Package 'pkgcache'

Description

Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.

Details

Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.

Installation

You can install the released version of pkgcache from CRAN with:

install.packages("pkgcache")

If you need the development version, you can install it from GitHub with:

pak::pak("r-lib/pkgcache")

Metadata cache

meta_cache_list() lists all packages in the metadata cache. It includes Bioconductor package, and all versions (i.e. both binary and source) of the packages for the current platform and R version.

(We load the pillar package, because it makes the pkgcache data frames print nicer, similarly to tibbles.)

library(pkgcache)
library(pillar)
meta_cache_list()
#> # A data frame: 48,094 x 32
#>    package     version depends suggests license imports linkingto archs enhances
#>    <chr>       <chr>   <chr>   <chr>    <chr>   <chr>   <chr>     <chr> <chr>   
#>  1 A3          1.0.0   R (>= ~ randomF~ GPL (>~ <NA>    <NA>      <NA>  <NA>    
#>  2 AATtools    0.0.2   R (>= ~ <NA>     GPL-3   magrit~ <NA>      <NA>  <NA>    
#>  3 ABACUS      1.0.0   R (>= ~ rmarkdo~ GPL-3   ggplot~ <NA>      <NA>  <NA>    
#>  4 ABC.RAP     0.9.0   R (>= ~ knitr, ~ GPL-3   graphi~ <NA>      <NA>  <NA>    
#>  5 ABCanalysis 1.2.1   R (>= ~ <NA>     GPL-3   plotrix <NA>      <NA>  <NA>    
#>  6 ABCoptim    0.15.0  <NA>    testtha~ MIT + ~ Rcpp, ~ Rcpp      ABCo~ <NA>    
#>  7 ABCp2       1.2     MASS    <NA>     GPL-2   <NA>    <NA>      <NA>  <NA>    
#>  8 ABHgenotyp~ 1.0.1   <NA>    knitr, ~ GPL-3   ggplot~ <NA>      <NA>  <NA>    
#>  9 ABM         0.4.1   <NA>    <NA>     GPL (>~ R6, Rc~ Rcpp      ABM.~ <NA>    
#> 10 ABPS        0.3     <NA>    testthat GPL (>~ kernlab <NA>      <NA>  <NA>    
#> # i 48,084 more rows
#> # i 23 more variables: license_restricts_use <chr>, priority <chr>,
#> #   license_is_foss <chr>, os_type <chr>, repodir <chr>, rversion <chr>,
#> #   platform <chr>, needscompilation <chr>, ref <chr>, type <chr>,
#> #   direct <lgl>, status <chr>, target <chr>, mirror <chr>, sources <list>,
#> #   filesize <int>, sha256 <chr>, sysreqs <chr>, built <chr>, published <dttm>,
#> #   deps <list>, md5sum <chr>, path <chr>

meta_cache_deps() and meta_cache_revdeps() can be used to look up dependencies and reverse dependencies.

The metadata is updated automatically if it is older than seven days, and it can also be updated manually with meta_cache_update().

See the cranlike_metadata_cache R6 class for a lower level API, and more control.

Package cache

Package management tools may use the ⁠pkg_cache_*⁠ functions and in particular the package_cache class, to make use of local caching of package files.

The ⁠pkg_cache_*⁠ API is high level, and uses a user level cache:

pkg_cache_summary()
#> $cachepath
#> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/pkg"
#> 
#> $files
#> [1] 40
#> 
#> $size
#> [1] 61300737

pkg_cache_list()
#> # A data frame: 40 x 11
#>    fullpath    path  package url   etag  sha256 version platform built vignettes
#>    <chr>       <chr> <chr>   <chr> <chr> <chr>  <chr>   <chr>    <int>     <int>
#>  1 /Users/gab~ arch~ <NA>    http~ "\"1~ 9da51~ <NA>    <NA>        NA        NA
#>  2 /Users/gab~ bin/~ cli     http~ "\"1~ b24b4~ 3.6.2   x86_64-~    NA        NA
#>  3 /Users/gab~ bin/~ jose    http~ "\"7~ b1bac~ 1.2.0   aarch64~    NA        NA
#>  4 /Users/gab~ src/~ gh      <NA>   <NA> <NA>   1.4.0.~ source       1         0
#>  5 /Users/gab~ src/~ gh      <NA>   <NA> <NA>   1.4.0.~ aarch64~     1         0
#>  6 /Users/gab~ bin/~ gh      http~ "\"1~ f5daf~ 1.4.0   aarch64~    NA        NA
#>  7 /Users/gab~ src/~ tic     <NA>   <NA> 11103~ <NA>    <NA>         0        NA
#>  8 /Users/gab~ src/~ tic     <NA>   <NA> 11103~ 0.14.0  source       1         0
#>  9 /Users/gab~ src/~ tic     <NA>   <NA> 11103~ 0.14.0  aarch64~     1         0
#> 10 /Users/gab~ bin/~ rhub    http~ "\"f~ af2d6~ 1.1.2   aarch64~    NA        NA
#> # i 30 more rows
#> # i 1 more variable: rversion <chr>

pkg_cache_find(package = "dplyr")
#> # A data frame: 0 x 11
#> # i 11 variables: fullpath <chr>, path <chr>, package <chr>, url <chr>,
#> #   etag <chr>, sha256 <chr>, version <chr>, platform <chr>, built <int>,
#> #   vignettes <int>, rversion <chr>

pkg_cache_add_file() can be used to add a file, pkg_cache_delete_files() to remove files, pkg_cache_get_files() to copy files out of the cache.

The package_cache class provides a finer API.

