| Title: | Another Approach to Package Installation |
| Version: | 0.9.0 |
| Description: | The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well. |
| License: | GPL-3 |
| URL: | https://pak.r-lib.org/, https://github.com/r-lib/pak |
| BugReports: | https://github.com/r-lib/pak/issues |
| Depends: | R (≥ 3.5) |
| Imports: | tools, utils |
| Suggests: | callr (≥ 3.7.0), cli (≥ 3.2.0), covr, curl (≥ 4.3.2), desc (≥ 1.4.1), filelock (≥ 1.0.2), gitcreds, glue (≥ 1.6.2), jsonlite (≥ 1.8.0), keyring (≥ 1.4.0), pingr, pkgbuild (≥ 1.4.2), pkgcache (≥ 2.2.4), pkgdepends (≥ 0.9.0), pkgload, pkgsearch (≥ 3.1.0), processx (≥ 3.8.1), ps (≥ 1.6.0), rstudioapi, testthat (≥ 3.2.0), webfakes, withr, yaml |
| Biarch: | true |
| ByteCompile: | true |
| Config/build/extra-sources: | configure* |
| Config/needs/dependencies: | callr, cli, curl, desc, filelock, jsonlite, keyring, lpSolve, pkgbuild, pkgcache, pkgdepends, pkgsearch, processx, ps, yaml |
| Config/Needs/website: | r-lib/asciicast, rmarkdown, roxygen2, tidyverse/tidytemplate |
| Config/Needs/deploy: | cli@3.6.2, curl, desc, gitcreds, glue@1.6.2, gaborcsardi/jsonlite, processx, R6@2.5.1 |
| Config/testthat/edition: | 3 |
| Config/usethis/last-upkeep: | 2025-05-13 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2.9000 |
| NeedsCompilation: | yes |
| Packaged: | 2025-05-27 11:31:57 UTC; gaborcsardi |
| Author: | Gábor Csárdi [aut, cre],
Jim Hester [aut],
Posit Software, PBC  [cph,
fnd],
Winston Chang [ctb] (R6, callr, processx),
Ascent Digital Services [cph, fnd] (callr, processx),
Hadley Wickham [ctb, cph] (cli, curl, pkgbuild, yaml),
Jeroen Ooms [ctb] (curl, jsonlite),
Maëlle Salmon [ctb] (desc, pkgsearch),
Duncan Temple Lang [ctb] (jsonlite),
Lloyd Hilaiel [cph] (jsonlite),
Alec Wong [ctb] (keyring),
Michel Berkelaar and lpSolve authors [ctb] (lpSolve),
R Consortium [fnd] (pkgsearch),
Jay Loden [ctb] (ps),
Dave Daeschler [ctb] (ps),
Giampaolo Rodola [ctb] (ps),
Shawn Garbett [ctb] (yaml),
Jeremy Stephens [ctb] (yaml),
Kirill Simonov [ctb] (yaml),
Yihui Xie [ctb] (yaml),
Zhuoer Dong [ctb] (yaml),
Jeffrey Horner [ctb] (yaml),
Will Beasley [ctb] (yaml),
Brendan O'Connor [ctb] (yaml),
Gregory Warnes [ctb] (yaml),
Michael Quinn [ctb] (yaml),
Zhian Kamvar [ctb] (yaml),
Charlie Gao [ctb] (yaml),
Kuba Podgórski [ctb] (zip),
Rich Geldreich [ctb] (zip) |
| Maintainer: | Gábor Csárdi <csardi.gabor@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-05-27 12:10:02 UTC |
pak: Another Approach to Package Installation
Description
The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
Author(s)
Maintainer: Gábor Csárdi csardi.gabor@gmail.com
Authors:
Jim Hester
Other contributors:
Posit Software, PBC (ROR) [copyright holder, funder]
Winston Chang (R6, callr, processx) [contributor]
Ascent Digital Services (callr, processx) [copyright holder, funder]
Hadley Wickham (cli, curl, pkgbuild, yaml) [contributor, copyright holder]
Jeroen Ooms (curl, jsonlite) [contributor]
Maëlle Salmon (desc, pkgsearch) [contributor]
Duncan Temple Lang (jsonlite) [contributor]
Lloyd Hilaiel (jsonlite) [copyright holder]
Alec Wong (keyring) [contributor]
Michel Berkelaar and lpSolve authors (lpSolve) [contributor]
R Consortium (pkgsearch) [funder]
Jay Loden (ps) [contributor]
Dave Daeschler (ps) [contributor]
Giampaolo Rodola (ps) [contributor]
Shawn Garbett (yaml) [contributor]
Jeremy Stephens (yaml) [contributor]
Kirill Simonov (yaml) [contributor]
Yihui Xie (yaml) [contributor]
Zhuoer Dong (yaml) [contributor]
Jeffrey Horner (yaml) [contributor]
Will Beasley (yaml) [contributor]
Brendan O'Connor (yaml) [contributor]
Gregory Warnes (yaml) [contributor]
Michael Quinn (yaml) [contributor]
Zhian Kamvar (yaml) [contributor]
Charlie Gao (yaml) [contributor]
Kuba Podgórski (zip) [contributor]
Rich Geldreich (zip) [contributor]
See Also
Useful links:
Report bugs at https://github.com/r-lib/pak/issues
Authenticated repositories
Description
pak supports HTTP basic authentication when interacting with CRAN-like repositories.
Configuring authenticated repositories
To use authentication you need to include a user name in the repository
URL. You can set the repository URL in the repos option with
base::options() as usual, or you can use repo_add().
For testing purposes pak includes a web app that creates an authenticated proxy to CRAN. This is how to run the proxy in a subprocess:
repo <- webfakes::new_app_process(pak:::auth_proxy_app()) repo$url() #> [1] "http://127.0.0.1:59571/"
(This needs the webfakes and callr packages.)
Next, we configure the proxy as the main CRAN repository. The default username
of the proxy is "username" and the default password is "token". We want to
replace the default CRAN repository with the proxy, so we name it CRAN:
repo_add(CRAN = repo$url(), username = "username") repo_get() #> x Did not find credentials for repo <http://username@127.0.0.1:59571/>, keyring #> lookup failed (macos backend). #> # A data frame: 6 x 7 #> name url type r_version bioc_version username has_password #> * <chr> <chr> <chr> <chr> <chr> <chr> <lgl> #> 1 CRAN http://usern~ cran * <NA> username FALSE #> 2 BioCsoft https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 3 BioCann https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 4 BioCexp https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 5 BioCworkflows https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 6 BioCbooks https://bioc~ bioc 4.4.2 3.20 <NA> NA
Note that the output includes a username and a has_password column.
These are only present if at least one configured repository needs
authentication. has_password is FALSE here, because pak did not find
the credentials for this repository.
repo_get() also displays a message if it cannot find the credentials
for an authenticated repository.
Next we are going to store the credentials in a place where pak can find them.
Credential lookup
pak can look up credentials from two sources:
The current user's
netrcfile.The system credential store via the keyring package. pak comes with its own copy of the keyring package, you don't need to install it separately.
netrc files
If the NETRC environment variable is set, pak uses its value to
determine the location of the netrc file.
Otherwise pak looks for the netrc file in current user's home
directory, at ~/.netrc. On Windows it also looks for ~/_netrc if the
file starting with a dot does not exist.
If you create a netrc file, make sure that is only readable by you.
E.g. on Unix run
chmod 600 ~/.netrc
netrc files are simple text files that can store passwords for multiple
hosts. They may contain three types of tokens:
machine <hostname>
A host name, without the protocol. Subsequent login and password
tokens belong to this host, until another machine token is found, or
the end of file.
login <username>
User name. It must be preceded by a machine token.
password <password>
Password. It must be preceded by a machine and a login token.
Whitespace is ignored in netrc files. You may include multiple tokens
on the same line, or have one token per line. Here is an example:
machine myhost.mydomain.com login myuser password secret machine myhost2.mydomain.com login myuser password secret login anotheruser password stillsecret
If you need to include whitespace in a password, put the password in double quotes.
The credential store
pak uses the keyring package to query the system credential store (or an alternative keyring credential store) to find credentials for authenticated repositories. pak comes with a copy of the keyring package, so you don't need to install it separately.
To store a repository password in the system credential store use the
repo_auth_key_set() function. If you want to use a non-default keyring
backend, set the keyring_backend option. In this manual we will use
the backend that stores secrets in environment variables. This is an
ephemeral store that is destroyed when the R process terminates.
To continue our example from above:
options(keyring_backend = "env") repo_auth_key_set(repo$url(), username = "username", password = "token")
Use repo_auth_key_get() to check that the key is properly set:
repo_auth_key_get(repo$url(), username = "username") #> [1] "token"
repo_get() now does not show a warning message, and also sets the
has_password column to TRUE, because pak could find the credentials
for our CRAN proxy:
repo_get() #> x Did not find credentials for repo <http://username@127.0.0.1:59571/>, keyring #> lookup failed (macos backend). #> # A data frame: 6 x 7 #> name url type r_version bioc_version username has_password #> * <chr> <chr> <chr> <chr> <chr> <chr> <lgl> #> 1 CRAN http://usern~ cran * <NA> username FALSE #> 2 BioCsoft https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 3 BioCann https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 4 BioCexp https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 5 BioCworkflows https://bioc~ bioc 4.4.2 3.20 <NA> NA #> 6 BioCbooks https://bioc~ bioc 4.4.2 3.20 <NA> NA
Repo vs. host credentials
pak handles credentials for repositories and hosts. A repository credential's key is a URL with a non-empty path:
https://repo.host.com/repos/repo1
A host credential's is an URL with an empty path:
https://repo.host.com
pak always looks for repository credentials first. If it does not find any credentials for a repository then it drops the path and looks for host credentials.
Because netrc files only store domain names and not URLs, they can only
contain host credentials.
Testing
To test that authentication works, use the repo_status() function:
repo_status() #> x Did not find credentials for repo <http://username@127.0.0.1:59571/>, keyring #> lookup failed (macos backend). #> # A data frame: 12 x 12 #> name url type bioc_version username has_password platform path r_version #> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> <chr> <chr> #> 1 CRAN http~ cran <NA> username FALSE source src/~ 4.4 #> 2 CRAN http~ cran <NA> username FALSE aarch64~ bin/~ 4.4 #> 3 BioC~ http~ bioc 3.20 <NA> NA source src/~ 4.4 #> 4 BioC~ http~ bioc 3.20 <NA> NA aarch64~ bin/~ 4.4 #> 5 BioC~ http~ bioc 3.20 <NA> NA source src/~ 4.4 #> 6 BioC~ http~ bioc 3.20 <NA> NA aarch64~ bin/~ 4.4 #> 7 BioC~ http~ bioc 3.20 <NA> NA source src/~ 4.4 #> 8 BioC~ http~ bioc 3.20 <NA> NA aarch64~ bin/~ 4.4 #> 9 BioC~ http~ bioc 3.20 <NA> NA source src/~ 4.4 #> 10 BioC~ http~ bioc 3.20 <NA> NA aarch64~ bin/~ 4.4 #> 11 BioC~ http~ bioc 3.20 <NA> NA source src/~ 4.4 #> 12 BioC~ http~ bioc 3.20 <NA> NA aarch64~ bin/~ 4.4 #> # i 3 more variables: ok <lgl>, ping <dbl>, error <list>
The output of repo_status() has extra columns, compared to repo_get(),
and it also has a separate row for each platform. If everything works,
then the has_password column is TRUE for authenticated repositories,
and the ok column is TRUE if repo_status() was able to perform
an (authenticated) HTTP HEAD request to the metadata file of a platform in
a repository.
If you need even more information about repo authentication, e.g. because
repo_status() shows some failures, then use the repo_auth() function:
repo_auth() #> v Found credentials for repo <http://username@127.0.0.1:59571/> (keyring:env). #> # A data frame: 1 x 11 #> name url type r_version bioc_version username has_password auth_domains auth_domain #> * <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <I<list>> <chr> #> 1 CRAN http://username~ cran * <NA> username TRUE <chr [4]> http://127~ #> # i 2 more variables: auth_source <chr>, auth_error <chr>
The output of repo_auth() has the following extra columns:
-
auth_domains: these are the URLs that pak tries to use as theservicewhen looking for credentials in the keyring. For our proxy, it tries these URLs:repo_auth()$auth_domains #> v Found credentials for repo <http://username@127.0.0.1:59571/> (keyring:env). #> [[1]] #> [1] "http://username@127.0.0.1:59571/" "http://127.0.0.1:59571/" #> [3] "http://username@127.0.0.1:59571" "http://127.0.0.1:59571"
-
auth_domain: one ofauth_domains, the URL for which pak found credentials in the keyring. If no credentials were found, then this isNA. -
auth_source: a short string that explains where pak found the credentials (orNAif not credentials were found). For examplesnetrcmeans the user'snetrcfile, andkeyring:macosmeans the macOS system credential store. -
auth_error:NAfor successful credential search, otherwise a short error message on why the search failed. Typically it would fail is the credentials are not in the credential store.
Usage
Once you set up your authenticated repositories, and stored the required passwords in the system credential store, you can use them like any other repository. Operations that need authentication will always include reassuring messages for successful authentications, and warning messages for failed ones. Function calls that do not perform any HTTP requests, e.g. because they list cached data, do not display such messages.
meta_update() #> Checking for 15 new metadata files #> ! Cannot find credentials for URL <http://username@127.0.0.1:59571//bin/macosx/big-sur-arm64/contrib/4.4/PACKAGES.gz>, credential lookup #> failed. Keyring backend: "macos". #> Checking for 15 new metadata files x Did not find credentials for repo <http://username@127.0.0.1:59571/>, keyring #> lookup failed (macos backend). #> #> i R 4.4 aarch64-apple-darwin20 packages are missing from CRAN: Failed to connect to 127.0.0.1 port 59571 after 0 ms: Couldn't connect to server and Failed to connect to 127.0.0.1 port 59571 after 0 ms: Couldn't connect to server #> i source packages are missing from CRAN: Failed to connect to 127.0.0.1 port 59571 after 0 ms: Couldn't connect to server and Failed to connect to 127.0.0.1 port 59571 after 0 ms: Couldn't connect to server #> i Updating metadata database #> v Updating metadata database ... done
meta_list() #> # A data frame: 50,701 x 33 #> package version depends suggests license md5sum sha256sum needscompilation #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 A3 1.0.0 R (>= ~ randomF~ GPL (>~ 929a4~ "\n ~ no #> 2 AATtools 0.0.3 R (>= ~ <NA> GPL-3 de2ec~ "\n ~ no #> 3 ABACUS 1.0.0 R (>= ~ rmarkdo~ GPL-3 28795~ "\n ~ no #> 4 ABC.RAP 0.9.0 R (>= ~ knitr, ~ GPL-3 0158e~ "\n ~ no #> 5 ABCanalys~ 1.2.1 R (>= ~ <NA> GPL-3 4cbe1~ "\n ~ no #> 6 ABCoptim 0.15.0 <NA> testtha~ MIT + ~ a294d~ "\n ~ yes #> 7 ABCp2 1.2 MASS <NA> GPL-2 d049b~ <NA> no #> 8 ABHgenoty~ 1.0.1 <NA> knitr, ~ GPL-3 fce25~ "\n ~ no #> 9 ABM 0.4.3 <NA> <NA> GPL (>~ 7aaae~ "\n ~ yes #> 10 ABPS 0.3 <NA> testthat GPL (>~ d3f00~ "\n ~ no #> # i 50,691 more rows #> # i 25 more variables: imports <chr>, linkingto <chr>, archs <chr>, #> # enhances <chr>, license_restricts_use <chr>, priority <chr>, os_type <chr>, #> # license_is_foss <chr>, repodir <chr>, rversion <chr>, platform <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>, path <chr>
E.g. here meta_update() outputs an authentication message, but
meta_list() does not.
See Also
Other authenticated repositories:
repo_auth(),
repo_auth_key_get()
Frequently Asked Questions
Description
Please take a look at this list before asking questions.
Package installation
How do I reinstall a package?
pak does not reinstall a package, if the same version is already installed.
Sometimes you still want a reinstall, e.g. to fix a broken installation.
In this case you can delete the package and then install it, or use the
?reinstall parameter:
pak::pkg_install("tibble")
#> #> → Will install 13 packages. #> → All 13 packages (7.68 MB) are cached. #> + cli 3.3.0 #> + crayon 1.5.1 #> + ellipsis 0.3.2 #> + fansi 1.0.3 #> + glue 1.6.2 #> + lifecycle 1.0.1 #> + magrittr 2.0.3 #> + pillar 1.7.0 #> + pkgconfig 2.0.3 #> + rlang 1.0.2 #> + tibble 3.1.7 #> + utf8 1.2.2 #> + vctrs 0.4.1 #> i No downloads are needed, 13 pkgs (7.68 MB) are cached #> v Got utf8 1.2.2 (aarch64-apple-darwin20) (209.24 kB) #> v Installed cli 3.3.0 (76ms) #> v Installed crayon 1.5.1 (87ms) #> v Installed ellipsis 0.3.2 (97ms) #> v Installed fansi 1.0.3 (103ms) #> v Installed glue 1.6.2 (111ms) #> v Installed lifecycle 1.0.1 (153ms) #> v Installed magrittr 2.0.3 (158ms) #> v Installed pillar 1.7.0 (162ms) #> v Installed pkgconfig 2.0.3 (87ms) #> v Installed rlang 1.0.2 (39ms) #> v Installed tibble 3.1.7 (41ms) #> v Installed utf8 1.2.2 (39ms) #> v Installed vctrs 0.4.1 (32ms) #> v 1 pkg + 12 deps: added 13, dld 1 (209.24 kB) [1.8s]
pak::pkg_install("tibble?reinstall")
#> #> → Will install 1 package. #> → The package (724.32 kB) is cached. #> + tibble 3.1.7 #> i No downloads are needed, 1 pkg (724.32 kB) is cached #> v Installed tibble 3.1.7 (42ms) #> v 1 pkg + 12 deps: kept 11, added 1 [343ms]
How do I install a dependency from a binary package
Sometimes it is sufficient to install the binary package of an older version of a dependency, instead of the newer source package that potentially needs compilers, system tools or libraries.
pkg_install() and lockfile_create() default to upgrade = FALSE, which
always chooses binaries over source packages, so if you use pkg_install()
you don't need to do anything extra.
