Package 'suggests'

List places where dependencies are used

Description

A quick-and-dirty diagnostic tool to find dependency usage within top-level expressions (e.g. declared functions) in R scripts within a development package.

Usage

find_deps(path = ".", threshold = NULL)

Arguments

path	Path to the base directory of a package.
threshold	Only report on dependencies used in fewer than this many top-level expressions.

Details

This might be useful for package developers hoping to use need() in their package, and looking for good candidates for dependencies which could be moved from Imports to Suggests in the DESCRIPTION file.

Dependencies are searched for in two ways:

• import() and importFrom() statements in the package's NAMESPACE file, such as those created by ⁠@import⁠ and ⁠@importFrom⁠ tags if creating package documentation with roxygen2

• Functions called by using :: or ::: to access a dependency's namespace directly

This approach isn't perfect, but it should capture most dependency uses.

Value

A data frame, with one row per distinct top-level expression where a package is used. Packages used in the fewest places are listed first.

Examples

find_deps(system.file("demopkg", package = "suggests"))

---

Check whether packages are installed

Description

Initially, utils::packageVersion() is used to try to retrieve a version from a package's DESCRIPTION file. This is a fast method, but doesn't categorically guarantee that the package is actually available to use.

If load = TRUE, then base::requireNamespace() is used to try to load the namespace of each package in turn. This is much slower, but is the closest we can get to ensuring that the package is genuinely usable.

Usage

is_installed(pkgs, load = FALSE, lib.loc = NULL)

Arguments

pkgs	A character vector of package names. You can check for a minimum version by appending ⁠>=[version]⁠ to a package name - see Examples.
load	Whether to make sure packages can be loaded - significantly slower, but gives an extra level of certainty.
lib.loc	Passed to utils::packageVersion().

Value

A logical vector of the same length as pkgs, where each element is TRUE if the package is installed, and FALSE otherwise.

Examples

is_installed("base")
  is_installed(c("base", "utils"))

  is_installed("base>=3.0.0")
  is_installed(c(
    "base>=3.0.0",
    "utils"
  ))

---

Declare that packages are needed

Description

Declare that one or more packages are required by subsequent functionality; and if they're missing, either prompt the user to install them, or exit with an informative error message.

Usage

need(
  ...,
  msg = NULL,
  install_cmd = NULL,
  ask = interactive(),
  load = FALSE,
  lib.loc = NULL
)

Arguments

...	Names of required packages, as character strings. You can require a minimum version by appending ⁠>=[version]⁠ to a package name - see Examples.
msg	Custom message to display; if NULL, an informative one will be constructed.
install_cmd	Installation command to run, as a call (i.e. probably wrapped with quote() or substitute()). If NULL, install.packages() will be used for package installation.
ask	Whether to give the user the option of installing the required packages immediately.
load	Whether to make sure packages can be loaded - significantly slower, but gives an extra level of certainty.
lib.loc	Passed to utils::packageVersion().

Value

Invisibly, any package names from ... which were installed.

Examples

## Not run: 
  need("dplyr")
  need("dplyr", "tidyr")

  # All unnamed arguments will be combined into one list of package names
  shared_deps <- c("dplyr", "tidyr")
  need(shared_deps, "stringr") # same as need("dplyr", "tidyr", "stringr")

  # You can require a minimum version for some or all packages
  need("dplyr>=1.0.0", "tidyr")


  # Typically you'll want to use need() within a function
  read_data <- function(path, clean_names = FALSE) {

    # Call need() as early as possible, to avoid wasted work
    if (isTRUE(clean_names))
      suggests::need("janitor")

    output <- utils::read.csv(path)

    if (isTRUE(clean_names))
      output <- janitor::clean_names(output)

    output
  }


  # You can provide a custom message and/or installation command if needed
  need(
    "dplyr",
    msg = "We need the development version of dplyr, for now!",
    install_cmd = quote(remotes::install_github("tidyverse/dplyr"))
  )


## End(Not run)

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