Installed packages

pkgcache contains a very fast DCF parser to parse ⁠PACKAGES*⁠ files, or the DESCRIPTION files in installed packages. parse_packages() parses all fields from PACKAGES, PACKAGES.gz or PACKAGES.rds files. parse_installed() reads all metadata from packages installed into a library:

parse_installed()
#> # A data frame: 888 x 128
#>    Package  Type  Title Version Date  `Authors@R` Maintainer Description Imports
#>    <chr>    <chr> <chr> <chr>   <chr> <chr>       <chr>      <chr>       <chr>  
#>  1 AdaptGa~ Pack~ Gaus~ 1.6     2024~ "c(person(~ Michael T~ "Multimoda~ "Rcpp,~
#>  2 Annotat~ <NA>  Mani~ 1.64.1  <NA>   <NA>       Bioconduc~ "Implement~ "DBI, ~
#>  3 Annotat~ <NA>  Tool~ 1.42.2  <NA>   <NA>       Bioconduc~ "Provides ~ "DBI, ~
#>  4 AsioHea~ Pack~ 'Asi~ 1.22.1~ 2022~  <NA>       Dirk Edde~ "'Asio' is~  <NA>  
#>  5 AutoQua~ <NA>  Auto~ 1.0.1   2023~ "\n    c(p~ Adrian An~ "R package~ "bit64~
#>  6 BH       Pack~ Boos~ 1.81.0~ 2023~  <NA>       Dirk Edde~ "Boost pro~  <NA>  
#>  7 BayesFa~ Pack~ Comp~ 0.9.12~ 2022~ "c(person(~ Richard D~ "A suite o~ "pbapp~
#>  8 Biobase  <NA>  Biob~ 2.62.0  <NA>  "c(\n    p~ Bioconduc~ "Functions~ "metho~
#>  9 BiocBas~ <NA>  Gene~ 1.4.0   <NA>  "c(\n  per~ Marcel Ra~ "The packa~ "metho~
#> 10 BiocFil~ <NA>  Mana~ 2.10.1  <NA>  "c(person(~ Lori Shep~ "This pack~ "metho~
#> # i 878 more rows
#> # i 119 more variables: Suggests <chr>, LinkingTo <chr>, Depends <chr>,
#> #   License <chr>, LazyLoad <chr>, URL <chr>, Encoding <chr>,
#> #   NeedsCompilation <chr>, VignetteBuilder <chr>, BugReports <chr>,
#> #   Packaged <chr>, Author <chr>, Repository <chr>, `Date/Publication` <chr>,
#> #   Built <chr>, Archs <chr>, RemoteType <chr>, RemotePkgRef <chr>,
#> #   RemoteRef <chr>, RemoteRepos <chr>, RemotePkgPlatform <chr>, ...

Bioconductor support

Both the metadata cache and the package cache support Bioconductor by default, automatically. See the BioC_mirror option and the R_BIOC_MIRROR and R_BIOC_VERSION environment variables below to configure Bioconductor support.

Package Options

• The BioC_mirror option can be used to select a Bioconductor mirror. This takes priority over the R_BIOC_MIRROR environment variable.

• You can use the pkg.current_platform option to set the platform string for the current platform for the current_r_platform() function. This is useful if pkgcache didn’t detect the platform correctly. Alternatively, you can use the PKG_CURRENT_PLATFORM environment variable. The option takes priority.

• pkgcache_timeout is the HTTP timeout for all downloads. It is in seconds, and the limit for downloading the whole file. Defaults to 3600, one hour. It corresponds to the TIMEOUT libcurl option.

• pkgcache_connecttimeout is the HTTP timeout for the connection phase. It is in seconds and defaults to 30 seconds. It corresponds to the CONNECTTIMEOUT libcurl option.

• pkgcache_low_speed_limit and pkgcache_low_speed_time are used for a more sensible HTTP timeout. If the download speed is less than pkgcache_low_speed_limit bytes per second for at least pkgcache_low_speed_time seconds, the download errors. They correspond to the LOW_SPEED_LIMIT and LOW_SPEED_TIME curl options.

Package environment variables

• The R_BIOC_VERSION environment variable can be used to override the default Bioconductor version detection and force a given version. E.g. this can be used to force the development version of Bioconductor.

• The R_BIOC_MIRROR environment variable can be used to select a Bioconductor mirror. The BioC_mirror option takes priority over this, if set.

• You can use the PKG_CURRENT_PLATFORM environment variable to set the platform string for the current platform for the current_r_platform() function. This is useful if pkgcache didn’t detect the platform correctly. Alternatively, you can use the pkg.current_platofrm option, which takes. priority over the environment variable.

• PKGCACHE_PPM_REPO is the name of the Posit Package Manager repository to use. Defaults to "cran".

• PKGCACHE_PPM_URL is the base URL of the Posit Package Manager instance to use. It defaults to the URL of the Posit Public Package Manager instance at https://packagemanager.posit.co/client/#/.

• PKGCACHE_TIMEOUT is the HTTP timeout for all downloads. It is in seconds, and the limit for downloading the whole file. Defaults to 3600, one hour. It corresponds to the TIMEOUT libcurl option. The pkgcache_timeout option has priority over this, if set.

• PKGCACHE_CONNECTTIMEOUT is the HTTP timeout for the connection phase. It is in seconds and defaults to 30 seconds. It corresponds to the CONNECTTIMEOUT libcurl option. The pkgcache_connecttimeout option takes precedence over this, if set.

• PKGCACHE_LOW_SPEED_LIMIT and PKGCACHE_LOW_SPEED_TIME are used for a more sensible HTTP timeout. If the download speed is less than PKGCACHE_LOW_SPEED_LIMIT bytes per second for at least PKGCACHE_LOW_SPEED_TIME seconds, the download errors. They correspond to the LOW_SPEED_LIMIT and LOW_SPEED_TIME curl options. The pkgcache_low_speed_time and pkgcache_low_speed_limit options have priority over these environment variables, if they are set.