The local_install_* functions default to upgrade = TRUE, as does pak()
with pkg = NULL, so for these you need to explicitly use upgrade = FALSE.
How do I install a package from source?
To force the installation of a source package (instead of a binary
package), use the ?source parameter:
pak::pkg_install("tibble?source")
#> #> → Will install 1 package. #> → The package (672.34 kB) is cached. #> + tibble 3.1.7 👷🏼♀️🔧 #> i No downloads are needed, 1 pkg (672.34 kB) is cached #> i Building tibble 3.1.7 #> v Built tibble 3.1.7 (3.1s) #> v Installed tibble 3.1.7 (35ms) #> v 1 pkg + 12 deps: kept 11, added 1 [4.1s]
How do I install the latest version of a dependency?
If you want to always install a dependency from source, because you want
the latest version or some other reason, you can use the source
parameter with the <package>= form: <package>=?source.
For example to install tibble, with its cli dependency installed from
source you could write:
pak::pkg_install(c("tibble", "cli=?source"))
#> #> → Will install 1 package. #> → The package (540.04 kB) is cached. #> + cli 3.3.0 👷🏽🔧 #> i No downloads are needed, 1 pkg (540.04 kB) is cached #> i Building cli 3.3.0 #> v Built cli 3.3.0 (4.5s) #> v Installed cli 3.3.0 (68ms) #> v 1 pkg + 12 deps: kept 11, added 1 [4.9s]
How do I ignore an optional dependency?
pak::pkg_install(
c("tibble", "DiagrammeR=?ignore", "formattable=?ignore"),
dependencies = TRUE
)
#> #> i No downloads are needed #> v 1 pkg + 12 deps: kept 12 [583ms]
The syntax is
<packagename>=?ignore
Note that you can only ignore optional dependencies, i.e. packages in
Suggests and Enhances.
Others
How can I use pak with renv?
Since version 1.0.0 renv has official support for using pak. This needs to be
enabled with the renv.config.pak.enabled option or the RENV_CONFIG_PAK_ENABLED environment variable set to TRUE. For more information see the renv
documentation.
Simplified manual. Start here!
Description
You don't need to read long manual pages for a simple task. This manual page collects the most common pak use cases.
Package installation
Install a package from CRAN or Bioconductor
pak::pkg_install("tibble")
pak automatically sets a CRAN repository and the Bioconductor repositories that corresponds to the current R version.
Install a package from GitHub
pak::pkg_install("tidyverse/tibble")
#> #> → Will update 2 packages. #> → All 2 packages (0 B) are cached. #> + tibble 3.1.8 → 3.1.8.9002 👷🏻🔧 (GitHub: 37ec86a) #> + vctrs 0.5.1 → 0.5.1.9000 👷🏾♀️🔧 (GitHub: 2d7de76) #> i No downloads are needed, 2 pkgs are cached #> i Packaging vctrs 0.5.1.9000 #> v Packaged vctrs 0.5.1.9000 (1.4s) #> i Building vctrs 0.5.1.9000 #> v Built vctrs 0.5.1.9000 (11.2s) #> v Installed vctrs 0.5.1.9000 (github::r-lib/vctrs@2d7de76) (34ms) #> i Packaging tibble 3.1.8.9002 #> v Packaged tibble 3.1.8.9002 (502ms) #> i Building tibble 3.1.8.9002 #> v Built tibble 3.1.8.9002 (2.7s) #> v Installed tibble 3.1.8.9002 (github::tidyverse/tibble@37ec86a) (28ms) #> v 1 pkg + 10 deps: kept 9, upd 2 [17.5s]
Use the user/repo form.
You can specify a branch or tag: user/repo@branch or user/repo@tag.
Install a package from a URL
pak::pkg_install( "url::https://cran.r-project.org/src/contrib/Archive/tibble/tibble_3.1.7.tar.gz" )
#> #> → Will install 1 package. #> → Will update 1 package. #> → All 2 packages (38.65 kB) are cached. #> + ellipsis 0.3.2 #> + tibble 3.1.8.9002 → 3.1.7 👷🏻♀️🔧 #> i No downloads are needed, 2 pkgs (38.65 kB) are cached #> v Installed ellipsis 0.3.2 (18ms) #> i Building tibble 3.1.7 #> v Built tibble 3.1.7 (2.5s) #> v Installed tibble 3.1.7 (31ms) #> v 1 pkg + 11 deps: kept 10, upd 1, added 1 [3.3s]
The URL may point to an R package file, made with R CMD build, or a
.tar.gz or .zip archive of a package tree.
Package updates
Update a package
pak::pkg_install("tibble")
#> #> → Will update 1 package. #> → The package (724.32 kB) is cached. #> + tibble 3.1.7 → 3.1.8 #> i No downloads are needed, 1 pkg (724.32 kB) is cached #> v Installed tibble 3.1.8 (36ms) #> v 1 pkg + 10 deps: kept 10, upd 1 [368ms]
pak::pkg_install() automatically updates the package.
Update all dependencies of a package
pak::pkg_install("tibble", upgrade = TRUE)
#> #> i No downloads are needed #> v 1 pkg + 10 deps: kept 11 [278ms]
upgrade = TRUE updates the package itself and all of its dependencies, if
necessary.
Reinstall a package
Add ?reinstall to the package name or package reference in general:
pak::pkg_install("tibble?reinstall")
#> #> → Will install 1 package. #> → The package (724.32 kB) is cached. #> + tibble 3.1.8 #> i No downloads are needed, 1 pkg (724.32 kB) is cached #> v Installed tibble 3.1.8 (60ms) #> v 1 pkg + 10 deps: kept 10, added 1 [340ms]
Dependency lookup
Dependencies of a CRAN or Bioconductor package
pak::pkg_deps("tibble")
#> # A data frame: 11 × 32 #> ref type direct direc…¹ status package version license needs…² #> <chr> <chr> <lgl> <lgl> <chr> <chr> <chr> <chr> <lgl> #> 1 cli stan… FALSE FALSE OK cli 3.4.1 MIT + … FALSE #> 2 fansi stan… FALSE FALSE OK fansi 1.0.3 GPL-2 … FALSE #> 3 glue stan… FALSE FALSE OK glue 1.6.2 MIT + … FALSE #> 4 lifecycle stan… FALSE FALSE OK lifecy… 1.0.3 MIT + … FALSE #> 5 magrittr stan… FALSE FALSE OK magrit… 2.0.3 MIT + … FALSE #> 6 pillar stan… FALSE FALSE OK pillar 1.8.1 MIT + … FALSE #> 7 pkgconfig stan… FALSE FALSE OK pkgcon… 2.0.3 MIT + … FALSE #> 8 rlang stan… FALSE FALSE OK rlang 1.0.6 MIT + … FALSE #> 9 tibble stan… TRUE TRUE OK tibble 3.1.8 MIT + … FALSE #> 10 utf8 stan… FALSE FALSE OK utf8 1.2.2 Apache… FALSE #> 11 vctrs stan… FALSE FALSE OK vctrs 0.5.1 MIT + … FALSE #> # … with 23 more variables: priority <chr>, md5sum <chr>, sha256 <chr>, #> # filesize <int>, built <chr>, platform <chr>, rversion <chr>, #> # repotype <chr>, repodir <chr>, target <chr>, deps <list>, #> # mirror <chr>, sources <list>, remote <list>, error <list>, #> # metadata <list>, dep_types <list>, params <list>, sysreqs <chr>, #> # cache_status <chr>, lib_status <chr>, old_version <chr>, #> # new_version <chr>, and abbreviated variable names ¹directpkg, …
The results are returned in a data frame.
Dependency tree of a CRAN / Bioconductor package
pak::pkg_deps_tree("tibble")
#> tibble 3.1.8 ✨ #> ├─fansi 1.0.3 ✨ #> ├─lifecycle 1.0.3 ✨ #> │ ├─cli 3.4.1 ✨ #> │ ├─glue 1.6.2 ✨ #> │ └─rlang 1.0.6 ✨ #> ├─magrittr 2.0.3 ✨ #> ├─pillar 1.8.1 ✨ #> │ ├─cli #> │ ├─fansi #> │ ├─glue #> │ ├─lifecycle #> │ ├─rlang #> │ ├─utf8 1.2.2 ✨ #> │ └─vctrs 0.5.1 ✨ #> │ ├─cli #> │ ├─glue #> │ ├─lifecycle #> │ └─rlang #> ├─pkgconfig 2.0.3 ✨ #> ├─rlang #> └─vctrs #> #> Key: ✨ new
The results are also silently returned in a data frame.
Dependency tree of a package on GitHub
pak::pkg_deps_tree("tidyverse/tibble")
#> tidyverse/tibble 3.1.8.9002 ✨👷🏼🔧 #> ├─fansi 1.0.3 ✨ #> ├─lifecycle 1.0.3 ✨ #> │ ├─cli 3.4.1 ✨ #> │ ├─glue 1.6.2 ✨ #> │ └─rlang 1.0.6 ✨ #> ├─magrittr 2.0.3 ✨ #> ├─pillar 1.8.1 ✨ #> │ ├─cli #> │ ├─fansi #> │ ├─glue #> │ ├─lifecycle #> │ ├─rlang #> │ ├─utf8 1.2.2 ✨ #> │ └─r-lib/vctrs 0.5.1.9000 ✨👷🏼🔧 #> │ ├─cli #> │ ├─glue #> │ ├─lifecycle #> │ └─rlang #> ├─pkgconfig 2.0.3 ✨ #> ├─rlang #> └─r-lib/vctrs #> #> Key: ✨ new | 👷🏼 build | 🔧 compile
Use the user/repo form.
As usual, you can also select a branch, tag, or sha, with the
user/repo@branch, user/repo@tag or user/repo@sha forms.
Dependency tree of the package in the current directory
pak::local_deps_tree("tibble")
#> local::tibble 3.1.8 ✨👷🏻♀️🔧 #> ├─fansi 1.0.3 ✨ #> ├─lifecycle 1.0.3 ✨ #> │ ├─cli 3.4.1 ✨ #> │ ├─glue 1.6.2 ✨ #> │ └─rlang 1.0.6 ✨ #> ├─magrittr 2.0.3 ✨ #> ├─pillar 1.8.1 ✨ #> │ ├─cli #> │ ├─fansi #> │ ├─glue #> │ ├─lifecycle #> │ ├─rlang #> │ ├─utf8 1.2.2 ✨ #> │ └─vctrs 0.5.1 ✨ #> │ ├─cli #> │ ├─glue #> │ ├─lifecycle #> │ └─rlang #> ├─pkgconfig 2.0.3 ✨ #> ├─rlang #> └─vctrs #> #> Key: ✨ new | 👷🏻♀️ build | 🔧 compile
Assuming package is in directory tibble.
Explain a recursive dependency
How does tibble depend on rlang?
pak::pkg_deps_explain("tibble", "rlang")
#> tibble -> lifecycle -> rlang #> tibble -> pillar -> lifecycle -> rlang #> tibble -> pillar -> rlang #> tibble -> pillar -> vctrs -> lifecycle -> rlang #> tibble -> pillar -> vctrs -> rlang #> tibble -> rlang #> tibble -> vctrs -> lifecycle -> rlang #> tibble -> vctrs -> rlang
Use can also use the user/repo form for packages from GitHub,
url::... for packages at URLs, etc.
Package development
Install dependencies of local package
pak::local_install_deps()
#> v Loading metadata database ... done #> #> → The package (0 B) is cached. #> i No downloads are needed #> v 10 deps: kept 10 [3.2s]
Install local package
pak::local_install()
#> #> → Will update 1 package. #> → The package (0 B) is cached. #> + tibble 3.1.8 → 3.1.8 👷🏻♂️🔧 #> i No downloads are needed, 1 pkg is cached #> v Got tibble 3.1.8 (source) (96 B) #> i Packaging tibble 3.1.8 #> v Packaged tibble 3.1.8 (864ms) #> i Building tibble 3.1.8 #> v Built tibble 3.1.8 (2.4s) #> v Installed tibble 3.1.8 (local) (38ms) #> v 1 pkg + 10 deps: kept 10, upd 1, dld 1 (NA B) [4.2s]
Install all dependencies of local package
pak::local_install_dev_deps()
#> #> → Will install 86 packages. #> → Will update 2 packages. #> → All 89 packages (100.53 MB) are cached. #> + askpass 1.1 #> + base64enc 0.1-3 #> + bench 1.1.2 #> + bit 4.0.5 #> + bit64 4.0.5 #> + blob 1.2.3 #> + brio 1.1.3 #> + bslib 0.4.1 #> + cachem 1.0.6 #> + callr 3.7.3 #> + clipr 0.8.0 #> + colorspace 2.0-3 #> + covr 3.6.1 #> + crayon 1.5.2 #> + curl 4.3.3 #> + desc 1.4.2 #> + DiagrammeR 1.0.9 #> + diffobj 0.3.5 #> + digest 0.6.31 #> + downloader 0.4 #> + dplyr 1.0.10 #> + evaluate 0.19 👷🏿♂️ #> + farver 2.1.1 #> + fastmap 1.1.0 #> + formattable 0.2.1 #> + fs 1.5.2 #> + generics 0.1.3 #> + ggplot2 3.4.0 #> + gridExtra 2.3 #> + gtable 0.3.1 #> + highr 0.9 #> + hms 1.1.2 #> + htmltools 0.5.4 #> + htmlwidgets 1.6.0 👷🏾♂️ #> + httr 1.4.4 #> + igraph 1.3.5 #> + influenceR 0.1.0.1 #> + isoband 0.2.6 #> + jquerylib 0.1.4 #> + jsonlite 1.8.4 #> + knitr 1.41 #> + labeling 0.4.2 #> + lazyeval 0.2.2 #> + lubridate 1.9.0 #> + Matrix 1.5-1 → 1.5-3 #> + memoise 2.0.1 #> + mime 0.12 #> + mockr 0.2.0 #> + munsell 0.5.0 #> + nlme 3.1-160 → 3.1-161 👷♂️🔧 #> + nycflights13 1.0.2 #> + openssl 2.0.5 #> + pkgbuild 1.4.0 #> + pkgload 1.3.2 #> + praise 1.0.0 #> + prettyunits 1.1.1 #> + processx 3.8.0 #> + profmem 0.6.0 #> + ps 1.7.2 #> + purrr 0.3.5 #> + R6 2.5.1 #> + rappdirs 0.3.3 #> + RColorBrewer 1.1-3 #> + readr 2.1.3 #> + rematch2 2.1.2 #> + rex 1.2.1 #> + rmarkdown 2.19 👷♂️ #> + rprojroot 2.0.3 #> + rstudioapi 0.14 #> + sass 0.4.4 #> + scales 1.2.1 #> + stringi 1.7.8 #> + stringr 1.5.0 #> + sys 3.4.1 #> + testthat 3.1.6 #> + tidyr 1.2.1 #> + tidyselect 1.2.0 #> + timechange 0.1.1 #> + tinytex 0.43 👷🏻♂️ #> + tzdb 0.3.0 #> + viridis 0.6.2 #> + viridisLite 0.4.1 #> + visNetwork 2.1.2 #> + vroom 1.6.0 #> + waldo 0.4.0 #> + withr 2.5.0 #> + xfun 0.35 #> + yaml 2.3.6 #> i No downloads are needed, 88 pkgs (100.53 MB) are cached #> i Packaging tibble 3.1.8 #> i Building evaluate 0.19 #> i Building nlme 3.1-161 #> v Installed R6 2.5.1 (31ms) #> v Installed DiagrammeR 1.0.9 (76ms) #> v Installed RColorBrewer 1.1-3 (72ms) #> v Installed askpass 1.1 (79ms) #> v Installed Matrix 1.5-3 (137ms) #> v Installed base64enc 0.1-3 (125ms) #> v Installed bench 1.1.2 (90ms) #> v Installed bit64 4.0.5 (44ms) #> v Installed bit 4.0.5 (43ms) #> v Installed blob 1.2.3 (41ms) #> v Installed brio 1.1.3 (40ms) #> v Installed cachem 1.0.6 (31ms) #> v Installed callr 3.7.3 (53ms) #> v Installed clipr 0.8.0 (89ms) #> v Installed colorspace 2.0-3 (99ms) #> v Installed covr 3.6.1 (58ms) #> v Installed crayon 1.5.2 (75ms) #> v Installed curl 4.3.3 (83ms) #> v Packaged tibble 3.1.8 (684ms) #> v Installed bslib 0.4.1 (315ms) #> v Installed desc 1.4.2 (77ms) #> v Installed diffobj 0.3.5 (68ms) #> v Installed digest 0.6.31 (60ms) #> v Installed downloader 0.4 (39ms) #> v Installed dplyr 1.0.10 (39ms) #> v Installed farver 2.1.1 (41ms) #> v Installed fastmap 1.1.0 (38ms) #> v Installed formattable 0.2.1 (43ms) #> v Built evaluate 0.19 (903ms) #> v Installed fs 1.5.2 (49ms) #> v Installed generics 0.1.3 (46ms) #> v Installed ggplot2 3.4.0 (65ms) #> v Installed gridExtra 2.3 (43ms) #> v Installed gtable 0.3.1 (38ms) #> v Installed highr 0.9 (37ms) #> v Installed hms 1.1.2 (39ms) #> v Installed htmltools 0.5.4 (40ms) #> v Installed httr 1.4.4 (40ms) #> v Installed influenceR 0.1.0.1 (17ms) #> v Installed igraph 1.3.5 (96ms) #> v Installed isoband 0.2.6 (68ms) #> v Installed jquerylib 0.1.4 (38ms) #> v Installed jsonlite 1.8.4 (37ms) #> v Installed labeling 0.4.2 (14ms) #> v Installed knitr 1.41 (73ms) #> v Installed lazyeval 0.2.2 (43ms) #> v Installed lubridate 1.9.0 (38ms) #> v Installed memoise 2.0.1 (39ms) #> v Installed mime 0.12 (58ms) #> v Installed mockr 0.2.0 (38ms) #> v Installed munsell 0.5.0 (36ms) #> v Installed nycflights13 1.0.2 (37ms) #> v Installed openssl 2.0.5 (41ms) #> v Installed pkgbuild 1.4.0 (39ms) #> v Installed pkgload 1.3.2 (37ms) #> v Installed praise 1.0.0 (35ms) #> v Installed prettyunits 1.1.1 (56ms) #> v Installed processx 3.8.0 (37ms) #> v Installed profmem 0.6.0 (37ms) #> v Installed ps 1.7.2 (37ms) #> v Installed purrr 0.3.5 (38ms) #> v Installed rappdirs 0.3.3 (37ms) #> v Installed readr 2.1.3 (42ms) #> v Installed rematch2 2.1.2 (41ms) #> v Installed rex 1.2.1 (58ms) #> v Installed rprojroot 2.0.3 (58ms) #> v Installed rstudioapi 0.14 (40ms) #> v Installed sass 0.4.4 (42ms) #> v Installed scales 1.2.1 (39ms) #> v Installed stringr 1.5.0 (33ms) #> v Installed sys 3.4.1 (49ms) #> v Installed testthat 3.1.6 (88ms) #> v Installed tidyr 1.2.1 (77ms) #> v Installed stringi 1.7.8 (195ms) #> v Installed tidyselect 1.2.0 (113ms) #> v Installed timechange 0.1.1 (55ms) #> v Installed tzdb 0.3.0 (40ms) #> v Installed viridisLite 0.4.1 (39ms) #> v Installed viridis 0.6.2 (39ms) #> v Installed visNetwork 2.1.2 (77ms) #> v Installed vroom 1.6.0 (77ms) #> v Installed waldo 0.4.0 (62ms) #> v Installed withr 2.5.0 (40ms) #> v Installed xfun 0.35 (39ms) #> i Building tinytex 0.43 #> v Installed yaml 2.3.6 (43ms) #> v Installed evaluate 0.19 (15ms) #> v Built tinytex 0.43 (1.1s) #> v Installed tinytex 0.43 (15ms) #> i Building rmarkdown 2.19 #> v Built rmarkdown 2.19 (3.9s) #> v Installed rmarkdown 2.19 (85ms) #> i Building htmlwidgets 1.6.0 #> v Built nlme 3.1-161 (8s) #> v Installed nlme 3.1-161 (33ms) #> v Built htmlwidgets 1.6.0 (1.1s) #> v Installed htmlwidgets 1.6.0 (22ms) #> v 103 deps: kept 15, upd 2, added 86 [10.2s]
Installs development and optional dependencies as well.
