty("cols")

readr::write_csv(
  shiny_revdeps,
  fs::path(working_dir, "shiny_revdeps.csv")
)
readr::write_csv(
  package_details,
  fs::path(working_dir, "package_details.csv")
)