• R_PKG_CACHE_DIR is used for the cache directory, if set. (Otherwise tools::R_user_dir("pkgcache", "cache") is used, see also meta_cache_summary() and pkg_cache_summary()).

Using pkgcache in CRAN packages

If you use pkgcache in your CRAN package, please make sure that

• you don’t use pkgcache in your examples, and

• you set the R_USER_CACHE_DIR environment variable to a temporary directory (e.g. via tempfile()) during test cases. See the tests/testthat/setup.R file in pkgcache for an example.

This is to make sure that pkgcache does not modify the user’s files while running ⁠R CMD check⁠.

Code of Conduct

Please note that the pkgcache project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

MIT (c) Posit Software, PBC

Author(s)

Maintainer: Gábor Csárdi [email protected]

Other contributors:

• Posit Software, PBC [copyright holder, funder]

See Also

Useful links:

• https://r-lib.github.io/pkgcache/

• https://github.com/r-lib/pkgcache

• Report bugs at https://github.com/r-lib/pkgcache/issues

Description

Various helper functions to deal with Bioconductor repositories. See https://www.bioconductor.org/ for more information on Bioconductor.

Usage

bioc_version(r_version = getRversion(), forget = FALSE)

bioc_version_map(forget = FALSE)

bioc_devel_version(forget = FALSE)

bioc_release_version(forget = FALSE)

bioc_repos(bioc_version = "auto", forget = FALSE)

Arguments

Details

bioc_version() queries the matching Bioconductor version for an R version, defaulting to the current R version

bioc_version_map() returns the current mapping between R versions and Bioconductor versions.

bioc_devel_version() returns the version number of the current Bioconductor devel version.

bioc_release_version() returns the version number of the current Bioconductor release.

bioc_repos() returns the Bioconductor repository URLs.

See the BioC_mirror option and the R_BIOC_MIRROR and R_BIOC_VERSION environment variables in the pkgcache manual page. They can be used to customize the desired Bioconductor version.

Value

bioc_version() returns a package_version object.

bioc_version_map() returns a data frame with columns:

• bioc_version: package_version object, Bioconductor versions.

• r_version: package_version object, the matching R versions.

• bioc_status: factor, with levels: out-of-date, release, devel, future.

bioc_devel_version() returns a package_version object.

bioc_release_version() returns a package_version object.

bioc_repos() returns a named character vector.

Examples

bioc_version()
bioc_version("4.0")
bioc_version("4.1")


bioc_version_map()


bioc_devel_version()


bioc_release_version()


bioc_repos()

Description

This is an R6 class that implements a cache from older CRAN package versions. For a higher level interface see the functions documented with cran_archive_list().

Details

The cache is similar to cranlike_metadata_cache and has the following layers:

• The data inside the cran_archive_cache object.

• Cached data in the current R session.

• An RDS file in the current session's temporary directory.

• An RDS file in the user's cache directory.

It has a synchronous and an asynchronous API.

Usage

cac <- cran_archive_cache$new(
  primary_path = NULL,
  replica_path = tempfile(),
  cran_mirror = default_cran_mirror(),
  update_after = as.difftime(7, units = "days"),
)

cac$list(packages = NULL, update_after = NULL)
cac$async_list(packages = NULL, update_after = NULL)

cac$update()
cac$async_update()

cac$check_update()
cac$async_check_update()

cac$summary()

cac$cleanup(force = FALSE)

Arguments

• primary_path: Path of the primary, user level cache. Defaults to the user level cache directory of the machine.

• replica_path: Path of the replica. Defaults to a temporary directory within the session temporary directory.

• cran_mirror: CRAN mirror to use, this takes precedence over repos.

• update_after: difftime object. Automatically update the cache if it gets older than this. Set it to Inf to avoid updates. Defaults to seven days.

• packages: Packages to query, character vector.

• force: Whether to force cleanup without asking the user.

Details

Create a new archive cache with cran_archive_cache$new(). Multiple caches are independent, so e.g. if you update one of them, the other existing caches are not affected.

cac$list() lists the versions of the specified packages, or all packages, if none were specified. cac$async_list() is the same, but asynchronous.

cac$update() updates the cache. It always downloads the new metadata. cac$async_update() is the same, but asynchronous.

cac$check_update() updates the cache if there is a newer version available. cac$async_check_update() is the same, but asynchronous.

cac$summary() returns a summary of the archive cache, a list with entries:

• cachepath: path to the directory of the main archive cache,

• current_rds: the RDS file that stores the cache. (This file might not exist, if the cache is not downloaded yet.)

• lockfile: the file used for locking the cache.

• 'timestamp: time stamp for the last update of the cache.

• size: size of the cache file in bytes.

cac$cleanup() cleans up the cache files.

Columns

cac$list() returns a data frame with columns:

• package: package name,

• version: package version. This is a character vector, and not a package_version() object. Some older package versions are not supported by package_version().

• raw: the raw row names from the CRAN metadata.

• mtime: mtime column from the CRAN metadata. This is usually pretty close to the release date and time of the package.

• url: package download URL.

• mirror: CRAN mirror that was used to get this data.

Examples

arch <- cran_archive_cache$new()
arch$update()
arch$list()

Description

CRAN mirrors store older versions of packages in ⁠/src/contrib/Archive⁠, and they also store some metadata about them in ⁠/src/contrib/Meta/archive.rds⁠. pkgcache can download and cache this metadata.