Repositories
List current repositories
pak::repo_get()
#> # A data frame: 5 × 5 #> name url type r_ver…¹ bioc_…² #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cloud.r-project.org cran * NA #> 2 BioCsoft https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 3 BioCann https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 4 BioCexp https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 5 BioCworkflows https://bioconductor.org/packages… bioc 4.2.2 3.16 #> # … with abbreviated variable names ¹r_version, ²bioc_version
If you haven't set a CRAN or Bioconductor repository, pak does that automatically.
Add custom repository
pak::repo_add(rhub = 'https://r-hub.r-universe.dev') pak::repo_get()
#> # A data frame: 6 × 5 #> name url type r_ver…¹ bioc_…² #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cloud.r-project.org cran * NA #> 2 rhub https://r-hub.r-universe.dev cran… * NA #> 3 BioCsoft https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 4 BioCann https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 5 BioCexp https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 6 BioCworkflows https://bioconductor.org/packages… bioc 4.2.2 3.16 #> # … with abbreviated variable names ¹r_version, ²bioc_version
Remove custom repositories
options(repos = getOption("repos")["CRAN"])
pak::repo_get()
#> # A data frame: 5 × 5 #> name url type r_ver…¹ bioc_…² #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cloud.r-project.org cran * NA #> 2 BioCsoft https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 3 BioCann https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 4 BioCexp https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 5 BioCworkflows https://bioconductor.org/packages… bioc 4.2.2 3.16 #> # … with abbreviated variable names ¹r_version, ²bioc_version
If you set the repos option to a CRAN repo only, or unset it completely,
then pak keeps only CRAN and (by default) Bioconductor.
Time travel using RSPM
pak::repo_add(CRAN = "RSPM@2022-06-30") pak::repo_get()
#> # A data frame: 5 × 5 #> name url type r_ver…¹ bioc_…² #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://packagemanager.posit.co/c… cran * NA #> 2 BioCsoft https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 3 BioCann https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 4 BioCexp https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 5 BioCworkflows https://bioconductor.org/packages… bioc 4.2.2 3.16 #> # … with abbreviated variable names ¹r_version, ²bioc_version
Sets a repository that is equivalent to CRAN's state closest to the
specified date.
Name this repository CRAN, otherwise pak will also add a default CRAN
repository.
Time travel using MRAN
pak::repo_add(CRAN = "MRAN@2022-06-30") pak::repo_get()
#> # A data frame: 5 × 5 #> name url type r_ver…¹ bioc_…² #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cran.microsoft.com/snapsh… cran * NA #> 2 BioCsoft https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 3 BioCann https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 4 BioCexp https://bioconductor.org/packages… bioc 4.2.2 3.16 #> 5 BioCworkflows https://bioconductor.org/packages… bioc 4.2.2 3.16 #> # … with abbreviated variable names ¹r_version, ²bioc_version
Sets a repository that is equivalent to CRAN's state at the specified date.
Name this repository CRAN, otherwise pak will also add a default CRAN
repository.
Caches
By default pak caches both metadata and downloaded packages.
Inspect metadata cache
pak::meta_list()
#> v Updated metadata database: 4.55 MB in 4 files. #> v Updating metadata database ... done #> # A data frame: 43,718 × 32 #> package version depends sugge…¹ license imports linki…² archs enhan…³ #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 A3 1.0.0 R (>= … random… GPL (>… NA NA NA NA #> 2 AATtoo… 0.0.1 R (>= … NA GPL-3 magrit… NA NA NA #> 3 ABACUS 1.0.0 R (>= … rmarkd… GPL-3 ggplot… NA NA NA #> 4 ABC.RAP 0.9.0 R (>= … knitr,… GPL-3 graphi… NA NA NA #> 5 ABCana… 1.2.1 R (>= … NA GPL-3 plotrix NA NA NA #> 6 ABCopt… 0.15.0 NA testth… MIT + … Rcpp, … Rcpp ABCo… NA #> 7 ABCp2 1.2 MASS NA GPL-2 NA NA NA NA #> 8 ABHgen… 1.0.1 NA knitr,… GPL-3 ggplot… NA NA NA #> 9 ABPS 0.3 NA testth… GPL (>… kernlab NA NA NA #> 10 ACA 1.1 R (>= … NA GPL graphi… NA NA NA #> # … with 43,708 more rows, 23 more variables: os_type <chr>, #> # priority <chr>, license_is_foss <chr>, license_restricts_use <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>, and …
Update metadata cache
By default pkg_install() and similar functions automatically update the
metadata for the currently set repositories if it is older than 24 hours.
You can also force an update manually:
pak::meta_update()
#> v Updating metadata database ... done
Clean metadata cache
pak::meta_clean(force = TRUE) pak::meta_summary()
#> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metad #> ata" #> #> $current_db #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metad #> ata/pkgs-d1c324e625.rds" #> #> $raw_files #> character(0) #> #> $db_files #> character(0) #> #> $size #> [1] 0 #>
Inspect package cache
Downloaded packages are also cached.
pak::cache_list()
#> # A data frame: 480 × 11 #> fullpath path package url etag sha256 version platf…¹ built #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <int> #> 1 /Users/gaborc… arch… NA http… "\"1… 0c8f0… NA NA NA #> 2 /Users/gaborc… bin/… evalua… http… "\"1… 08a39… 0.17 aarch6… NA #> 3 /Users/gaborc… bin/… crayon http… "\"2… 1e6d5… 1.5.2 aarch6… NA #> 4 /Users/gaborc… bin/… common… http… "\"4… 47b4a… 1.8.1 aarch6… NA #> 5 /Users/gaborc… bin/… curl http… "\"b… 7b8ba… 4.3.3 aarch6… NA #> 6 /Users/gaborc… bin/… tinytex http… "\"2… 7e9ba… 0.42 aarch6… NA #> 7 /Users/gaborc… bin/… jsonli… http… "\"1… 68e59… 1.8.2 aarch6… NA #> 8 /Users/gaborc… bin/… lifecy… http… "\"1… 7ce27… 1.0.3 aarch6… NA #> 9 /Users/gaborc… bin/… vctrs http… "\"1… c3a69… 0.4.2 aarch6… NA #> 10 /Users/gaborc… src/… pkgcac… NA NA 9b70a… NA NA 0 #> # … with 470 more rows, 2 more variables: vignettes <int>, #> # rversion <chr>, and abbreviated variable name ¹platform
View a package cache summary
pak::cache_summary()
#> $cachepath #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/pkg" #> #> $files #> [1] 480 #> #> $size #> [1] 653325143 #>
Clean package cache
pak::cache_clean()
Libraries
List packages in a library
pak::lib_status(Sys.getenv("R_LIBS_USER"))
#> # A data frame: 701 × 39 #> library package title version depends repos…¹ license needs…² built #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> #> 1 /Users/g… abc "Too… 2.2.1 R (>= … CRAN GPL (>… FALSE R 4.… #> 2 /Users/g… abc.da… "Dat… 1.0 R (>= … CRAN GPL (>… FALSE R 4.… #> 3 /Users/g… abind "Com… 1.4-5 R (>= … CRAN LGPL (… FALSE R 4.… #> 4 /Users/g… ade4 "Ana… 1.7-19 R (>= … CRAN GPL (>… TRUE R 4.… #> 5 /Users/g… ape "Ana… 5.6-2 R (>= … CRAN GPL-2 … TRUE R 4.… #> 6 /Users/g… aplot "Dec… 0.1.7 NA CRAN Artist… FALSE R 4.… #> 7 /Users/g… archive "Mul… 1.1.5 R (>= … CRAN MIT + … TRUE R 4.… #> 8 /Users/g… arrayh… "Con… 1.1-0 NA CRAN GPL FALSE R 4.… #> 9 /Users/g… arrow "Int… 9.0.0 R (>= … CRAN Apache… TRUE R 4.… #> 10 /Users/g… arules "Min… 1.7-5 R (>= … CRAN GPL-3 TRUE R 4.… #> # … with 691 more rows, 30 more variables: remotetype <chr>, #> # remotepkgref <chr>, remoteref <chr>, remoterepos <chr>, #> # remotepkgplatform <chr>, remotesha <chr>, imports <chr>, #> # suggests <chr>, linkingto <chr>, remotes <chr>, remotehost <chr>, #> # remoterepo <chr>, remoteusername <chr>, enhances <chr>, #> # biocviews <chr>, remoteurl <chr>, remotesubdir <chr>, #> # priority <chr>, remoteetag <chr>, remotepackaged <chr>, …
Pass the directory of the library as the argument.
A list of the most important pak features
Description
A list of the most important pak features.
pak is fast
Parallel HTTP
pak performs HTTP queries concurrently. This is true when
it downloads package metadata from package repositories,
it resolves packages from CRAN, GitHub, URLs, etc,
it downloads the actual package files,
etc.
Parallel installation
pak installs packages concurrently, as much as their dependency graph allows this.
Caching
pak caches metadata and package files, so you don't need to re-download the same files over and over.
pak is safe
Plan installation up front
pak creates an installation plan before downloading any packages. If the plan is unsuccessful, then it fails without downloading any packages.
Auto-install missing dependencies
When requesting the installation of a package, pak makes sure that all of its dependencies are also installed.
Keeping binary packages up-to-date
pak automatically discards binary packages from the cache, if a new build of the same version is available on CRAN.
Correct CRAN metadata errors
pak can correct some of CRAN's metadata issues, e.g.:
New version of the package was released since we obtained the metadata.
macOS binary package is only available at https://mac.r-project.org/ because of a synchronization issue.
Graceful handling of locked package DLLs on Windows
pak handles the situation of locked package DLLs, as well as possible. It detects which process locked them, and offers the choice of terminating these processes. It also unloads packages from the current R session as needed.
pak keeps its own dependencies isolated
pak keeps its own dependencies in a private package library and never loads any packages. (Only in background processes).
pak is convenient
pak comes as a self-contained binary package
On the most common platforms. No dependencies, no system dependencies, no compiler needed. (See also the installation manual.)
Install packages from multiple sources
CRAN, Bioconductor
GitHub
URLs
Local files or directories.
Ignore certain optional dependencies
pak can ignore certain optional dependencies if requested.
CRAN package file sizes
pak knows the sizes of CRAN package files, so it can estimate how much data you need to download, before the installation.
Bioconductor version detection
pak automatically selects the Bioconductor version that is appropriate for your R version. No need to set any repositories.
Time travel with PPM
pak can use PPM (Posit Public Package Manager) to install from snapshots or CRAN.
pak can install dependencies of local packages
Very handy for package development!
All about installing pak.
Description
Read this if the default installation methods do not work for you or if you want the release candidate or development version.
Pre-built binaries
Our pre-built binaries have the advantage that they are completely self-contained and dependency free. No additional R packages, system libraries or tools (e.g. compilers) are needed for them. Install a pre-built binary build of pak from our repository on GitHub:
install.packages("pak", repos = sprintf(
"https://r-lib.github.io/p/pak/stable/%s/%s/%s",
.Platform$pkgType,
R.Version()$os,
R.Version()$arch
))
This is supported for the following systems:
| OS | CPU | R version |
| Linux | x86_64 | R 3.4.0 - R-devel |
| Linux | aarch64 | R 3.4.0 - R-devel |
| macOS High Sierra+ | x86_64 | R 3.4.0 - R-devel |
| macOS Big Sur+ | aarch64 | R 4.1.0 - R-devel |
| Windows | x86_64 | R 3.4.0 - R-devel |
| FreeBSD 13.x or later | x86_64 | R 4.4.x |
| OpenBSD 7.4, 7.5, 7.6 | x86_64 | R 4.2.x (7.4, 7.5), R 4.4.x (7.6) |
| NetBSD 10.0 | x86_64 | R 4.4.x |
| DragonFly BSD 6.4 | x86_64 | R 4.3.x |
Notes
For macOS we only support the official CRAN R build. Other builds, e.g. Homebrew R, are not supported.
We only support R builds that have an R shared library. CRAN's Windows and macOS installers are such, so the the R builds in the common Linux distributions. But this might be an issue if you build R yourself without the
--enable-R-shliboption.
Install from CRAN
Install the released version of the package from CRAN as usual:
install.packages("pak")
This potentially needs a C compiler on platforms CRAN does not have binaries packages for.
Nightly builds
We have nightly binary builds, for the same systems as the table above:
install.packages("pak", repos = sprintf(
"https://r-lib.github.io/p/pak/devel/%s/%s/%s",
.Platform$pkgType,
R.Version()$os,
R.Version()$arch
))
stable, rc and devel streams
We have three types of binaries available:
-
stablecorresponds to the latest CRAN release of pak. -
rcis a release candidate build, and it is available about 1-2 weeks before a release. Otherwise it is the same as thestablebuild. -
develhas builds from the development tree. Before release it might be the same as thercbuild.
The streams are available under different repository URLs:
stream <- "rc"
install.packages("pak", repos = sprintf(
"https://r-lib.github.io/p/pak/%s/%s/%s/%s",
stream,
.Platform$pkgType,
R.Version()$os,
R.Version()$arch
))
Various types of R package dependencies
Description
Various types of R package dependencies
Details
include_docs("pkgdepends", "docs/deps.rds")
Install packages from CRAN, Bioconductor, GitHub, URLs, etc.
Description
Install packages from CRAN, Bioconductor, GitHub, URLs, etc. Learn how to tell pak which packages to install, and where those packages can be found.
If you want a quick overview of package sources, see "Get started with pak".
Details
include_docs("pkgdepends", "docs/pkg-refs.rds", top = FALSE)
System requirements
Description
pak takes care of your system requirements.
Introduction
Many R packages need external software to be present on the machine,
otherwise they do not work, or not even load. For example the RPostgres
R package uses the PostgreSQL client library, and by default dynamically
links to it on Linux systems. This means that you (or the administrators
of your system) need to install this library, typically in the form of a
system package: libpq-dev on Ubuntu and Debian systems, or
postgresql-server-devel or postgresql-devel on RedHat, Fedora, etc.
systems.
The good news is that pak helps you with this: - it looks up the
required system packages when installing R packages, - it checks if the
required system packages are installed, and - it installs them
automatically, if you are a superuser, or you can use password-less
sudo to start a superuser shell.
In addition, pak also has some functions to query system requirements and system packages.
Requirements, supported platforms
Call pak::sysreqs_platforms() to list all platforms that support
system requirements:
pak::sysreqs_platforms()
## # A data frame: 10 × 7 ## name os distribution version update_command install_command ## <chr> <chr> <chr> <chr> <chr> <chr> ## 1 Ubuntu Lin… linux ubuntu * apt-get -y up… apt-get -y ins… ## 2 Debian Lin… linux debian * apt-get -y up… apt-get -y ins… ## 3 CentOS Lin… linux centos * NA yum install -y ## 4 Rocky Linux linux rockylinux * NA dnf install -y ## 5 Red Hat En… linux redhat 6 NA yum install -y ## 6 Red Hat En… linux redhat 7 NA yum install -y ## 7 Red Hat En… linux redhat * NA dnf install -y ## 8 Fedora Lin… linux fedora * NA dnf install -y ## 9 openSUSE L… linux opensuse * NA zypper --non-i… ## 10 SUSE Linux… linux sle * NA zypper --non-i… ## # i 1 more variable: query_command <chr>
Call pak::sysreqs_is_supported() to see if your system is supported:
pak::sysreqs_is_supported()
## [1] TRUE
This vignette was built on Ubuntu 22.04.2 LTS, which is a platform pak does support. So in the following you will see the output of the code.