Usage

cran_archive_list(
  cran_mirror = default_cran_mirror(),
  update_after = as.difftime(7, units = "days"),
  packages = NULL
)

cran_archive_update(cran_mirror = default_cran_mirror())

cran_archive_cleanup(cran_mirror = default_cran_mirror(), force = FALSE)

cran_archive_summary(cran_mirror = default_cran_mirror())

Arguments

Details

cran_archive_list() lists all versions of all (or some) packages. It updates the cached data first, if it is older than the specified limit.

cran_archive_update() updates the archive cache.

cran_archive_cleanup() cleans up the archive cache for cran_mirror.

cran_archive_summary() prints a summary about the archive cache.

Value

cran_archive_list() returns a data frame with columns:

• package: package name,

• version: package version. This is a character vector, and not a package_version() object. Some older package versions are not supported by package_version().

• raw: the raw row names from the CRAN metadata.

• mtime: mtime column from the CRAN metadata. This is usually pretty close to the release date and time of the package.

• url: package download URL.

• mirror: CRAN mirror that was used to get this data. The output is ordered according to package names (case insensitive) and release dates.

cran_archive_update() returns all archive data in a data frame, in the same format as cran_archive_list(), invisibly.

cran_archive_cleanup() returns nothing.

cran_archive_summary() returns a named list with elements:

• cachepath: Path to the directory that contains all archive cache.

• current_rds: Path to the RDS file that contains the data for the specified cran_mirror.

• lockfile: Path to the lock file for current_rds.

• timestamp: Path to the time stamp for current_rds. NA if the cache is empty.

• size: Size of current_rds. Zero if the cache is empty.

See Also

The cran_archive_cache class for more flexibility.

Examples

cran_archive_list(packages = "readr")

Description

This is an R6 class that implements the metadata cache of a CRAN-like repository. For a higher level interface, see the meta_cache_list(), meta_cache_deps(), meta_cache_revdeps() and meta_cache_update() functions.

Details

The cache has several layers:

• The data is stored inside the cranlike_metadata_cache object.

• It is also stored as an RDS file, in the session temporary directory. This ensures that the same data is used for all queries of a cranlike_metadata_cache object.

• It is stored in an RDS file in the user's cache directory.

• The downloaded raw ⁠PACKAGES*⁠ files are cached, together with HTTP ETags, to minimize downloads.

It has a synchronous and an asynchronous API.

Usage

cmc <- cranlike_metadata_cache$new(
  primary_path = NULL, replica_path = tempfile(),
  platforms = default_platforms(), r_version = getRversion(),
  bioc = TRUE, cran_mirror = default_cran_mirror(),
  repos = getOption("repos"),
  update_after = as.difftime(7, units = "days"))

cmc$list(packages = NULL)
cmc$async_list(packages = NULL)

cmc$deps(packages, dependencies = NA, recursive = TRUE)
cmc$async_deps(packages, dependencies = NA, recursive = TRUE)

cmc$revdeps(packages, dependencies = NA, recursive = TRUE)
cmc$async_revdeps(packages, dependencies = NA, recursive = TRUE)

cmc$update()
cmc$async_update()
cmc$check_update()
cmc$asnyc_check_update()

cmc$summary()

cmc$cleanup(force = FALSE)

Arguments

• primary_path: Path of the primary, user level cache. Defaults to the user level cache directory of the machine.

• replica_path: Path of the replica. Defaults to a temporary directory within the session temporary directory.

• platforms: see default_platforms() for possible values.

• r_version: R version to create the cache for.

• bioc: Whether to include BioConductor packages.

• cran_mirror: CRAN mirror to use, this takes precedence over repos.

• repos: Repositories to use.

• update_after: difftime object. Automatically update the cache if it gets older than this. Set it to Inf to avoid updates. Defaults to seven days.

• packages: Packages to query, character vector.

• dependencies: Which kind of dependencies to include. Works the same way as the dependencies argument of utils::install.packages().

• recursive: Whether to include recursive dependencies.

• force: Whether to force cleanup without asking the user.

Details

cranlike_metadata_cache$new() creates a new cache object. Creation does not trigger the population of the cache. It is only populated on demand, when queries are executed against it. In your package, you may want to create a cache instance in the .onLoad() function of the package, and store it in the package namespace. As this is a cheap operation, the package will still load fast, and then the package code can refer to the common cache object.

cmc$list() lists all (or the specified) packages in the cache. It returns a data frame, see the list of columns below.

cmc$async_list() is similar, but it is asynchronous, it returns a deferred object.

cmc$deps() returns a data frame, with the (potentially recursive) dependencies of packages.

cmc$async_deps() is the same, but it is asynchronous, it returns a deferred object.

cmc$revdeps() returns a data frame, with the (potentially recursive) reverse dependencies of packages.

cmc$async_revdeps() does the same, asynchronously, it returns an deferred object.

cmc$update() updates the the metadata (as needed) in the cache, and then returns a data frame with all packages, invisibly.

cmc$async_update() is similar, but it is asynchronous.

cmc$check_update() checks if the metadata is current, and if it is not, it updates it.

cmc$async_check_update() is similar, but it is asynchronous.

cmc$summary() lists metadata about the cache, including its location and size.

cmc$cleanup() deletes the cache files from the disk, and also from memory.

Columns

The metadata data frame contains all available versions (i.e. sources and binaries) for all packages. It usually has the following columns, some might be missing on some platforms.

• package: Package name.

• title: Package title.

• version: Package version.

• depends: Depends field from DESCRIPTION, or NA_character_.

• suggests: Suggests field from DESCRIPTION, or NA_character_.

• built: Built field from DESCIPTION, if a binary package, or NA_character_.

• imports: Imports field from DESCRIPTION, or NA_character_.

• archs: Archs entries from PACKAGES files. Might be missing.

• repodir: The directory of the file, inside the repository.

• platform: This is a character vector. See default_platforms() for more about platform names. In practice each value of the platform column is either

  • "source" for source packages,

  • a platform string, e.g. x86_64-apple-darwin17.0 for macOS packages compatible with macOS High Sierra or newer.

• needscompilation: Whether the package needs compilation.

• type: bioc or cran currently.

• target: The path of the package file inside the repository.

• mirror: URL of the CRAN/BioC mirror.

• sources: List column with URLs to one or more possible locations of the package file. For source CRAN packages, it contains URLs to the Archive directory as well, in case the package has been archived since the metadata was cached.

• filesize: Size of the file, if known, in bytes, or NA_integer_.

• sha256: The SHA256 hash of the file, if known, or NA_character_.

• deps: All package dependencies, in a data frame.

• license: Package license, might be NA for binary packages.

• linkingto: LinkingTo field from DESCRIPTION, or NA_character_.

• enhances: Enhances field from DESCRIPTION, or NA_character_.

• os_type: unix or windows for OS specific packages. Usually NA.

• priority: "optional", "recommended" or NA. (Base packages are normally not included in the list, so "base" should not appear here.)

• md5sum: MD5 sum, if available, may be NA.

• sysreqs: The SystemRequirements field, if available. This lists the required system libraries or other software for the package. This is usually available for CRAN and Bioconductor package and when it is explicitly available in the repository metadata.

• published: The time the package was published at, in GMT, POSIXct class.

The data frame contains some extra columns as well, these are for internal use only.

Examples

dir.create(cache_path <- tempfile())
cmc <- cranlike_metadata_cache$new(cache_path, bioc = FALSE)
cmc$list()
cmc$list("pkgconfig")
cmc$deps("pkgconfig")
cmc$revdeps("pkgconfig", recursive = FALSE)

Description

R platforms

Usage

current_r_platform()

current_r_platform_data()

default_platforms()

Details

current_r_platform() detects the platform of the current R version. current_r_platform_data() is similar, but returns the raw data instead of a character scalar.

By default pkgcache works with source packages and binary packages for the current platform. You can change this, by providing different platform names as arguments to cranlike_metadata_cache$new(), repo_status(), etc.

These functions accept the following platform names:

• "source" for source packages,

• "macos" for macOS binaries that are appropriate for the R versions pkgcache is working with. Packages for incompatible CPU architectures are dropped (defaulting to the CPU of the current macOS machine and x86_64 on non-macOS systems). The macOS Darwin version is selected based on the CRAN macOS binaries. E.g. on R 3.5.0 macOS binaries are built for macOS El Capitan.

• "windows" for Windows binaries for the default CRAN architecture. This is currently Windows Vista for all supported R versions, but it might change in the future. The actual binary packages in the repository might support both 32 bit and 64 builds, or only one of them. In practice 32-bit only packages are very rare. CRAN builds before and including R 4.1 have both architectures, from R 4.2 they are 64 bit only. "windows" is an alias to i386+x86_64-w64-mingw32 currently.

• A platform string like R.version$platform, but on Linux the name and version of the distribution are also included. Examples:

  • x86_64-apple-darwin17.0: macOS High Sierra.

  • aarch64-apple-darwin20: macOS Big Sur on arm64.

  • x86_64-w64-mingw32: 64 bit Windows.

  • i386-w64-mingw32: 32 bit Windows.

  • i386+x86_64-w64-mingw32: 64 bit + 32 bit Windows.

  • i386-pc-solaris2.10: 32 bit Solaris. (Some broken 64 Solaris builds might have the same platform string, unfortunately.)

  • x86_64-pc-linux-gnu-debian-10: Debian Linux 10 on x86_64.

  • ⁠x86_64-pc-linux-musl-alpine-3.14.1⁠: Alpine Linux.

  • x86_64-pc-linux-gnu-unknown: Unknown Linux Distribution on x86_64.

  • s390x-ibm-linux-gnu-ubuntu-20.04: Ubuntu Linux 20.04 on S390x.

  • amd64-portbld-freebsd12.1: FreeBSD 12.1 on x86_64.

default_platfoms() returns the default platforms for the current R session. These typically consist of the detected platform of the current R session, and "source", for source packages.

Value

current_r_platform() returns a character scalar.

current_r_platform_data() returns a data frame with character scalar columns:

• cpu,

• vendor,

• os,

• distribution (only on Linux),

• release (only on Linux),

• platform: the concatenation of the other columns, separated by a dash.

default_platforms() returns a character vector of the default platforms.

Examples

current_r_platform()
default_platforms()

Description

If options("repos") (see options()) contains an entry called "CRAN", then that is returned. If it is a list, it is converted to a character vector.

Usage

default_cran_mirror()

Details

Otherwise the RStudio CRAN mirror is used.

Value

A named character vector of length one, where the name is "CRAN".

Examples

default_cran_mirror()

Description

This is used by the meta_cache_deps(), meta_cache_list(), etc. functions.

Usage

get_cranlike_metadata_cache()

Examples

get_cranlike_metadata_cache()
get_cranlike_metadata_cache()$list("cli")

Description

A package compiled with a certain version of the graphics API will not work with R installations that use a different version.

Usage

get_graphics_api_version()

Value

An integer scalar, the version of the graphics API of this R version.

Examples

get_graphics_api_version()

Description

Packages need to be recompiled if this id changes.

Usage

get_internals_id()

Value

String, a UUID.

Examples

get_internals_id()

Description

It uses CRAN and BioConductor packages, for the current platform and R version, from the default repositories.