R package installation
If you are using pak as a superuser, on a supported platform, then pak will look up system requirements, and install the missing ones. Here is an example:
pak::pkg_install("RPostgres")
## v Loading metadata database ... done ## ## → Will install 17 packages. ## → All 17 packages (0 B) are cached. ## + DBI 1.1.3 ## + RPostgres 1.4.5 + x libpq-dev ## + Rcpp 1.0.10 ## + bit 4.0.5 ## + bit64 4.0.5 ## + blob 1.2.4 ## + cli 3.6.1 ## + generics 0.1.3 ## + glue 1.6.2 ## + hms 1.1.3 ## + lifecycle 1.0.3 ## + lubridate 1.9.2 ## + pkgconfig 2.0.3 ## + rlang 1.1.1 ## + timechange 0.2.0 ## + vctrs 0.6.2 ## + withr 2.5.0 ## → Will install 1 system package: ## + libpq-dev - RPostgres ## i No downloads are needed, 17 pkgs are cached ## i Installing system requirements ## i Executing `sh -c apt-get -y update` ## i Executing `sh -c apt-get -y install libpq-dev` ## v Installed DBI 1.1.3 (1.1s) ## v Installed RPostgres 1.4.5 (1.2s) ## v Installed Rcpp 1.0.10 (1.2s) ## v Installed bit 4.0.5 (1.2s) ## v Installed bit64 4.0.5 (148ms) ## v Installed blob 1.2.4 (63ms) ## v Installed cli 3.6.1 (88ms) ## v Installed generics 0.1.3 (61ms) ## v Installed glue 1.6.2 (63ms) ## v Installed hms 1.1.3 (62ms) ## v Installed lifecycle 1.0.3 (61ms) ## v Installed lubridate 1.9.2 (87ms) ## v Installed pkgconfig 2.0.3 (62ms) ## v Installed rlang 1.1.1 (1.1s) ## v Installed timechange 0.2.0 (1.1s) ## v Installed vctrs 0.6.2 (1.1s) ## v Installed withr 2.5.0 (1.1s) ## v 1 pkg + 16 deps: added 17 [17.5s]
Running R as a regular user
If you don’t want to use R as the superuser, but you can set up sudo
without a password, that works as well. pak will automatically detect
the password-less sudo capability, and use it to install system
packages, as needed.
If you run R as a regular (not root) user, and password-less sudo is
not available, then pak will print the system requirements, but it will
not try to install or update them. If you are installing source packages
that need to link to system libraries, then their installation will
probably fail, until you install these system packages. If you are
installing binary R packages, then the installation typically succeeds,
but you won’t be able to load these packages into R, until you install
the required system packages. Here is an example, on a system that does
not have the required system package installed for RPostgres. If you are
installing a source R package, the installation already fails:
pak::pkg_install("RPostgres?source")
## + plogr 0.2.0 ## x Missing 1 system package. You'll probably need to install it ## manually: ## + libpq-dev - RPostgres ## i No downloads are needed, 2 pkgs (1.47 MB) are cached ## v Installed plogr 0.2.0 (1.1s) ## i Building RPostgres 1.4.5 ## x Failed to build RPostgres 1.4.5 ## Registered S3 methods overwritten by 'callr': ## method from ## format.callr_status_error ## print.callr_status_error ## Error: ## ! error in pak subprocess ## Caused by error in `stop_task_build(state, worker)`: ## ! Failed to build source package 'RPostgres' ## Full installation output: ## * installing *source* package ‘RPostgres’ ... ## ** package ‘RPostgres’ successfully unpacked and MD5 sums checked ## staged installation is only possible with locking ## ** using non-staged installation ## Using PKG_CFLAGS= ## Using PKG_LIBS=-lpq ## Using PKG_PLOGR= ## ------------------------- ANTICONF ERROR --------------------------- ## Configuration failed because libpq was not found. Try installing: ## * deb: libpq-dev libssl-dev (Debian, Ubuntu, etc) ## * rpm: postgresql-devel (Fedora, EPEL) ## * rpm: postgreql8-devel, psstgresql92-devel, postgresql93-devel, or pos ## tgresql94-devel (Amazon Linux) ## * csw: postgresql_dev (Solaris) ## * brew: libpq (OSX) ## If libpq is already installed, check that either: ## (i) 'pkg-config' is in your PATH AND PKG_CONFIG_PATH contains ## a libpq.pc file; or ## (ii) 'pg_config' is in your PATH. ## If neither can detect , you can set INCLUDE_DIR ## and LIB_DIR manually via: ## R CMD INSTALL --configure-vars='INCLUDE_DIR=... LIB_DIR=...' ## --------------------------[ ERROR MESSAGE ]---------------------------- ## <stdin>:1:10: fatal error: libpq-fe.h: No such file or directory ## compilation terminated. ## ----------------------------------------------------------------------- ## ERROR: configuration failed for package ‘RPostgres’ ## * removing ‘/tmp/RtmpsOXbPZ/pkg-lib4a492949a49e/RPostgres’ ## --- ## Backtrace: ## 1. pak::pkg_install("RPostgres?source") ## 2. pak:::remote(function(...) get("pkg_install_do_plan", asNamespace("pa ## k")… at package.R:84:3 ## 3. err$throw(res$error) at subprocess.R:115:5 ## --- ## Subprocess backtrace: ## 1. base::withCallingHandlers(cli_message = function(msg) { … ## 2. get("pkg_install_do_plan", asNamespace("pak"))(...) ## 3. proposal$install() ## 4. pkgdepends::install_package_plan(plan, lib = private$library, num_wo ## rkers = nw… ## 5. base::withCallingHandlers({ … ## 6. pkgdepends:::handle_events(state, events) ## 7. pkgdepends:::handle_event(state, i) ## 8. pkgdepends:::stop_task(state, worker) ## 9. pkgdepends:::stop_task_build(state, worker) ## 10. base::throw(new_pkg_build_error("Failed to build source package {pkg ## }", … ## 11. | base::signalCondition(cond) ## 12. global (function (e) … ## Execution halted
On the other hand, if you are installing binary packages, e.g. from the Posit Package Manager, then the installation typically succeeds, but then loading the package fails:
pak::pkg_install("RPostgres")
library(RPostgres)
## → Will install 17 packages. ## → All 17 packages (0 B) are cached. ## + DBI 1.1.3 ## + RPostgres 1.4.5 + x libpq-dev ## + Rcpp 1.0.10 ## + bit 4.0.5 ## + bit64 4.0.5 ## + blob 1.2.4 ## + cli 3.6.1 ## + generics 0.1.3 ## + glue 1.6.2 ## + hms 1.1.3 ## + lifecycle 1.0.3 ## + lubridate 1.9.2 ## + pkgconfig 2.0.3 ## + rlang 1.1.1 ## + timechange 0.2.0 ## + vctrs 0.6.2 ## + withr 2.5.0 ## x Missing 1 system package. You'll probably need to install it ## manually: ## + libpq-dev - RPostgres ## i No downloads are needed, 17 pkgs are cached ## v Installed DBI 1.1.3 (1.1s) ## v Installed RPostgres 1.4.5 (1.1s) ## v Installed Rcpp 1.0.10 (1.2s) ## v Installed bit 4.0.5 (1.2s) ## v Installed bit64 4.0.5 (144ms) ## v Installed blob 1.2.4 (1.1s) ## v Installed cli 3.6.1 (1.1s) ## v Installed generics 0.1.3 (90ms) ## v Installed glue 1.6.2 (87ms) ## v Installed hms 1.1.3 (1.1s) ## v Installed lifecycle 1.0.3 (1.1s) ## v Installed lubridate 1.9.2 (1.1s) ## v Installed pkgconfig 2.0.3 (1.1s) ## v Installed rlang 1.1.1 (1.1s) ## v Installed timechange 0.2.0 (1.1s) ## v Installed vctrs 0.6.2 (1.1s) ## v Installed withr 2.5.0 (1.1s) ## v 1 pkg + 16 deps: added 17 [11.6s] ## Error: package or namespace load failed for ‘RPostgres’ in dyn.load(file ## , DLLpath = DLLpath, ...): ## unable to load shared object '/tmp/RtmpWqZycA/lib/RPostgres/libs/RPostg ## res.so': ## libpq.so.5: cannot open shared object file: No such file or directory ## Execution halted
Query system requirements without installation
If you only want to query system requirements, without installing any
packages, use the pkg_sysreqs() function. This is similar to
pkg_deps() but in addition to looking up package dependencies, it also
looks up system dependencies, and only reports the latter:
pak::pkg_sysreqs(c("curl", "xml2", "devtools", "CHRONOS"))
## v Loading metadata database ... done
## ── Install scripts ───────────────────────────────────── Ubuntu 22.04 ──
## apt-get -y update
## apt-get -y install libcurl4-openssl-dev libssl-dev libxml2-dev git make
## libgit2-dev zlib1g-dev pandoc libfreetype6-dev libjpeg-dev libpng-dev
## libtiff-dev libicu-dev libfontconfig1-dev libfribidi-dev
## libharfbuzz-dev libglpk-dev libgmp3-dev default-jdk
## R CMD javareconf
## R CMD javareconf
##
## ── Packages and their system dependencies ──────────────────────────────
## CHRONOS – default-jdk, pandoc
## credentials – git
## curl – libcurl4-openssl-dev, libssl-dev
## fs – make
## gert – libgit2-dev
## gitcreds – git
## httpuv – make, zlib1g-dev
## igraph – libglpk-dev, libgmp3-dev, libxml2-dev
## knitr – pandoc
## openssl – libssl-dev
## pkgdown – pandoc
## png – libpng-dev
## ragg – libfreetype6-dev, libjpeg-dev, libpng-dev, libtiff-dev
## RCurl – libcurl4-openssl-dev, make
## remotes – git
## rJava – default-jdk, make
## rmarkdown – pandoc
## sass – make
## stringi – libicu-dev
## systemfonts – libfontconfig1-dev, libfreetype6-dev
## textshaping – libfreetype6-dev, libfribidi-dev, libharfbuzz-dev
## XML – libxml2-dev
## xml2 – libxml2-dev
See the manual of pkg_sysreqs() to see how to programmatically extract
information from its return value.
Other queries
In addition to the automatic system package lookup and installation, pak
also has some other functions to help you with system dependencies. The
sysreqs_db_list() function lists all system requirements pak knows
about.
pak::sysreqs_db_list()
## # A data frame: 106 × 5 ## name patterns packages pre_install post_install ## <chr> <list> <list> <list> <list> ## 1 QuantLib <chr [1]> <chr [1]> <NULL> <NULL> ## 2 apparmor <chr [2]> <chr [1]> <NULL> <NULL> ## 3 atk <chr [1]> <chr [1]> <NULL> <NULL> ## 4 automake <chr [1]> <chr [1]> <NULL> <NULL> ## 5 berkeleydb <chr [2]> <chr [1]> <NULL> <NULL> ## 6 blender <chr [1]> <chr [1]> <NULL> <NULL> ## 7 bowtie2 <chr [1]> <chr [1]> <NULL> <NULL> ## 8 bwidget <chr [1]> <chr [1]> <NULL> <NULL> ## 9 cairo <chr [1]> <chr [1]> <NULL> <NULL> ## 10 chrome <chr [1]> <NULL> <chr [3]> <chr [1]> ## # i 96 more rows
sysreqs_db_match() manually matches SystemRequirements fields
against these system requirements:
sq <- pak::sysreqs_db_match("Needs libcurl and also Java.")
sq
## [[1]] ## # A data frame: 2 × 5 ## spec sysreq packages pre_install post_install ## <chr> <chr> <list> <list> <list> ## 1 Needs libcurl and also Java. java <chr> <NULL> <chr [1]> ## 2 Needs libcurl and also Java. libcurl <chr> <NULL> <NULL> ##
sq[[1]]$packages
## [[1]] ## [1] "default-jdk" ## ## [[2]] ## [1] "libcurl4-openssl-dev" ##
You can also use it to query system requirements for other platforms:
sqrhel9 <- pak::sysreqs_db_match("Needs libcurl and also Java.", "redhat-9")
sqrhel9
## [[1]] ## # A data frame: 2 × 5 ## spec sysreq packages pre_install post_install ## <chr> <chr> <list> <list> <list> ## 1 Needs libcurl and also Java. java <chr> <NULL> <chr [1]> ## 2 Needs libcurl and also Java. libcurl <chr> <NULL> <NULL> ##
sqrhel9[[1]]$packages
## [[1]] ## [1] "java-11-openjdk-devel" ## ## [[2]] ## [1] "libcurl-devel" ##
sysreqs_list_system_packages() is a cross-platform way of listing all
installed system packages and capabilities:
pak::sysreqs_list_system_packages()
## # A data frame: 433 × 4 ## status package version provides ## <chr> <chr> <chr> <list> ## 1 ii adduser 3.118ubuntu5 <chr [0]> ## 2 ii apt 2.4.8 <chr [1]> ## 3 ii autoconf 2.71-2 <chr [0]> ## 4 ii automake 1:1.16.5-1.3 <chr [2]> ## 5 ii autotools-dev 20220109.1 <chr [0]> ## 6 ii base-files 12ubuntu4.3 <chr [1]> ## 7 ii base-passwd 3.5.52build1 <chr [0]> ## 8 ii bash 5.1-6ubuntu1 <chr [0]> ## 9 ii binutils 2.38-4ubuntu2.1 <chr [2]> ## 10 ii binutils-common 2.38-4ubuntu2.1 <chr [0]> ## # i 423 more rows
sysreqs_check_installed() is a handy function that checks if all
system requirements are installed for some or all R packages that are
installed in your library:
pak::sysreqs_check_installed()
## system package installed required by ## -------------- -- ----------- ## git v gitcreds ## gsfonts v magick ## imagemagick v magick ## libarchive-dev v archive ## libcurl4-openssl-dev v curl ## libfontconfig1-dev v systemfonts ## libfreetype6-dev v ragg, systemfonts, textshaping ## libfribidi-dev v textshaping ## libharfbuzz-dev v textshaping ## libicu-dev v stringi ## libjpeg-dev v ragg ## libmagick++-dev v magick ## libnode-dev v V8 ## libpng-dev v ragg ## libpq-dev x RPostgres ## libssl-dev v curl, openssl ## libtiff-dev v ragg ## libxml2-dev v xml2 ## make v fs, sass ## pandoc v knitr, rmarkdown ## zlib1g-dev v data.table
sysreqs_fix_installed() goes one step further and also tries to
install the missing system requirements.
Build-time and run-time dependencies
The system requirements database that pak uses does not currently differentiate between build-time and run-time dependencies. A build-time dependency is a system package that you need when installing an R package from source. A run-time dependency is a system package that you need when using an R package. Most Linux distribution create (at least) two packages for each software library: a runtime package and a development package. For an R package that uses such a software library, the runtime package is a run-time dependency and the development package is a build-time dependency. However, pak does not currently know the difference between build-time and run-time dependencies, and it will install both types of dependencies, always. This means that pak usually installs system packages that are not strictly necessary. These are typically development packages of libraries, i.e. header files, and typically do not cause any issues. If you are short on disk space, then you can try removing them.
How it works
pak uses the database of system requirements at
https://github.com/rstudio/r-system-requirements. It has its own copy
of the database embedded into the package, and it also tries to download
updated versions of the database from GitHub, if its current copy is
older than one day. You can explicitly update the database from GitHub
using the sysreqs_db_update() function.
For CRAN packages, it downloads the SystemRequirements fields from
https://cran.r-pkg.org/metadata, which is a database updated daily.
For Bioconductor packages, it downloads then from GitHub. (We are
planning on moving CRAN database to GitHub as well.)
For packages sources that require pak to obtain a package DESCRIPTION
file (e.g. github::, git::, etc.), pak obtains SystemRequirements
directly from the DESCRIPTION file.
Once having the SystemRequirements fields, pak matches them to the
database, to obtain the canonized list of system requirements.
Then pak queries the local platform, to see the exact system packages needed. It also queries the installed system packages, to avoid trying to install system packages that are already installed.
Configuration
There are several pak configuration options you can use to adjust how
system requirements are handled. We will list some of them here, please
see the options with a sysreqs prefix in the ?pak-config manual page
for a complete and current list.
-
sysreqs: whether to install system requirements. The default isTRUEif the platform is supported and the user can install system packages, either because it is the superuser, or viasudo. If it isFALSE(or the user cannot install system packages), but the platform is supported, system requirements are printed, but not installed. -
sysreqs_db_update: whether to try to update the system requirements database from GitHub. -
sysreqs_db_update_timeout: timeout for the system requirements update from GitHub. -
sysreqs_dry_run: ifTRUEthen pak only prints the install commands, but does not actually run them. -
sysreqs_platform: the platform name to use for determining system requirements. Defaults to the current platform. If you are using a Linux distribution that is compatible with some distribution that pak supports, then you can set this option manually. E.g. Ubuntu-based distros can set it toubuntu-22.04, or the appropriate Ubuntu version. -
sysreqs_sudo: whether to usesudoto install system packages. If this is not set, then pak tries to auto-detect ifsudois needed or not. -
sysreqs_update: whether to try to update system packages that are already installed. pak does not know which version of a system package is required, and it does not try to update system packages by default. If you think that you need newer system packages, then you can set this option toTRUE. -
sysreqs_verbose: whether to print the output of the system package installation commands. Useful for debugging, and it isTRUEby default in a CI environment.
About other OSes
Windows
While the system requirements database has some information about system dependencies on Windows, pak does not use this information and it does not try to install system software on Windows. CRAN, PPM and Bioconductor have Windows binary packages available for the majority of R packages they serve, and these packages practically always link to system libraries statically, so they don’t need any external software.