Usage

meta_cache_deps(packages, dependencies = NA, recursive = TRUE)

meta_cache_revdeps(packages, dependencies = NA, recursive = TRUE)

meta_cache_update()

meta_cache_list(packages = NULL)

meta_cache_cleanup(force = FALSE)

meta_cache_summary()

Arguments

Details

meta_cache_list() lists all packages.

meta_cache_update() updates all metadata. Note that metadata is automatically updated if it is older than seven days.

meta_cache_deps() queries packages dependencies.

meta_cache_revdeps() queries reverse package dependencies.

meta_cache_summary() lists data about the cache, including its location and size.

meta_cache_cleanup() deletes the cache files from the disk.

Value

A data frame of the dependencies. For meta_cache_deps() and meta_cache_revdeps() it includes the queried packages as well.

Examples

meta_cache_list("pkgdown")
meta_cache_deps("pkgdown", recursive = FALSE)
meta_cache_revdeps("pkgdown", recursive = FALSE)

Description

This is an R6 class that implements a concurrency safe package cache.

Details

By default these fields are included for every package:

• fullpath Full package path.

• path Package path, within the repository.

• package Package name.

• url URL it was downloaded from.

• etag ETag for the last download, from the given URL.

• sha256 SHA256 hash of the file.

Additional fields can be added as needed.

For a simple API to a session-wide instance of this class, see pkg_cache_summary() and the other functions listed there.

Usage

pc <- package_cache$new(path = NULL)

pc$list()
pc$find(..., .list = NULL)
pc$copy_to(..., .list = NULL)
pc$add(file, path, sha256 = shasum256(file), ..., .list = NULL)
pc$add_url(url, path, ..., .list = NULL, on_progress = NULL,
  http_headers = NULL)
pc$async_add_url(url, path, ..., .list = NULL, on_progress = NULL,
  http_headers = NULL)
pc$copy_or_add(target, urls, path, sha256 = NULL, ..., .list = NULL,
               on_progress = NULL, http_headers = NULL)
pc$async_copy_or_add(target, urls, path, ..., sha256 = NULL, ...,
               .list = NULL, on_progress = NULL, http_headers = NULL)
pc$update_or_add(target, urls, path, ..., .list = NULL,
               on_progress = NULL, http_headers = NULL)
pc$async_update_or_add(target, urls, path, ..., .list = NULL,
               on_progress = NULL, http_headers = NULL)
pc$delete(..., .list = NULL)

Arguments

• path: For package_cache$new() the location of the cache. For other functions the location of the file inside the cache.

• ...: Extra attributes to search for. They have to be named.

• .list: Extra attributes to search for, they have to in a named list.

• file: Path to the file to add.

• url: URL attribute. This is used to update the file, if requested.

• sha256: SHA256 hash of the file.

• on_progress: Callback to create progress bar. Passed to internal function http_get().

• target: Path to copy the (first) to hit to.

• urls: Character vector or URLs to try to download the file from.

• http_headers: HTTP headers to add to all HTTP queries.

Details

package_cache$new() attaches to the cache at path. (By default a platform dependent user level cache directory.) If the cache does not exists, it creates it.

pc$list() lists all files in the cache, returns a data frame with all the default columns, and potentially extra columns as well.

pc$find() list all files that match the specified criteria (fullpath, path, package, etc.). Custom columns can be searched for as well.

pc$copy_to() will copy the first matching file from the cache to target. It returns the data frame of all matching records, invisibly. If no file matches, it returns an empty (zero-row) data frame.

pc$add() adds a file to the cache.

pc$add_url() downloads a file and adds it to the cache.

pc$async_add_url() is the same, but it is asynchronous.

pc$copy_or_add() works like pc$copy_to(), but if the file is not in the cache, it tries to download it from one of the specified URLs first.

pc$async_copy_or_add() is the same, but asynchronous.

pc$update_or_add() is like pc$copy_to_add(), but if the file is in the cache it tries to update it from the urls, using the stored ETag to avoid unnecessary downloads.

pc$async_update_or_add() is the same, but it is asynchronous.

pc$delete() deletes the file(s) from the cache.

Examples

## Although package_cache usually stores packages, it may store
## arbitrary files, that can be search by metadata
pc <- package_cache$new(path = tempfile())
pc$list()

cat("foo\n", file = f1 <- tempfile())
cat("bar\n", file = f2 <- tempfile())
pc$add(f1, "/f1")
pc$add(f2, "/f2")
pc$list()
pc$find(path = "/f1")
pc$copy_to(target = f3 <- tempfile(), path = "/f1")
readLines(f3)

Description

This function is similar to utils::installed.packages(). See the differences below.

Usage

parse_installed(
  library = .libPaths(),
  priority = NULL,
  lowercase = FALSE,
  reencode = TRUE,
  packages = NULL
)

Arguments

Details

Differences with utils::installed.packages():

• parse_installed() cannot subset the extracted fields. (But you can subset the result.)

• parse_installed() does not cache the results.

• parse_installed() handles errors better. See Section 'Errors' below. #' * parse_installed() uses the DESCRIPTION files in the installed packages instead of the Meta/package.rds files. This should not matter, but because of a bug Meta/package.rds might contain the wrong Archs field on multi-arch platforms.

• parse_installed() reads all fields from the DESCRIPTION files. utils::installed.packages() only reads the specified fields.

• parse_installed() converts its output to UTF-8 encoding, from the encodings declared in the DESCRIPTION files.

• parse_installed() is considerably faster.

Encodings

parse_installed() always returns its result in UTF-8 encoding. It uses the Encoding fields in the DESCRIPTION files to learn their encodings. parse_installed() does not check that an UTF-8 file has a valid encoding. If it fails to convert a string to UTF-8 from another declared encoding, then it leaves it as "bytes" encoded, without a warning.

Errors

pkgcache silently ignores files and directories inside the library directory.

The result also omits broken package installations. These include

• packages with invalid DESCRIPTION files, and

• packages the current user have no access to.

These errors are reported via a condition with class pkgcache_broken_install. The condition has an errors entry, which is a data frame with columns

• file: path to the DESCRIPTION file of the broken package,

• error: error message for this particular failure.

If you intend to handle broken package installation, you need to catch this condition with withCallingHandlers().

Description

Parse a repository metadata ⁠PACAKGES*⁠ file

Usage

parse_packages(path, type = NULL)

Arguments

Details

Non-existent, unreadable or corrupt PACKAGES files with trigger an error.

⁠PACKAGES*⁠ files do not usually declare an encoding, but nevertheless parse_packages() works correctly if they do.

Value

A data frame, with all columns from the file at path.

Note

parse_packages() cannot currently read files that have very many different fields (many columns in the result data frame). The current limit is 1000. Typical PACKAGES files contain less than 20 field types.

Description

pkg_cache_summary() returns a short summary of the state of the cache, e.g. the number of files and their total size. It returns a named list.

Usage

pkg_cache_summary(cachepath = NULL)

pkg_cache_list(cachepath = NULL)

pkg_cache_find(cachepath = NULL, ...)

pkg_cache_get_file(cachepath = NULL, target, ...)

pkg_cache_delete_files(cachepath = NULL, ...)

pkg_cache_add_file(cachepath = NULL, file, relpath = dirname(file), ...)

Arguments

See Also

The package_cache R6 class for a more flexible API.

Examples

pkg_cache_summary()
pkg_cache_list()
pkg_cache_find(package = "forecast")
tmp <- tempfile()
pkg_cache_get_file(target = tmp, package = "forecast", version = "8.10")
pkg_cache_delete_files(package = "forecast")

Description

Does PPM build binary packages for the current platform?

Usage

ppm_has_binaries()

Value

TRUE or FALSE.

See Also

The 'pkgcache and Posit Package Manager on Linux' article at https://r-lib.github.io/pkgcache/dev/.

Other PPM functions: ppm_platforms(), ppm_r_versions(), ppm_repo_url(), ppm_snapshots()

Examples

current_r_platform()
ppm_has_binaries()

Description

List all platforms supported by Posit Package Manager (PPM)

Usage

ppm_platforms()

Value

Data frame with columns:

• name: platform name, this is essentially an identifier,

• os: operating system, linux, windows or macOS currently,

• binary_url: the URL segment of the binary repository URL of this platform, see ppm_snapshots().

• distribution: for Linux platforms the name of the distribution,

• release: for Linux platforms, the name of the release,

• binaries: whether PPM builds binaries for this platform.

See Also

The 'pkgcache and Posit Package Manager on Linux' article at https://r-lib.github.io/pkgcache/dev/.

Other PPM functions: ppm_has_binaries(), ppm_r_versions(), ppm_repo_url(), ppm_snapshots()

Examples

ppm_platforms()

Description

List all R versions supported by Posit Package Manager (PPM)

Usage

ppm_r_versions()

Value

Data frame with columns:

• r_version: minor R versions, i.e. version numbers containing the first two components of R versions supported by this PPM instance.

See Also

The 'pkgcache and Posit Package Manager on Linux' article at https://r-lib.github.io/pkgcache/dev/.

Other PPM functions: ppm_has_binaries(), ppm_platforms(), ppm_repo_url(), ppm_snapshots()

Examples

ppm_r_versions()

Description

Returns the current Posit Package Manager (PPM) repository URL

Usage

ppm_repo_url()

Details

This URL has the form {base}/{repo}, e.g. ⁠https://packagemanager.posit.co/all⁠.

To configure a hosted PPM instance, set the PKGCACHE_PPM_URL environment variable to the base URL (e.g. ⁠https://packagemanager.posit.co⁠).

To use repo_add() with PPM snapshots, you may also set the PKGCACHE_PPM_REPO environment variable to the name of the default repository.

On Linux, instead of setting these environment variables, you can also add a PPM repository to the repos option, see base::options(). If the environment variables are not set, then ppm_repo_url() will try to extract the PPM base URL and repository name from this option.

If the PKGCACHE_PPM_URL environment variable is not set, and the repos option does not contain a PPM URL (on Linux), then pkgcache uses the public PPM instance at ⁠https://packagemanager.posit.co⁠, with the cran repository.

Value

String scalar, the repository URL of the configured PPM instance. If no PPM instance is configured, then the URL of the Posit Public Package Manager instance. It includes the repository name, e.g. ⁠https://packagemanager.posit.co/all⁠.

See Also

The 'pkgcache and Posit Package Manager on Linux' article at https://r-lib.github.io/pkgcache/dev/.

repo_resolve() and repo_add() to find and configure PPM snapshots.

Other PPM functions: ppm_has_binaries(), ppm_platforms(), ppm_r_versions(), ppm_snapshots()

Examples

ppm_repo_url()

Description

List all available Posit Package Manager (PPM) snapshots

Usage

ppm_snapshots()

Details

The repository URL of a snapshot has the following form on Windows:

{base}/{repo}/{id}

where {base} is the base URL for PPM (see ppm_repo_url()) and {id} is either the date or id of the snapshot, or latest for the latest snapshot. E.g. these are equivalent:

https://packagemanager.posit.co/cran/5
https://packagemanager.posit.co/cran/2017-10-10

On a Linux distribution that has PPM support, the repository URL that contains the binary packages looks like this:

{base}/{repo}/__linux__/{binary_url}/{id}

where {id} is as before, and {binary_url} is a code name for a release of a supported Linux distribution. See the binary_url column of the result of ppm_platforms() for these code names.

Value

Data frame with two columns:

• date: the time the snapshot was taken, a POSIXct vector,

• id: integer id of the snapshot, this can be used in the repository URL.