If you wish to compile Windows packages from source, then you need to
install the appropriate version of Rtools, and possibly extra packages
using the pacman tool of Rtools4x.
Rtools42 and newer Rtools versions bundle lots of libraries, so most
likely no extra pacman packages are needed. Rtools40 has a leaner
default installation, and you’ll probably need to install packages
manually:
https://github.com/r-windows/docs/blob/master/rtools40.md#readme
We are planning on adding better Windows system software support to pak in the future.
macOS
pak does not currently have system requirement information for macOS. macOS is similar to Windows, in that most repositories will serve statically linked macOS binary packages that do not need system software.
If you do need to compile packages from source, then you possibly need to install some system libraries, either via Homebrew, or by downloading CRAN’s static library builds from https://mac.r-project.org/bin/
We are planning on adding better macOS system software support to pak in the future.
Find the ideal set of packages and versions to install
Description
pak contains a package dependency solver, that makes sure that the package source and version requirements of all packages are satisfied, before starting an installation. For CRAN and BioC packages this is usually automatic, because these repositories are generally in a consistent state. If packages depend on other other package sources, however, this is not the case.
Details
Here is an example of a conflict detected:
> pak::pkg_install(c("r-lib/pkgcache@conflict", "r-lib/cli@message"))
Error: Cannot install packages:
* Cannot install `r-lib/pkgcache@conflict`.
- Cannot install dependency r-lib/cli@main
* Cannot install `r-lib/cli@main`.
- Conflicts r-lib/cli@message
r-lib/pkgcache@conflict depends on the main branch of r-lib/cli,
whereas, we explicitly requested the message branch. Since it cannot
install both versions into a single library, pak quits.
When pak considers a package for installation, and the package is given with its name only, (e.g. as a dependency of another package), then the package may have any package source. This is necessary, because one R package library may contain only at most one version of a package with a given name.
pak's behavior is best explained via an example.
Assume that you are installing a local package (see below), e.g.
local::., and the local package depends on pkgA and user/pkgB,
the latter being a package from GitHub (see below), and that pkgA
also depends on pkgB. Now pak must install pkgB and user/pkgB.
In this case pak interprets pkgB as a package from any package source,
instead of a standard package, so installing user/pkgB satisfies both
requirements.
Note that that cran::pkgB and user/pkgB requirements result a
conflict that pak cannot resolve. This is because the first one must
be a CRAN package, and the second one must be a GitHub package, and
two different packages with the same cannot be installed into an R
package library.
Package cache utilities
Description
Various utilities to inspect and clean the package cache. See the pkgcache package if you need for control over the package cache.
Usage
cache_summary()
cache_list(...)
cache_delete(...)
cache_clean()
Arguments
... |
For |
Details
cache_summary() returns a summary of the package cache.
cache_list() lists all (by default), or a subset of
packages in the package cache.
cache_delete() deletes files from the cache.
cache_clean() deletes all files from the cache.
Value
cache_summary() returns a list with elements:
-
cachepath: absolute path to the package cache -
files: number of files (packages) in the cache -
size: total size of package cache in bytes
cache_list() returns a data frame with the data about the cache.
cache_delete() returns nothing.
cache_clean() returns nothing.
Examples
cache_summary()
#> $cachepath #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/pkg" #> #> $files #> [1] 483 #> #> $size #> [1] 654662486 #>
cache_list()
#> # A data frame: 483 × 11 #> fullpath path package url etag sha256 version platf…¹ built #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <int> #> 1 /Users/gaborc… arch… NA http… "\"1… 0c8f0… NA NA NA #> 2 /Users/gaborc… bin/… evalua… http… "\"1… 08a39… 0.17 aarch6… NA #> 3 /Users/gaborc… bin/… crayon http… "\"2… 1e6d5… 1.5.2 aarch6… NA #> 4 /Users/gaborc… bin/… common… http… "\"4… 47b4a… 1.8.1 aarch6… NA #> 5 /Users/gaborc… bin/… curl http… "\"b… 7b8ba… 4.3.3 aarch6… NA #> 6 /Users/gaborc… bin/… tinytex http… "\"2… 7e9ba… 0.42 aarch6… NA #> 7 /Users/gaborc… bin/… jsonli… http… "\"1… 68e59… 1.8.2 aarch6… NA #> 8 /Users/gaborc… bin/… lifecy… http… "\"1… 7ce27… 1.0.3 aarch6… NA #> 9 /Users/gaborc… bin/… vctrs http… "\"1… c3a69… 0.4.2 aarch6… NA #> 10 /Users/gaborc… src/… pkgcac… NA NA 9b70a… NA NA 0 #> # … with 473 more rows, 2 more variables: vignettes <int>, #> # rversion <chr>, and abbreviated variable name ¹platform
cache_list(package = "recipes")
#> # A data frame: 1 × 11 #> fullp…¹ path package url etag sha256 version platf…² built vigne…³ #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <int> <int> #> 1 /Users… bin/… recipes http… "\"1… e281e… 1.0.2 aarch6… NA NA #> # … with 1 more variable: rversion <chr>, and abbreviated variable #> # names ¹fullpath, ²platform, ³vignettes
cache_list(platform = "source")
#> # A data frame: 69 × 11 #> fullpath path package url etag sha256 version platf…¹ built #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <int> #> 1 /Users/gaborc… src/… crayon http… "\"9… 70a9a… 1.5.2 source NA #> 2 /Users/gaborc… src/… zip http… "\"1… 14873… 2.2.1 source NA #> 3 /Users/gaborc… src/… curl http… "\"a… 3567b… 4.3.3 source NA #> 4 /Users/gaborc… src/… rlang http… "\"b… e6973… 1.0.6 source NA #> 5 /Users/gaborc… src/… openssl http… "\"1… 7cde9… 2.0.3 source NA #> 6 /Users/gaborc… src/… tinytex http… "\"8… 205f7… 0.42 source NA #> 7 /Users/gaborc… src/… evalua… http… "\"6… 49c74… 0.17 source NA #> 8 /Users/gaborc… src/… Rcpp http… "\"2… 807ce… 1.0.9 source NA #> 9 /Users/gaborc… src/… knitr http… "\"d… 9b8f9… 1.40 source NA #> 10 /Users/gaborc… src/… lpSolve http… "\"7… f7258… 5.6.17 source NA #> # … with 59 more rows, 2 more variables: vignettes <int>, #> # rversion <chr>, and abbreviated variable name ¹platform
cache_delete(package = "knitr") cache_delete(platform = "macos")
cache_clean()
Install missing packages on the fly
Description
Use this function to set up a global error handler, that is called if R fails to load a package. This handler will offer you the choice of installing the missing package (and all its dependencies), and in some cases it can also remedy the error and restart the code.
Usage
handle_package_not_found(err)
Arguments
err |
The error object, of class |
Details
You are not supposed to call this function directly. Instead, set it
up as a global error handler, possibly in your .Rprofile file:
if (interactive() && getRversion() >= "4.0.0") {
globalCallingHandlers(
packageNotFoundError = function(err) {
try(pak::handle_package_not_found(err))
}
)
}
Global error handlers are only supported in R 4.0.0 and later.
Currently handle_package_not_found() does not do anything in
non-interactive mode (including in knitr, testthat and RStudio
notebooks), this might change in the future.
In some cases it is possible to remedy the original computation that
tried to load the missing package, and pak will offer you to do so
after a successful installation. Currently, in R 4.0.4, it is not
possible to continue a failed library() call.
Value
Nothing.
Status of packages in a library
Description
Status of packages in a library
Usage
lib_status(lib = .libPaths()[1])
pkg_list(lib = .libPaths()[1])
Arguments
lib |
Path to library. |
Value
Data frame the contains data about the packages
installed in the library.
include_docs("pkgdepends", "docs/lib-status-return.rds")
Examples
lib_status(.Library)
#> # A data frame: 31 × 31 #> library package version prior…¹ title license sugge…² built depends #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 /Library… base 4.2.2 base "The… Part o… methods R 4.… NA #> 2 /Library… boot 1.3-28 recomm… "Boo… Unlimi… MASS, … R 4.… R (>= … #> 3 /Library… class 7.3-20 recomm… "Fun… GPL-2 … NA R 4.… R (>= … #> 4 /Library… cluster 2.1.4 recomm… "\"F… GPL (>… MASS, … R 4.… R (>= … #> 5 /Library… codeto… 0.2-18 recomm… "Cod… GPL NA R 4.… R (>= … #> 6 /Library… compil… 4.2.2 base "The… Part o… NA R 4.… NA #> 7 /Library… datase… 4.2.2 base "The… Part o… NA R 4.… NA #> 8 /Library… filelo… 1.0.2 NA "Por… MIT + … callr … R 4.… NA #> 9 /Library… foreign 0.8-83 recomm… "Rea… GPL (>… NA R 4.… R (>= … #> 10 /Library… graphi… 4.2.2 base "The… Part o… NA R 4.… NA #> # … with 21 more rows, 22 more variables: needscompilation <lgl>, #> # repository <chr>, imports <chr>, remotetype <chr>, #> # remotepkgref <chr>, remoteref <chr>, remoterepos <chr>, #> # remotepkgplatform <chr>, remotesha <chr>, enhances <chr>, #> # linkingto <chr>, md5sum <chr>, platform <chr>, biocviews <chr>, #> # sysreqs <chr>, ref <chr>, type <chr>, status <chr>, rversion <chr>, #> # sources <list>, repotype <chr>, deps <list>, and abbreviated …
See Also
Other package functions:
pak(),
pkg_deps_tree(),
pkg_deps(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Dependencies of a package tree
Description
Dependencies of a package tree
Usage
local_deps(root = ".", upgrade = TRUE, dependencies = NA)
local_deps_tree(root = ".", upgrade = TRUE, dependencies = NA)
local_dev_deps(root = ".", upgrade = TRUE, dependencies = TRUE)
local_dev_deps_tree(root = ".", upgrade = TRUE, dependencies = TRUE)
Arguments
root |
Path to the package tree. |
upgrade |
Whether to use the most recent available package versions. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Value
All of these functions return the dependencies in a data
frame. local_deps_tree() and local_dev_deps_tree() also
print the dependency tree.
See Also
Other local package trees:
local_deps_explain(),
local_install_deps(),
local_install_dev_deps(),
local_install(),
local_package_trees,
pak()
Explain dependencies of a package tree
Description
These functions are similar to pkg_deps_explain(), but work on a
local package tree. local_dev_deps_explain() also includes development
dependencies.
Usage
local_deps_explain(deps, root = ".", upgrade = TRUE, dependencies = NA)
local_dev_deps_explain(deps, root = ".", upgrade = TRUE, dependencies = TRUE)
Arguments
deps |
Package names of the dependencies to explain. |
root |
Path to the package tree. |
upgrade |
Whether to use the most recent available package versions. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
See Also
Other local package trees:
local_deps(),
local_install_deps(),
local_install_dev_deps(),
local_install(),
local_package_trees,
pak()
Install a package tree
Description
Installs a package tree (or source package file), together with its dependencies.
Usage
local_install(
root = ".",
lib = .libPaths()[1],
upgrade = TRUE,
ask = interactive(),
dependencies = NA
)
Arguments
root |
Path to the package tree. |
lib |
Package library to install the packages to. Note that all
dependent packages will be installed here, even if they are
already installed in another library. The only exceptions are base
and recommended packages installed in |
upgrade |
When When |
ask |
Whether to ask for confirmation when installing a different version of a package that is already installed. Installations that only add new packages never require confirmation. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Details
local_install() is equivalent to pkg_install("local::.").
Value
Data frame, with information about the installed package(s).
See Also
Other local package trees:
local_deps_explain(),
local_deps(),
local_install_deps(),
local_install_dev_deps(),
local_package_trees,
pak()
Install the dependencies of a package tree
Description
Installs the hard dependencies of a package tree (or source package file), without installing the package tree itself.
Usage
local_install_deps(
root = ".",
lib = .libPaths()[1],
upgrade = TRUE,
ask = interactive(),
dependencies = NA
)
Arguments
root |
Path to the package tree. |
lib |
Package library to install the packages to. Note that all
dependent packages will be installed here, even if they are
already installed in another library. The only exceptions are base
and recommended packages installed in |
upgrade |
When When |
ask |
Whether to ask for confirmation when installing a different version of a package that is already installed. Installations that only add new packages never require confirmation. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Details
Note that development (and optional) dependencies, under Suggests in
DESCRIPTION, are not installed. If you want to install them as well,
use local_install_dev_deps().
Value
Data frame, with information about the installed package(s).
See Also
Other local package trees:
local_deps_explain(),
local_deps(),
local_install_dev_deps(),
local_install(),
local_package_trees,
pak()
Install all (development) dependencies of a package tree
Description
Installs all dependencies of a package tree (or source package file),
without installing the package tree itself. It installs the development
dependencies as well, specified in the Suggests field of
DESCRIPTION.
Usage
local_install_dev_deps(
root = ".",
lib = .libPaths()[1],
upgrade = TRUE,
ask = interactive(),
dependencies = TRUE
)
Arguments
root |
Path to the package tree. |
lib |
Package library to install the packages to. Note that all
dependent packages will be installed here, even if they are
already installed in another library. The only exceptions are base
and recommended packages installed in |
upgrade |
When When |
ask |
Whether to ask for confirmation when installing a different version of a package that is already installed. Installations that only add new packages never require confirmation. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
See Also
Other local package trees:
local_deps_explain(),
local_deps(),
local_install_deps(),
local_install(),
local_package_trees,
pak()
About local package trees
Description
pak can install packages from local package trees. This is convenient for package development. See the following functions:
-
local_install()installs a package from a package tree and all of its dependencies. -
local_install_deps()installs all hard dependencies of a package. -
local_install_dev_deps()installs all hard and soft dependencies of a package. This function is intended for package development.
Details
Note that the last two functions do not install the package in the
specified package tree itself, only its dependencies. This is convenient
if the package itself is loaded via some other means, e.g.
devtools::load_all(), for development.
See Also
Other local package trees:
local_deps_explain(),
local_deps(),
local_install_deps(),
local_install_dev_deps(),
local_install(),
pak()
Query system requirements
Description
![[Deprecated]](./figures/lifecycle-deprecated.svg)
Note that these functions are now deprecated, in favor of
pkg_sysreqs() and the sysreqs_* functions, which are more
powerful, as they work for all package sources (packages at Github,
GitLab, URLs, etc.) and they have more detailed output.
Instead of
pak::pkg_system_requirement("curl")
call
pak::pkg_sysreqs("curl")$install_scripts
and the equivalent of
pak::local_system_requirements()
is
pak::pkg_sysreqs("local::.", dependencies = TRUE)$install_script
Usage
local_system_requirements(
os = NULL,
os_release = NULL,
root = ".",
execute = FALSE,
sudo = execute,
echo = FALSE
)
pkg_system_requirements(
package,
os = NULL,
os_release = NULL,
execute = FALSE,
sudo = execute,
echo = FALSE
)
Arguments
os, os_release |
The operating system and operating system release
version, e.g. "ubuntu", "centos", "redhat". See
If |
root |
Path to the package tree. |
execute, sudo |
If |
echo |
If |
package |
Package names to lookup system requirements for. |
Details
Returns a character vector of commands to run that will install system requirements for the queried operating system.
local_system_requirements() queries system requirements for a dev package
(and its dependencies) given its root path.
pkg_system_requirements() queries system requirements for existing packages
(and their dependencies).
Value
A character vector of commands needed to install the system requirements for the package.
Examples
local_system_requirements("ubuntu", "20.04")
pkg_system_requirements("pak", "ubuntu", "20.04")
pkg_system_requirements("pak", "redhat", "7")
pkg_system_requirements("config", "ubuntu", "20.04") # no sys reqs
pkg_system_requirements("curl", "ubuntu", "20.04")
pkg_system_requirements("git2r", "ubuntu", "20.04")
pkg_system_requirements(c("config", "git2r", "curl"), "ubuntu", "20.04")
# queried packages must exist
pkg_system_requirements("iDontExist", "ubuntu", "20.04")
pkg_system_requirements(c("curl", "iDontExist"), "ubuntu", "20.04")
Create a lock file
Description
The lock file can be used later, possibly in a new R session, to carry
out the installation of the dependencies, with
lockfile_install().
Usage
lockfile_create(
pkg = "deps::.",
lockfile = "pkg.lock",
lib = NULL,
upgrade = FALSE,
dependencies = NA
)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
lockfile |
Path to the lock file. |
lib |
Package library to install the packages to. Note that all
dependent packages will be installed here, even if they are
already installed in another library. The only exceptions are base
and recommended packages installed in |
upgrade |
When When |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Details
Note, since the URLs of CRAN and most CRAN-like repositories change over time, in practice you cannot use the lock file much later. For example, binary packages of older package version might be deleted from the repository, breaking the URLs in the lock file.
Currently the intended use case of lock files in on CI systems, to facilitate caching. The (hash of the) lock file provides a good key for caching systems.
See Also
Other lock files:
lockfile_install()
Install packages based on a lock file
Description
Install a lock file that was created with lockfile_create().
Usage
lockfile_install(lockfile = "pkg.lock", lib = .libPaths()[1], update = TRUE)
Arguments
lockfile |
Path to the lock file. |
lib |
Library to carry out the installation on. |
update |
Whether to online install the packages that
either not installed in |
See Also
Other lock files:
lockfile_create()
Metadata cache utilities
Description
Various utilities to inspect, update and clean the metadata cache. See the pkgcache package if you need for control over the metadata cache.
Usage
meta_summary()
meta_list(pkg = NULL)
meta_update()
meta_clean(force = FALSE)
Arguments
pkg |
Package names, if specified then only entries for |
force |
If |
Details
meta_summary() returns a summary of the metadata cache.
meta_list() lists all (or some) packages in the metadata
database.
meta_update() updates the metadata database. You don't
normally need to call this function manually, because all pak functions
(e.g. pkg_install(), pkg_download(), etc.) call it automatically,
to make sure that they use the latest available metadata.
meta_clean() deletes the whole metadata DB.