See Also

The 'pkgcache and Posit Package Manager on Linux' article at https://r-lib.github.io/pkgcache/dev/.

Other PPM functions: ppm_has_binaries(), ppm_platforms(), ppm_r_versions(), ppm_repo_url()

Examples

ppm_snapshots()

Description

pkgcache uses the repos option, see options(). It also automatically uses the current Bioconductor repositories, see bioc_version(). These functions help to query and manipulate the repos option.

Usage

repo_get(
  r_version = getRversion(),
  bioc = TRUE,
  cran_mirror = default_cran_mirror()
)

repo_resolve(spec)

repo_add(..., .list = NULL)

with_repo(repos, expr)

Arguments

Details

repo_get() queries the repositories pkgcache uses. It uses the repos option (see options), and also the default Bioconductor repository.

repo_resolve() resolves a single repository specification to a repository URL.

repo_add() adds a new repository to the repos option. (To remove a repository, call option() directly, with the subset that you want to keep.)

with_repo() temporarily adds the repositories in repos, evaluates expr, and then resets the configured repositories.

Value

repo_get() returns a data frame with columns:

• name: repository name. Names are informational only.

• url: repository URL.

• type: repository type. This is also informational, currently it can be cran for CRAN, bioc for a Bioconductor repository, and cranlike: for other repositories.

• r_version: R version that is supposed to be used with this repository. This is only set for Bioconductor repositories. It is * for others. This is also informational, and not used when retrieving the package metadata.

• bioc_version: Bioconductor version. Only set for Bioconductor repositories, and it is NA for others.

repo_resolve() returns a named character vector, with the URL(s) of the repository.

repo_add() returns the same data frame as repo_get(), invisibly.

with_repo() returns the value of expr.

Repository specifications

The format of a repository specification is a named or unnamed character scalar. If the name is missing, pkgcache adds a name automatically. The repository named CRAN is the main CRAN repository, but otherwise names are informational.

Currently supported repository specifications:

• URL pointing to the root of the CRAN-like repository. Example:

  https://cloud.r-project.org
  

• PPM@latest, PPM (Posit Package Manager, formerly RStudio Package Manager), the latest snapshot.

• ⁠PPM@<date>⁠, PPM (Posit Package Manager, formerly RStudio Package Manager) snapshot, at the specified date.

• ⁠PPM@<package>-<version>⁠ PPM snapshot, for the day after the release of ⁠<version>⁠ of ⁠<package>⁠.

• ⁠PPM@R-<version>⁠ PPM snapshot, for the day after R ⁠<version>⁠ was released.

Still works for dates starting from 2017-10-10, but now deprecated, because MRAN is discontinued:

• ⁠MRAN@<date>⁠, MRAN (Microsoft R Application Network) snapshot, at the specified date.

• ⁠MRAN@<package>-<version>⁠ MRAN snapshot, for the day after the release of ⁠<version>⁠ of ⁠<package>⁠.

• ⁠MRAN@R-<version>⁠ MRAN snapshot, for the day after R ⁠<version>⁠ was released.

Notes:

• See more about PPM at https://packagemanager.posit.co/client/#/.

• The ⁠RSPM@⁠ prefix is still supported and treated the same way as ⁠PPM@⁠.

• The MRAN service is now retired, see https://techcommunity.microsoft.com/t5/azure-sql-blog/microsoft-r-application-network-retirement/ba-p/3707161 for details.

• MRAN@... repository specifications now resolve to PPM, but note that PPM snapshots are only available from 2017-10-10. See more about this at https://posit.co/blog/migrating-from-mran-to-posit-package-manager/.

• All dates (or times) can be specified in the ISO 8601 format.

• If PPM does not have a snapshot available for a date, the next available date is used.

• Dates that are before the first, or after the last PPM snapshot will trigger an error.

• Unknown R or package versions will trigger an error.

See Also

Other repository functions: repo_status()

Examples

repo_get()

repo_resolve("PPM@2021-01-21")
#' repo_resolve("[email protected]")
#' repo_resolve("[email protected]")


with_repo(c(CRAN = "[email protected]"), repo_get())
with_repo(c(CRAN = "[email protected]"), meta_cache_list(package = "dplyr"))

with_repo(c(CRAN = "MRAN@2018-06-30"), summary(repo_status()))

Description

It checks the status of the configured or supplied repositories, for the specified platforms and R versions.

Usage

repo_status(
  platforms = default_platforms(),
  r_version = getRversion(),
  bioc = TRUE,
  cran_mirror = default_cran_mirror()
)

Arguments

Details

The returned data frame has a summary() method, which shows the same information is a concise table. See examples below.

Value

A data frame that has a row for every repository, on every queried platform and R version. It has these columns:

• name: the name of the repository. This comes from the names of the configured repositories in options("repos"), or added by pkgcache. It is typically CRAN for CRAN, and the current Bioconductor repositories are BioCsoft, BioCann, BioCexp, BioCworkflows, BioCbooks.

• url: base URL of the repository.

• bioc_version: Bioconductor version, or NA for non-Bioconductor repositories.

• platform: platform, see default_platforms() for possible values.

• path: the path to the packages within the base URL, for a given platform and R version.

• r_version: R version, one of the specified R versions.

• ok: Logical flag, whether the repository contains a metadata file for the given platform and R version.

• ping: HTTP response time of the repository in seconds. If the ok column is FALSE, then this columns in NA.

• error: the error object if the HTTP query failed for this repository, platform and R version.

See Also

Other repository functions: repo_get()

Examples

repo_status()
rst <- repo_status(
  platforms = c("windows", "macos"),
  r_version = c("4.0", "4.1")
)
summary(rst)