Value
meta_summary() returns a list with entries:
-
cachepath: absolute path of the metadata cache. -
current_db: the file that contains the current metadata database. It is currently an RDS file, but this might change in the future. -
raw_files: the files that are the downloadedPACKAGES*files. -
db_files: all metadata database files. -
size: total size of the metadata cache.
meta_list() returns a data frame of all available
packages in the configured repositories.
meta_update() returns nothing.
meta_clean() returns nothing
Examples
Metadata cache summary:
meta_summary() #> $cachepath #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata" #> #> $current_db #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/pkgs-34444e3072.rds" #> #> $raw_files #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCann-59693086a0/bin/macosx/big-sur-arm64/contrib/4.2/PACKAGES.gz" #> [2] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCann-59693086a0/src/contrib/PACKAGES.gz" #> [3] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCexp-90d4a3978b/bin/macosx/big-sur-arm64/contrib/4.2/PACKAGES.gz" #> [4] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCexp-90d4a3978b/src/contrib/PACKAGES.gz" #> [5] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCsoft-2a43920999/bin/macosx/big-sur-arm64/contrib/4.2/PACKAGES.gz" #> [6] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCsoft-2a43920999/src/contrib/PACKAGES.gz" #> [7] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCworkflows-26330ba3ca/bin/macosx/big-sur-arm64/contrib/4.2/PACKAGES.gz" #> [8] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/BioCworkflows-26330ba3ca/src/contrib/PACKAGES.gz" #> [9] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/CRAN-075c426938/bin/macosx/big-sur-arm64/contrib/4.2/PACKAGES.gz" #> [10] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/CRAN-075c426938/src/contrib/PACKAGES.gz" #> #> $db_files #> [1] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/pkgs-34444e3072.rds" #> [2] "/Users/gaborcsardi/Library/Caches/org.R-project.R/R/pkgcache/_metadata/pkgs-ccacf1b389.rds" #> #> $size #> [1] 174848200
The current metadata DB:
meta_list()
#> v Loading metadata database ... done #> # A data frame: 45,279 × 32 #> package version depends sugge…¹ license imports linki…² archs enhan…³ #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 A3 1.0.0 R (>= … random… GPL (>… NA NA NA NA #> 2 AATtoo… 0.0.2 R (>= … NA GPL-3 magrit… NA NA NA #> 3 ABACUS 1.0.0 R (>= … rmarkd… GPL-3 ggplot… NA NA NA #> 4 ABC.RAP 0.9.0 R (>= … knitr,… GPL-3 graphi… NA NA NA #> 5 ABCana… 1.2.1 R (>= … NA GPL-3 plotrix NA NA NA #> 6 ABCopt… 0.15.0 NA testth… MIT + … Rcpp, … Rcpp ABCo… NA #> 7 ABCp2 1.2 MASS NA GPL-2 NA NA NA NA #> 8 ABHgen… 1.0.1 NA knitr,… GPL-3 ggplot… NA NA NA #> 9 ABPS 0.3 NA testth… GPL (>… kernlab NA NA NA #> 10 ACA 1.1 R (>= … NA GPL graphi… NA NA NA #> # … with 45,269 more rows, 23 more variables: #> # license_restricts_use <chr>, os_type <chr>, priority <chr>, #> # license_is_foss <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>, …
Selected packages only:
meta_list(pkg = c("shiny", "htmlwidgets"))
#> package version depends sugge…¹ license imports linki…² archs enhan…³ #> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 htmlwid… 1.5.4 NA "knitr… MIT + … "grDev… NA NA shiny … #> 2 shiny 1.7.3 R (>= … "datas… GPL-3 … "utils… NA NA NA #> 3 htmlwid… 1.6.0 NA "testt… MIT + … "grDev… NA NA shiny … #> 4 shiny 1.7.4 R (>= … "datas… GPL-3 … "utils… NA NA NA #> # … with 23 more variables: license_restricts_use <chr>, os_type <chr>, #> # priority <chr>, license_is_foss <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>, and abbreviated variable names ¹suggests, ²linkingto, #> …
Update the metadata DB
meta_update()
#> v Updated metadata database: 1.23 MB in 1 file. #> v Updating metadata database ... done
Delete the metadata DB
meta_clean()
#> i Cleaning up cache directory /Users/gaborcsardi/Library/Caches/org.R-pr #> oject.R/R/pkgcache/_metadata.
Install specified required packages
Description
Install the specified packages, or the ones required by the package or project in the current working directory.
Usage
pak(pkg = NULL, ...)
Arguments
pkg |
Package names or remote package specifications to install.
See pak package sources for details. If |
... |
Extra arguments are passed to |
Details
This is a convenience function:
If you want to install some packages, it is easier to type than
pkg_install().If you want to install all the packages that are needed for the development of a package or project, then it is easier to type than
local_install_dev_deps().You don't need to remember two functions to install packages, just one.
See Also
Other package functions:
lib_status(),
pkg_deps_tree(),
pkg_deps(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Other local package trees:
local_deps_explain(),
local_deps(),
local_install_deps(),
local_install_dev_deps(),
local_install(),
local_package_trees
Environment variables and options that modify the default behavior
Description
pak behavior can be finetuned with environment variables and
options (as in base::options()).
R options affecting pak's behavior
Ncpus
Set to the desired number of worker processes for package installation. If not set, then pak will use the number of logical processors in the machine.
repos
The CRAN-like repositories to use. See base::options() for details.
pak configuration
Configuration entries (unless noted otherwise on this manual page) have a corresponding environment variable, and a corresponding option.
The environment variable is always uppercase and uses underscores as the
word separator. It always has the PKG_ prefix.
The option is typically lowercase, use it uses underscores as the word
separator, but it always has the pkg. prefix (notice the dot!).
Some examples:
| Config entry name | Env var name | Option name |
| platforms | PKG_PLATFORMS | pkg.platforms |
| cran_mirror | PKG_CRAN_MIRROR | pkg.cran_mirror |
pak configuration entries
doc_config()
Notes
From version 0.4.0 pak copies the PKG_* environment variables and
the pkg.* options to the pak subprocess, where they are actually
used, so you don't need to restart R or reload pak after a
configuration change.
Clean up pak caches
Description
Clean up pak caches
Usage
pak_cleanup(
package_cache = TRUE,
metadata_cache = TRUE,
pak_lib = TRUE,
force = FALSE
)
Arguments
package_cache |
Whether to clean up the cache of package files. |
metadata_cache |
Whether to clean up the cache of package meta data. |
pak_lib |
This argument is now deprecated and does nothing. |
force |
Do not ask for confirmation. Note that to use this function
in non-interactive mode, you have to specify |
See Also
Other pak housekeeping:
pak_sitrep()
Install all optional dependencies of pak
Description
These packages are not required for any pak functionality. They are recommended for some functions that return values that are best used with these packages. E.g. many functions return data frames, which print nicer when the pillar package is available.
Usage
pak_install_extra(upgrade = FALSE)
Arguments
upgrade |
Whether to install or upgrade to the latest versions of the optional packages. |
Details
Currently only one package is optional: pillar.
Set up private pak library (deprecated)
Description
This function is deprecated and does nothing.
Recent versions of pak do not need a pak_setup() call.
Usage
pak_setup(mode = c("auto", "download", "copy"), quiet = FALSE)
Arguments
mode |
Where to get the packages from. "download" will try to download them from CRAN. "copy" will try to copy them from your current "regular" package library. "auto" will try to copy first, and if that fails, then it tries to download. |
quiet |
Whether to omit messages. |
Value
The path to the private library, invisibly.
pak SITuation REPort
Description
It prints
pak version,
platform the package was built on, and the current platform,
the current library path,
versions of dependencies,
whether dependencies can be loaded.
Usage
pak_sitrep()
Examples
pak_sitrep()
#> compatible) #> - pak repository: - (local install?) #> * Optional packages installed: #> - pillar #> * Library path: #> - /private/var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpRxl7Vu/fi #> le1868066d6ae59 #> - /private/var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpRxl7Vu/fi #> le186806281b34a #> - /Users/gaborcsardi/Library/R/arm64/4.3/library #> - /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library #> * Private library location: #> - /Users/gaborcsardi/Library/Caches/org.R-project.R/R/pak/lib/4.3/aarch6 #> 4 #> * Private library exists. #> * Private library is functional
See Also
Other pak housekeeping:
pak_cleanup()
Update pak itself
Description
Use this function to update the released or development version of pak.
Usage
pak_update(force = FALSE, stream = c("auto", "stable", "rc", "devel"))
Arguments
force |
Whether to force an update, even if no newer version is available. |
stream |
Whether to update to the
Often there is no release candidate version, then |
Value
Nothing.
Look up the dependencies of a package
Description
Look up the dependencies of a package
Usage
pkg_deps(pkg, upgrade = TRUE, dependencies = NA)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
upgrade |
Whether to use the most recent available package versions. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Value
A data frame with the dependency data, it includes pkg
as well. It has the following columns.
include_docs("pkgdepends", "docs/resolution-result.rds")
Examples
pkg_deps("dplyr")
#> # A data frame: 16 × 32 #> ref type direct direc…¹ status package version license needs…² #> <chr> <chr> <lgl> <lgl> <chr> <chr> <chr> <chr> <lgl> #> 1 R6 stan… FALSE FALSE OK R6 2.5.1 MIT + … FALSE #> 2 cli stan… FALSE FALSE OK cli 3.4.1 MIT + … FALSE #> 3 dplyr stan… TRUE TRUE OK dplyr 1.0.10 MIT + … FALSE #> 4 fansi stan… FALSE FALSE OK fansi 1.0.3 GPL-2 … FALSE #> 5 generics stan… FALSE FALSE OK generi… 0.1.3 MIT + … FALSE #> 6 glue stan… FALSE FALSE OK glue 1.6.2 MIT + … FALSE #> 7 lifecycle stan… FALSE FALSE OK lifecy… 1.0.3 MIT + … FALSE #> 8 magrittr stan… FALSE FALSE OK magrit… 2.0.3 MIT + … FALSE #> 9 pillar stan… FALSE FALSE OK pillar 1.8.1 MIT + … FALSE #> 10 pkgconfig stan… FALSE FALSE OK pkgcon… 2.0.3 MIT + … FALSE #> 11 rlang stan… FALSE FALSE OK rlang 1.0.6 MIT + … FALSE #> 12 tibble stan… FALSE FALSE OK tibble 3.1.8 MIT + … FALSE #> 13 tidysele… stan… FALSE FALSE OK tidyse… 1.2.0 MIT + … FALSE #> 14 utf8 stan… FALSE FALSE OK utf8 1.2.2 Apache… FALSE #> 15 vctrs stan… FALSE FALSE OK vctrs 0.5.1 MIT + … FALSE #> 16 withr stan… FALSE FALSE OK withr 2.5.0 MIT + … FALSE #> # … with 23 more variables: priority <chr>, md5sum <chr>, sha256 <chr>, #> # filesize <int>, built <chr>, platform <chr>, rversion <chr>, #> # repotype <chr>, repodir <chr>, target <chr>, deps <list>, #> # mirror <chr>, sources <list>, remote <list>, error <list>, #> # metadata <list>, dep_types <list>, params <list>, sysreqs <chr>, #> # cache_status <chr>, lib_status <chr>, old_version <chr>, #> # new_version <chr>, and abbreviated variable names ¹directpkg, …
For a package on GitHub:
pkg_deps("r-lib/callr")
#> # A data frame: 4 × 32 #> ref type direct direc…¹ status package version license needs…² #> <chr> <chr> <lgl> <lgl> <chr> <chr> <chr> <chr> <lgl> #> 1 r-lib/cal… gith… TRUE TRUE OK callr 3.7.3.… MIT + … TRUE #> 2 R6 stan… FALSE FALSE OK R6 2.5.1 MIT + … FALSE #> 3 processx stan… FALSE FALSE OK proces… 3.8.0 MIT + … FALSE #> 4 ps stan… FALSE FALSE OK ps 1.7.2 MIT + … FALSE #> # … with 23 more variables: priority <chr>, md5sum <chr>, sha256 <chr>, #> # filesize <int>, built <chr>, platform <chr>, rversion <chr>, #> # repotype <chr>, repodir <chr>, target <chr>, deps <list>, #> # mirror <chr>, sources <list>, remote <list>, error <list>, #> # metadata <list>, dep_types <list>, params <list>, sysreqs <chr>, #> # cache_status <chr>, lib_status <chr>, old_version <chr>, #> # new_version <chr>, and abbreviated variable names ¹directpkg, …
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps_tree(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Explain how a package depends on other packages
Description
Extract dependency chains from pkg to deps.
Usage
pkg_deps_explain(pkg, deps, upgrade = TRUE, dependencies = NA)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
deps |
Package names of the dependencies to explain. |
upgrade |
Whether to use the most recent available package versions. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Details
This function is similar to pkg_deps_tree(), but its output is easier
to read if you are only interested is certain packages (deps).
Value
A named list with a print method. First entries are the
function arguments: pkg, deps, dependencies, the last one is
paths and it contains the results in a named list, the names are
the package names in deps.
Examples
How does dplyr depend on rlang?
pkg_deps_explain("dplyr", "rlang")
#> v Updated metadata database: 5.09 MB in 12 files. #> v Updating metadata database ... done #> dplyr -> lifecycle -> rlang #> dplyr -> rlang #> dplyr -> tibble -> lifecycle -> rlang #> dplyr -> tibble -> pillar -> lifecycle -> rlang #> dplyr -> tibble -> pillar -> rlang #> dplyr -> tibble -> pillar -> vctrs -> lifecycle -> rlang #> dplyr -> tibble -> pillar -> vctrs -> rlang #> dplyr -> tibble -> rlang #> dplyr -> tibble -> vctrs -> lifecycle -> rlang #> dplyr -> tibble -> vctrs -> rlang #> dplyr -> tidyselect -> lifecycle -> rlang #> dplyr -> tidyselect -> rlang #> dplyr -> tidyselect -> vctrs -> lifecycle -> rlang #> dplyr -> tidyselect -> vctrs -> rlang #> dplyr -> vctrs -> lifecycle -> rlang #> dplyr -> vctrs -> rlang #> dplyr -> pillar -> lifecycle -> rlang #> dplyr -> pillar -> rlang #> dplyr -> pillar -> vctrs -> lifecycle -> rlang #> dplyr -> pillar -> vctrs -> rlang
How does the GH version of usethis depend on cli and ps?
pkg_deps_explain("r-lib/usethis", c("cli", "ps"))
#> usethis -> cli #> usethis -> desc -> cli #> usethis -> gh -> cli #> usethis -> lifecycle -> cli #> #> x ps
Draw the dependency tree of a package
Description
Draw the dependency tree of a package
Usage
pkg_deps_tree(pkg, upgrade = TRUE, dependencies = NA)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
upgrade |
Whether to use the most recent available package versions. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Value
The same data frame as pkg_deps(), invisibly.
Examples
pkg_deps_tree("dplyr")
#> dplyr 1.0.10 ✨ #> ├─generics 0.1.3 ✨ #> ├─glue 1.6.2 ✨ #> ├─lifecycle 1.0.3 ✨ #> │ ├─cli 3.4.1 ✨ #> │ ├─glue #> │ └─rlang 1.0.6 ✨ #> ├─magrittr 2.0.3 ✨ #> ├─R6 2.5.1 ✨ #> ├─rlang #> ├─tibble 3.1.8 ✨ #> │ ├─fansi 1.0.3 ✨ #> │ ├─lifecycle #> │ ├─magrittr #> │ ├─pillar 1.8.1 ✨ #> │ │ ├─cli #> │ │ ├─fansi #> │ │ ├─glue #> │ │ ├─lifecycle #> │ │ ├─rlang #> │ │ ├─utf8 1.2.2 ✨ #> │ │ └─vctrs 0.5.1 ✨ #> │ │ ├─cli #> │ │ ├─glue #> │ │ ├─lifecycle #> │ │ └─rlang #> │ ├─pkgconfig 2.0.3 ✨ #> │ ├─rlang #> │ └─vctrs #> ├─tidyselect 1.2.0 ✨ #> │ ├─cli #> │ ├─glue #> │ ├─lifecycle #> │ ├─rlang #> │ ├─vctrs #> │ └─withr 2.5.0 ✨ #> ├─vctrs #> └─pillar #> #> Key: ✨ new
pkg_deps_tree("r-lib/usethis")
#> r-lib/usethis 2.1.6.9000 ✨👷🏼🔧 #> ├─cli 3.4.1 ✨ #> ├─clipr 0.8.0 ✨ #> ├─crayon 1.5.2 ✨ #> ├─curl 4.3.3 ✨ #> ├─desc 1.4.2 ✨ #> │ ├─cli #> │ ├─R6 2.5.1 ✨ #> │ └─rprojroot 2.0.3 ✨ #> ├─fs 1.5.2 ✨ #> ├─gert 1.9.2 ✨ ⬇ (1.91 MB) #> │ ├─askpass 1.1 ✨ #> │ │ └─sys 3.4.1 ✨ #> │ ├─credentials 1.3.2 ✨ ⬇ (170.15 kB) #> │ │ ├─openssl 2.0.5 ✨ #> │ │ │ └─askpass #> │ │ ├─sys #> │ │ ├─curl #> │ │ ├─jsonlite 1.8.4 ✨ #> │ │ └─askpass #> │ ├─openssl #> │ ├─rstudioapi 0.14 ✨ #> │ ├─sys #> │ └─zip 2.2.2 ✨ #> ├─gh 1.3.1 ✨ ⬇ (95.20 kB) #> │ ├─cli #> │ ├─gitcreds 0.1.2 ✨ ⬇ (95.59 kB) #> │ ├─httr 1.4.4 ✨ #> │ │ ├─curl #> │ │ ├─jsonlite #> │ │ ├─mime 0.12 ✨ #> │ │ ├─openssl #> │ │ └─R6 #> │ ├─ini 0.3.1 ✨ ⬇ (13.13 kB) #> │ └─jsonlite #> ├─glue 1.6.2 ✨ #> ├─jsonlite #> ├─lifecycle 1.0.3 ✨ #> │ ├─cli #> │ ├─glue #> │ └─rlang 1.0.6 ✨ #> ├─purrr 0.3.5 ✨ #> │ ├─magrittr 2.0.3 ✨ #> │ └─rlang #> ├─rappdirs 0.3.3 ✨ #> ├─rlang #> ├─rprojroot #> ├─rstudioapi #> ├─whisker 0.4.1 ✨ ⬇ (65.36 kB) #> ├─withr 2.5.0 ✨ #> └─yaml 2.3.6 ✨ #> #> Key: ✨ new | ⬇ download | 👷🏼 build | 🔧 compile
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Download a package and its dependencies
Description
TODO: explain result
Usage
pkg_download(
pkg,
dest_dir = ".",
dependencies = FALSE,
platforms = NULL,
r_versions = NULL
)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
dest_dir |
Destination directory for the packages. If it does not exist, then it will be created. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
platforms |
Types of binary or source packages to download. The
default is the value of |
r_versions |
R version(s) to download packages for. (This does not matter for source packages, but it does for binaries.) It defaults to the current R version. |
Value
Data frame with information about the downloaded
packages, invisibly. Columns:
include_docs("pkgdepends", "docs/download-result.rds")
Examples
dl <- pkg_download("forcats")
#> i No downloads are needed, 2 pkgs (641.53 kB) are cached
dl
#> # A data frame: 2 × 35 #> ref type direct direc…¹ status package version license needs…² #> <chr> <chr> <lgl> <lgl> <chr> <chr> <chr> <chr> <lgl> #> 1 forcats standard TRUE TRUE OK forcats 0.5.2 MIT + … FALSE #> 2 forcats standard TRUE TRUE OK forcats 0.5.2 MIT + … FALSE #> # … with 26 more variables: priority <chr>, md5sum <chr>, sha256 <chr>, #> # filesize <int>, built <chr>, platform <chr>, rversion <chr>, #> # repotype <chr>, repodir <chr>, target <chr>, deps <list>, #> # mirror <chr>, sources <list>, remote <list>, error <list>, #> # metadata <list>, extra <list>, dep_types <list>, params <list>, #> # sysreqs <chr>, cache_status <chr>, fulltarget <chr>, #> # fulltarget_tree <chr>, download_status <chr>, …
dl$fulltarget
#> [1] "./bin/macosx/big-sur-arm64/contrib/4.2/forcats_0.5.2.tgz" #> [2] "./src/contrib/forcats_0.5.2.tar.gz"
pkg_download("r-lib/pak", platforms = "source")
#> i No downloads are needed, 1 pkg is cached
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps_tree(),
pkg_deps(),
pkg_install(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Query the history of a CRAN package
Description
Query the history of a CRAN package
Usage
pkg_history(pkg)
Arguments
pkg |
Package name. |
Value
A data frame, with one row per package version. The columns are
the entries of the DESCRIPTION files in the released package
versions.
Examples
pkg_history("ggplot2")
#> # A data frame: 44 × 30 #> Package Type Title Version Date Author Maint…¹ Descr…² License #> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 ggplot2 Package An impl… 0.5 2007… Hadle… Hadley… "An im… GPL #> 2 ggplot2 Package An impl… 0.5.1 2007… Hadle… Hadley… "An im… GPL #> 3 ggplot2 Package An impl… 0.5.2 2007… Hadle… Hadley… "An im… GPL #> 4 ggplot2 Package An impl… 0.5.4 2007… Hadle… Hadley… "An im… GPL #> 5 ggplot2 Package An impl… 0.5.5 2007… Hadle… Hadley… "An im… GPL #> 6 ggplot2 Package An impl… 0.5.6 2007… Hadle… Hadley… "An im… GPL #> 7 ggplot2 Package An impl… 0.5.7 2007… Hadle… Hadley… "An im… GPL #> 8 ggplot2 Package An impl… 0.6 2008… Hadle… Hadley… "An im… GPL #> 9 ggplot2 Package An impl… 0.7 2008… Hadle… Hadley… "An im… GPL #> 10 ggplot2 Package An impl… 0.8 2008… Hadle… Hadley… "An im… GPL #> # … with 34 more rows, 21 more variables: SaveImage <chr>, #> # LazyData <chr>, Packaged <chr>, crandb_file_date <chr>, date <chr>, #> # dependencies <list>, URL <chr>, LazyLoad <chr>, Extends <chr>, #> # Collate <chr>, Repository <chr>, `Date/Publication` <chr>, #> # NeedsCompilation <chr>, VignetteBuilder <chr>, BugReports <chr>, #> # `Authors@R` <chr>, RoxygenNote <chr>, Encoding <chr>, MD5sum <chr>, #> # `Config/Needs/website` <chr>, `Config/testthat/edition` <chr>, …
Install packages
Description
Install one or more packages and their dependencies into a single package library.
Usage
pkg_install(
pkg,
lib = .libPaths()[[1L]],
upgrade = FALSE,
ask = interactive(),
dependencies = NA
)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
lib |
Package library to install the packages to. Note that all
dependent packages will be installed here, even if they are
already installed in another library. The only exceptions are base
and recommended packages installed in |
upgrade |
When When |
ask |
Whether to ask for confirmation when installing a different version of a package that is already installed. Installations that only add new packages never require confirmation. |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
Value
(Invisibly) A data frame with information about the installed package(s).
Examples
pkg_install("dplyr")
#> #> → Will install 5 packages. #> → All 5 packages (2.14 MB) are cached. #> + dplyr 1.0.9 #> + generics 0.1.2 #> + purrr 0.3.4 #> + R6 2.5.1 #> + tidyselect 1.1.2 #> i No downloads are needed, 5 pkgs (2.14 MB) are cached #> v Got R6 2.5.1 (aarch64-apple-darwin20) (82.52 kB) #> v Installed R6 2.5.1 (43ms) #> v Installed generics 0.1.2 (62ms) #> v Installed dplyr 1.0.9 (88ms) #> v Installed purrr 0.3.4 (88ms) #> v Installed tidyselect 1.1.2 (94ms) #> v 1 pkg + 17 deps: kept 12, added 5, dld 1 (82.52 kB) [1.2s]
Upgrade dplyr and all its dependencies:
pkg_install("dplyr", upgrade = TRUE)
#> #> → Will update 1 package. #> → The package (742.51 kB) is cached. #> + rlang 1.0.2 → 1.0.3 👷🏿♀️🔧 #> i No downloads are needed, 1 pkg (742.51 kB) is cached #> i Building rlang 1.0.3 #> v Built rlang 1.0.3 (5.8s) #> v Installed rlang 1.0.3 (32ms) #> v 1 pkg + 17 deps: kept 17, upd 1 [6.3s]
Install the development version of dplyr:
pkg_install("tidyverse/dplyr")
#> v Loading metadata database ... done #> #> → Will install 16 packages. #> → All 16 packages (8.09 MB) are cached. #> + cli 3.4.1 #> + dplyr 1.0.99.9000 👷🏾♂️🔧 (GitHub: e6252f8) #> + fansi 1.0.3 #> + generics 0.1.3 #> + glue 1.6.2 #> + lifecycle 1.0.3 #> + magrittr 2.0.3 #> + pillar 1.8.1 #> + pkgconfig 2.0.3 #> + R6 2.5.1 #> + rlang 1.0.6 #> + tibble 3.1.8 #> + tidyselect 1.2.0 #> + utf8 1.2.2 #> + vctrs 0.5.1 #> + withr 2.5.0 #> i No downloads are needed, 16 pkgs (8.09 MB) are cached #> v Installed R6 2.5.1 (58ms) #> v Installed cli 3.4.1 (69ms) #> v Installed fansi 1.0.3 (92ms) #> v Installed generics 0.1.3 (99ms) #> v Installed glue 1.6.2 (108ms) #> v Installed lifecycle 1.0.3 (144ms) #> v Installed magrittr 2.0.3 (152ms) #> v Installed pillar 1.8.1 (160ms) #> v Installed pkgconfig 2.0.3 (63ms) #> v Installed rlang 1.0.6 (37ms) #> v Installed tibble 3.1.8 (41ms) #> v Installed tidyselect 1.2.0 (38ms) #> v Installed utf8 1.2.2 (36ms) #> v Installed vctrs 0.5.1 (39ms) #> v Installed withr 2.5.0 (30ms) #> i Packaging dplyr 1.0.99.9000 #> v Packaged dplyr 1.0.99.9000 (8.3s) #> i Building dplyr 1.0.99.9000 #> v Built dplyr 1.0.99.9000 (5.2s) #> v Installed dplyr 1.0.99.9000 (github::tidyverse/dplyr@e6252f8) (24ms) #> v 1 pkg + 15 deps: added 16 [18.9s]
Switch back to the CRAN version. This will be fast because pak will have cached the prior install.
pkg_install("dplyr")
#> v Updated metadata database: 2.43 MB in 6 files. #> v Updating metadata database ... done #> #> → Will install 16 packages. #> → All 16 packages (9.42 MB) are cached. #> + cli 3.4.1 #> + dplyr 1.0.10 #> + fansi 1.0.3 #> + generics 0.1.3 #> + glue 1.6.2 #> + lifecycle 1.0.3 #> + magrittr 2.0.3 #> + pillar 1.8.1 #> + pkgconfig 2.0.3 #> + R6 2.5.1 #> + rlang 1.0.6 #> + tibble 3.1.8 #> + tidyselect 1.2.0 #> + utf8 1.2.2 #> + vctrs 0.5.1 #> + withr 2.5.0 #> i No downloads are needed, 16 pkgs (9.42 MB) are cached #> v Installed R6 2.5.1 (66ms) #> v Installed cli 3.4.1 (76ms) #> v Installed dplyr 1.0.10 (111ms) #> v Installed fansi 1.0.3 (119ms) #> v Installed generics 0.1.3 (125ms) #> v Installed glue 1.6.2 (132ms) #> v Installed lifecycle 1.0.3 (149ms) #> v Installed magrittr 2.0.3 (162ms) #> v Installed pillar 1.8.1 (56ms) #> v Installed pkgconfig 2.0.3 (35ms) #> v Installed rlang 1.0.6 (57ms) #> v Installed tibble 3.1.8 (41ms) #> v Installed tidyselect 1.2.0 (40ms) #> v Installed utf8 1.2.2 (37ms) #> v Installed vctrs 0.5.1 (39ms) #> v Installed withr 2.5.0 (31ms) #> v 1 pkg + 15 deps: added 16 [7.2s]
See Also
Get started with pak, Package sources, FAQ, The dependency solver.
Other package functions:
lib_status(),
pak(),
pkg_deps_tree(),
pkg_deps(),
pkg_download(),
pkg_remove(),
pkg_status(),
pkg_sysreqs()
Check if an R package name is available
Description
Additionally, look up the candidate name in a number of dictionaries, to make sure that it does not have a negative meaning.
Usage
pkg_name_check(name, dictionaries = NULL)
Arguments
name |
Package name candidate. |
dictionaries |
Character vector, the dictionaries to query.
Available dictionaries:
* |
Details
Valid package name check
Check the validity of name as a package name. See 'Writing R
Extensions' for the allowed package names. Also checked against a list
of names that are known to cause problems.
CRAN checks
Check name against the names of all past and current packages on
CRAN, including base and recommended packages.
Bioconductor checks
Check name against all past and current Bioconductor packages.
Profanity check
Check name with https://www.purgomalum.com/service/containsprofanity
to make sure it is not a profanity.
Dictionaries
See the dictionaries argument.
Value
pkg_name_check object with a custom print method.
Examples
pkg_name_check("sicily")
#> ╔══════════════════════════════════════════════════════════════════════╗ #> ║ –*– sicily –*– ║ #> ╚══════════════════════════════════════════════════════════════════════╝ #> ┌──────────────────────────────────────────────────────────────────────┐ #> │ v valid name v CRAN v Bioconductor │ #> │ v not a profanity │ #> └──────────────────────────────────────────────────────────────────────┘ #> ┌ Wikipedia ───────────────────────────────────────────────────────────┐ #> │ Sicily Sicily (Italian: Sicilia [siˈtʃiːlja], Sicilian │ #> │ pronunciation: [sɪˈʃiːlja]) is the largest island in the │ #> │ Mediterranean Sea and one of the 20 regions of Italy. The Strait of │ #> │ Messina divides it from the region of Calabria in Southern Italy. │ #> │ It is one of the five Italian autonomous regions and is officially │ #> │ referred to as Regione Siciliana. The region has 5 million │ #> │ … │ #> └──────────────────────────────── https://en.wikipedia.org/wiki/Sicily ┘ #> ┌ Wiktionary ──────────────────────────────────────────────────────────┐ #> │ sicily No English definition found │ #> └──────────────────────────────────────────────────────────────────── ┘ #> ┌──────────────────────────────────────────────────────────────────────┐ #> │ Sentiment: 😐 (0) │ #> └──────────────────────────────────────────────────────────────────────┘
Remove installed packages
Description
Remove installed packages
Usage
pkg_remove(pkg, lib = .libPaths()[[1L]])
Arguments
pkg |
A character vector of packages to remove. |
lib |
library to remove packages from. |
Value
Nothing.
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps_tree(),
pkg_deps(),
pkg_download(),
pkg_install(),
pkg_status(),
pkg_sysreqs()
Search CRAN packages
Description
Search the indexed database of current CRAN packages. It uses the
pkgsearch package. See that package for more details and also
pkgsearch::pkg_search() for pagination, more advanced searching,
etc.
Usage
pkg_search(query, ...)
Arguments
query |
Search query string. |
... |
Arguments passed on to
|
Value
A data frame, that is also a pak_search_result object
with a custom print method. To see the underlying table, you
can use [] to drop the extra classes. See examples below.
Examples
Simple search
pkg_search("survival")
#> #> 1 survival 3.4.0 -- by Terry M Therneau, 4 months ago #> Survival Analysis #> #> 2 survminer 0.4.9 -- by Alboukadel Kassambara, 2 years ago #> Drawing Survival Curves using 'ggplot2' #> #> 3 flexsurv 2.2 -- by Christopher Jackson, 6 months ago #> Flexible Parametric Survival and Multi-State Models #> #> 4 muhaz 1.2.6.4 -- by David Winsemius, 2 years ago #> Hazard Function Estimation in Survival Analysis #> #> 5 pec 2022.5.4 -- by Thomas A. Gerds, 8 months ago #> Prediction Error Curves for Risk Prediction Models in Survival Analysi #> s #> #> 6 randomForestSRC 3.1.1 -- by Udaya B. Kogalur, 5 months ago #> Fast Unified Random Forests for Survival, Regression, and Classificati #> on (RF-SRC) #> #> 7 relsurv 2.2.8 -- by Damjan Manevski, 4 months ago #> Relative Survival #> #> 8 survRM2 1.0.4 -- by Hajime Uno, 6 months ago #> Comparing Restricted Mean Survival Time #> #> 9 titanic 0.1.0 -- by Paul Hendricks, 7 years ago #> Titanic Passenger Survival Data Set #> #> 10 KMsurv 0.1.5 -- by Jun Yan, 10 years ago #> Data sets from Klein and Moeschberger (1997), Survival Analysis
See the underlying data frame
psro <- pkg_search("ropensci")
psro[]
#> # A data frame: 10 × 15 #> score package version title descr…¹ date maint…² #> <dbl> <chr> <pckg_vrs> <chr> <chr> <dttm> <chr> #> 1 538. webmockr 0.8.2 Stub… "Stubb… 2022-08-28 19:20:02 Scott … #> 2 520. RSelenium 1.7.9 R Bi… "Provi… 2022-09-02 07:10:11 Ju Yeo… #> 3 416. tracerer 2.2.2 Trac… "'BEAS… 2021-05-30 08:40:03 Richèl… #> 4 376. rfisheries 0.2 'Pro… "A pro… 2016-02-19 08:50:03 Karthi… #> 5 367. mcbette 1.15 Mode… "'BEAS… 2022-08-27 12:30:02 Richèl… #> 6 359. taxize 0.9.100 Taxo… "Inter… 2022-04-22 07:30:02 Zachar… #> 7 350. beastier 2.4.11 Call… "'BEAS… 2022-08-11 13:40:04 Richèl… #> 8 347. spocc 1.2.0 Inte… "A pro… 2021-01-05 19:50:03 Scott … #> 9 316. chromer 0.3 Inte… "A pro… 2022-10-27 22:45:36 Karl W… #> 10 315. visdat 0.5.3 Prel… "Creat… 2019-02-15 14:30:03 Nichol… #> # … with 8 more variables: maintainer_email <chr>, revdeps <int>, #> # downloads_last_month <int>, license <chr>, url <chr>, #> # bugreports <chr>, package_data <I<list>>, ago <chr>, and #> # abbreviated variable names ¹description, ²maintainer_name
Display installed locations of a package
Description
Display installed locations of a package
Usage
pkg_status(pkg, lib = .libPaths())
Arguments
pkg |
Name of one or more installed packages to display status for. |
lib |
One or more library paths to lookup packages status in. By default all libraries are used. |
Value
Data frame with data about installations of pkg.
include_docs("pkgdepends", "docs/lib-status-return.rds")
Examples
pkg_status("MASS")
#> # A data frame: 2 × 39 #> library package title version depends repos…¹ license needs…² built #> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> #> 1 /Users/ga… MASS Supp… 7.3-58… R (>= … CRAN GPL-2 … TRUE R 4.… #> 2 /Library/… MASS Supp… 7.3-58… R (>= … CRAN GPL-2 … TRUE R 4.… #> # … with 30 more variables: remotetype <chr>, remotepkgref <chr>, #> # remoteref <chr>, remoterepos <chr>, remotepkgplatform <chr>, #> # remotesha <chr>, imports <chr>, suggests <chr>, linkingto <chr>, #> # remotes <chr>, remotehost <chr>, remoterepo <chr>, #> # remoteusername <chr>, enhances <chr>, biocviews <chr>, #> # remoteurl <chr>, remotesubdir <chr>, priority <chr>, #> # remoteetag <chr>, remotepackaged <chr>, md5sum <chr>, …
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps_tree(),
pkg_deps(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_sysreqs()
Calculate system requirements of one of more packages
Description
Calculate system requirements of one of more packages
Usage
pkg_sysreqs(pkg, upgrade = TRUE, dependencies = NA, sysreqs_platform = NULL)
Arguments
pkg |
Package names or package references. E.g.
See "Package sources" for more details. |
upgrade |
When When |
dependencies |
What kinds of dependencies to install. Most commonly one of the following values:
|
sysreqs_platform |
System requirements platform. If Set this option if to one of |
Value
List with entries:
-
os: character string. Operating system. -
distribution: character string. Linux distribution,NAif the OS is not Linux. -
version: character string. Distribution version,NAis the OS is not Linux. -
pre_install: character vector. Commands to run before the installation of system packages. -
install_scripts: character vector. Commands to run to install the system packages. -
post_install: character vector. Commands to run after the installation of system packages. -
packages: data frame. Information about the system packages that are needed. It has columns:-
sysreq: string, cross-platform name of the system requirement. -
packages: list column of character vectors. The names of the R packages that have this system requirement. -
pre_install: list column of character vectors. Commands run before the package installation for this system requirement. -
system_packages: list column of character vectors. Names of system packages to install. -
post_install: list column of character vectors. Commands run after the package installation for this system requirement.
-
See Also
Other package functions:
lib_status(),
pak(),
pkg_deps(),
pkg_deps_tree(),
pkg_download(),
pkg_install(),
pkg_remove(),
pkg_status()
Other system requirements functions:
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Does PPM build binary packages for the current platform?
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/.
Other PPM functions:
ppm_platforms(),
ppm_r_versions(),
ppm_repo_url(),
ppm_snapshots()
Examples
system_r_platform()
ppm_has_binaries()
List all platforms supported by Posit Package Manager (PPM)
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,windowsormacOScurrently, -
binary_url: the URL segment of the binary repository URL of this platform, seeppm_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/.
Other PPM functions:
ppm_has_binaries(),
ppm_r_versions(),
ppm_repo_url(),
ppm_snapshots()
Examples
ppm_platforms()
List all R versions supported by Posit Package Manager (PPM)
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/.
Other PPM functions:
ppm_has_binaries(),
ppm_platforms(),
ppm_repo_url(),
ppm_snapshots()
Examples
ppm_r_versions()
Returns the current Posit Package Manager (PPM) repository URL
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().
In the environment variables are not set, then ppm_repo_url() will
try 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 pak
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/.
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()
List all available Posit Package Manager (PPM) snapshots
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, aPOSIXctvector, -
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/.
Other PPM functions:
ppm_has_binaries(),
ppm_platforms(),
ppm_r_versions(),
ppm_repo_url()
Examples
ppm_snapshots()
Add a new CRAN-like repository
Description
Add a new repository to the list of repositories that pak uses to look for packages.
Usage
repo_add(..., .list = NULL, username = NULL)
repo_resolve(spec, username = NULL)
Arguments
... |
Repository specifications, possibly named character vectors. See details below. |
.list |
List or character vector of repository specifications.
This argument is easier to use programmatically than |
username |
User name to set, for authenticated repositories, see
|
spec |
Repository specification, a possibly named character scalar. |
Details
repo_add() adds new repositories. It resolves the specified
repositories using repo_resolve() and then modifies the repos
global option.
repo_add() only has an effect in the current R session. If you
want to keep your configuration between R sessions, then set the
repos option to the desired value in your user or project .Rprofile
file.
Value
repo_resolve() returns a named character scalar, the URL
of the repository.
Repository specifications
The format of a repository specification is a named or unnamed
character scalar. If the name is missing, pak 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 asPPM@.The MRAN service is now retired, see
https://techcommunity.microsoft.com/blog/azuresqlblog/microsoft-r-application-network-retirement/3707161for 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.
Examples
repo_add(PPMdplyr100 = "PPM@dplyr-1.0.0") repo_get()
#> # A data frame: 7 × 5 #> name url type r_version bioc_version #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cloud.r-project.org cran * NA #> 2 PPMdplyr100 https://packagemanager.pos… cran… * NA #> 3 BioCsoft https://bioconductor.org/p… bioc 4.4.2 3.20 #> 4 BioCann https://bioconductor.org/p… bioc 4.4.2 3.20 #> 5 BioCexp https://bioconductor.org/p… bioc 4.4.2 3.20 #> 6 BioCworkflows https://bioconductor.org/p… bioc 4.4.2 3.20 #> 7 BioCbooks https://bioconductor.org/p… bioc 4.4.2 3.20
repo_resolve("PPM@2020-01-21")
#> CRAN #> "https://packagemanager.posit.co/cran/2020-01-21"
repo_resolve("PPM@dplyr-1.0.0")
#> CRAN #> "https://packagemanager.posit.co/cran/2020-05-30"
repo_resolve("PPM@R-4.0.0")
#> CRAN #> "https://packagemanager.posit.co/cran/2020-04-25"
See Also
Other repository functions:
repo_get(),
repo_status()
Authenticated repositories
Description
pak supports HTTP basic authentication when interacting with CRAN-like repositories. To use authentication, include a username in the repo URL:
https://<username>@<repo-host>/<repo-path>
Usage
repo_auth(
r_version = getRversion(),
bioc = NULL,
cran_mirror = NULL,
check_credentials = TRUE
)
Arguments
r_version |
R version to use to determine the correct Bioconductor
version, if |
bioc |
Whether to automatically add the Bioconductor repositories to the result. |
cran_mirror |
CRAN mirror to use. Leave it at |
check_credentials |
Whether to check that credentials are available for authenticated repositories. |
Details
pak will look up the password for this url and username from the
the user's .netrc file and from the system credential store using
the keyring package.
'.netrc“ files
First pak searches in the .netrc file. If the NETRC environment
variable is set, pak uses its value to determine the location of the
netrc file.
Otherwise pak looks for the netrc file in current user's home
directory, at ~/.netrc. On Windows it also looks for ~/_netrc if the
file starting with a dot does not exist.
If you create a netrc file, make sure that is only readable by you.
E.g. on Unix run
chmod 600 ~/.netrc
netrc files are simple text files that can store passwords for multiple
hosts. They may contain three types of tokens:
machine <hostname>
A host name, without the protocol. Subsequent login and password
tokens belong to this host, until another machine token is found, or
the end of file.
login <username>
User name. It must be preceded by a machine token.
password <password>
Password. It must be preceded by a machine and a login token.
Whitespace is ignored in netrc files. You may include multiple tokens
on the same line, or have one token per line. Here is an example:
machine myhost.mydomain.com login myuser password secret machine myhost2.mydomain.com login myuser password secret login anotheruser password stillsecret
If you need to include whitespace in a password, put the password in double quotes.
The system credential store
pak currently supports the following keyring backends:
Windows credential store,
macOS Keychain,
Linux Secret Service via libsecret, if built with libsecret support,
environment variables.
For the URL above it tries the following keyring keys, in this order:
https://<username>@repo-host/<repo-path> https://repo-host/<repo-path> https://<username>@repo-host https://repo-host
To add an authenticated repository use repo_add() with the username
argument. Alternatively, you can set the repos option directly using
base::options() and including the username in the repository URL.
repo_auth() lists authentication information for all configured
repositories.
Value
Data frame with columns:
all columns from the output of
repo_get(),-
auth_domains: authentication domains. pak tries to find the credentials for these domains, until the search is successful or all domains fail. -
auth_domain: if the credential lookup is successful, then this is the authentication domain that was used to get the credentials. -
auth_source: where the credentials were found. E.g.keyring:<backend>means it was in the default macos keyring. -
auth_error: for failed credential searches this is the description of why the search failed. E.g. maybe the keyring package is not installed, or pak found no credentials for any of the authentication domains.
See Also
Other authenticated repositories:
Authenticated repositories,
repo_auth_key_get()
Query or set repository password in the system credential store
Description
Use pak's keyring functions to query or set a repository password in the system credential store.
Usage
repo_auth_key_get(url, username = NULL)
repo_auth_key_set(url, password, username = NULL)
repo_auth_unlock(keyring_password)
Arguments
url |
Repository URL. It may contain a username, in which case
|
username |
User name, if it is not included in |
password |
Password (key) to set. |
keyring_password |
Password to unlock the keyring. |
Details
repo_auth_key_get() retrieves a password from the default keyring. It
errors if it cannot find the credentials for url.
repo_auth_key_set() adds or updates a password in the system
credential store.
repo_auth_unlock() unlocks the default keyring, if it is locked.
You might need this if the keyring is locked. If you are using
ecrypted files to store the keys, then you typically need to call this
function in each session. You typically don't need to do that if you
are using the native Windows, macOS or Linux (Secret Service) backends.
Value
repo_auth_key_get() returns a single string, the repository
password.
See Also
Other authenticated repositories:
Authenticated repositories,
repo_auth()
Query the currently configured CRAN-like repositories
Description
pak uses the repos option, see options(). It also automatically
adds a CRAN mirror if none is set up, and the correct version of the
Bioconductor repositories. See the cran_mirror and bioc arguments.
Usage
repo_get(r_version = getRversion(), bioc = NULL, cran_mirror = NULL)
Arguments
r_version |
R version to use to determine the correct Bioconductor
version, if |
bioc |
Whether to automatically add the Bioconductor repositories to the result. |
cran_mirror |
CRAN mirror to use. Leave it at |
Details
repo_get() returns the table of the currently 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 becranfor CRAN,biocfor a Bioconductor repository, andcranlike: 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 isNAfor others. -
username: user name, for authenticated repositories. -
has_password: whetherrepo_get()could find the password for this repository. Callrepo_auth()for more information if the credential lookup failed.
Examples
repo_get()
#> # A data frame: 6 × 5 #> name url type r_version bioc_version #> * <chr> <chr> <chr> <chr> <chr> #> 1 CRAN https://cloud.r-project.org cran * NA #> 2 BioCsoft https://bioconductor.org/p… bioc 4.4.2 3.20 #> 3 BioCann https://bioconductor.org/p… bioc 4.4.2 3.20 #> 4 BioCexp https://bioconductor.org/p… bioc 4.4.2 3.20 #> 5 BioCworkflows https://bioconductor.org/p… bioc 4.4.2 3.20 #> 6 BioCbooks https://bioconductor.org/p… bioc 4.4.2 3.20
See Also
Other repository functions:
repo_add(),
repo_status()
Show the status of CRAN-like repositories
Description
It checks the status of the configured or supplied repositories.
Usage
repo_status(
platforms = NULL,
r_version = getRversion(),
bioc = NULL,
cran_mirror = NULL
)
repo_ping(
platforms = NULL,
r_version = getRversion(),
bioc = NULL,
cran_mirror = NULL
)
Arguments
platforms |
Platforms to use, default is the current platform,
plus source packages, via the |
r_version |
R version(s) to use, the default is the current
R version, via |
bioc |
Whether to add the Bioconductor repositories. If you
already configured them via |
cran_mirror |
The CRAN mirror to use. Defaults to the
|
Details
repo_ping() is similar to repo_status() but also prints a short
summary of the data, and it returns its result invisibly.
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 inoptions("repos"), or added by pak. It is typicallyCRANfor CRAN, and the current Bioconductor repositories areBioCsoft,BioCann,BioCexp,BioCworkflows. -
url: base URL of the repository. -
bioc_version: Bioconductor version, orNAfor non-Bioconductor repositories. -
username: Included if at least one repository is authenticated.NA_character_for repositories without authentication. Seerepo_auth(). -
has_password:TRUEis the function could retrieve the password for the authenticated repository. It isNAfor repositories without authentication. This column is included only if at least one repository has authentication. Seerepo_auth(). -
platform: platform, possible values aresource,macosandwindowscurrently. -
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 theokcolumn isFALSE, then this columns inNA. -
error: the error object if the HTTP query failed for this repository, platform and R version.
Examples
repo_status()
#> # A data frame: 12 × 10 #> name url type bioc_version platform path r_version ok ping #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <dbl> #> 1 CRAN http… cran NA source src/… 4.4 TRUE 0.246 #> 2 CRAN http… cran NA aarch64… bin/… 4.4 TRUE 0.298 #> 3 BioCso… http… bioc 3.20 source src/… 4.4 TRUE 0.298 #> 4 BioCso… http… bioc 3.20 aarch64… bin/… 4.4 TRUE 0.322 #> 5 BioCann http… bioc 3.20 source src/… 4.4 TRUE 0.530 #> 6 BioCann http… bioc 3.20 aarch64… bin/… 4.4 TRUE 0.643 #> 7 BioCexp http… bioc 3.20 source src/… 4.4 TRUE 0.498 #> 8 BioCexp http… bioc 3.20 aarch64… bin/… 4.4 TRUE 0.707 #> 9 BioCwo… http… bioc 3.20 source src/… 4.4 TRUE 0.569 #> 10 BioCwo… http… bioc 3.20 aarch64… bin/… 4.4 TRUE 0.724 #> 11 BioCbo… http… bioc 3.20 source src/… 4.4 TRUE 0.662 #> 12 BioCbo… http… bioc 3.20 aarch64… bin/… 4.4 TRUE 0.754 #> # i 1 more variable: error <list>
repo_status(
platforms = c("windows", "macos"),
r_version = c("4.0", "4.1")
)
#> # A data frame: 18 × 10 #> name url type bioc_version platform r_version path ok ping #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <dbl> #> 1 CRAN http… cran NA i386+x8… 4.0 bin/… TRUE 0.175 #> 2 CRAN http… cran NA i386+x8… 4.1 bin/… TRUE 0.180 #> 3 CRAN http… cran NA aarch64… 4.1 bin/… FALSE NA #> 4 BioCs… http… bioc 3.12 i386+x8… 4.0 bin/… TRUE 0.539 #> 5 BioCa… http… bioc 3.12 i386+x8… 4.0 bin/… TRUE 0.538 #> 6 BioCe… http… bioc 3.12 i386+x8… 4.0 bin/… TRUE 1.04 #> 7 BioCw… http… bioc 3.12 i386+x8… 4.0 bin/… TRUE 0.809 #> 8 BioCb… http… bioc 3.12 i386+x8… 4.0 bin/… TRUE 0.610 #> 9 BioCs… http… bioc 3.14 i386+x8… 4.1 bin/… TRUE 1.16 #> 10 BioCs… http… bioc 3.14 aarch64… 4.1 bin/… FALSE NA #> 11 BioCa… http… bioc 3.14 i386+x8… 4.1 bin/… TRUE 0.659 #> 12 BioCa… http… bioc 3.14 aarch64… 4.1 bin/… FALSE NA #> 13 BioCe… http… bioc 3.14 i386+x8… 4.1 bin/… TRUE 0.913 #> 14 BioCe… http… bioc 3.14 aarch64… 4.1 bin/… FALSE NA #> 15 BioCw… http… bioc 3.14 i386+x8… 4.1 bin/… TRUE 0.811 #> 16 BioCw… http… bioc 3.14 aarch64… 4.1 bin/… FALSE NA #> 17 BioCb… http… bioc 3.14 i386+x8… 4.1 bin/… TRUE 1.04 #> 18 BioCb… http… bioc 3.14 aarch64… 4.1 bin/… FALSE NA #> # i 1 more variable: error <list>
repo_ping()
#> Repository summary: source aarch64-apple-darwin20 #> CRAN @ cloud.r-project.org v v (63ms ) #> BioCsoft @ bioconductor.org v v (68ms ) #> BioCann @ bioconductor.org v v (153ms) #> BioCexp @ bioconductor.org v v (186ms) #> BioCworkflows @ bioconductor.org v v (112ms) #> BioCbooks @ bioconductor.org v v (193ms)
See Also
Other repository functions:
repo_add(),
repo_get()
Scan R code for dependent packages
Description
Scan all R files of a project or directory for packages used within
them. It parses R code to find library(package), package::func(),
and similar calls that imply package dependencies. See details below.
Usage
scan_deps(path = NULL, root = NULL)
Arguments
path |
Files and/or directories to scan. Defaults to the current
project, detected by finding the first parent directory of the current
working directory, that contains a file or directory called
DESCRIPTION, .git, .Rproj.user, renv.lock, or renv.
(Note that this is different from If |
root |
The root directory of the project. It is used to find the
|
Value
Data frame with columns:
-
path: Path to the file in which the dependencies was found. -
package: Detected package dependency. Typically a package name, but it can also be a package reference, e.g. a package from GitHub. -
type: Dependency type. It is"prod","test"or"dev". See 'Dependency types' below. -
code: The piece of code the dependency was extracted from. -
start_row: Start row of the code the dependency was extracted from. -
start_column: Start column of the code the dependency was extracted from. -
start_byte: Start byte of the code the dependency was extracted from.
Note the data frame may contain the same package multiple times, if it
was detected multiple times, e.g. multiple library() calls load the
same package.
Detected dependencies
scan_deps() detects package dependencies from these R expressions:
-
library(),require(),loadNamespace()andrequireNamespacecalls. -
::and:::operators. Any of the calls in this list in R code from R markdown or quarto
RandRscript(case insensitive) code blocks or inline R code.A dependency on the methods package is inferred from finding
setClass()and/orsetGeneric()calls.-
xfun::pkg_attach()andxfun::pkg_attach2()calls. -
pacman::p_load()calls. -
modules::import()andmodules::module()calls. -
import::from(),import::here()andimport::into()calls. -
box::use()calls. -
targets::tar_option_set(packages = ...)calls. Any of the calls in this list in R code from
glue::glue()strings.A dependency on the svglite package is inferred from
ggplot2::ggsave()calls saving.svgfiles.Dependencies from
parsnip::set_engine()calls, the default engine to package mapping is:-
"glm"-> stats, -
"glmnet"-> glmnet, -
"keras"-> keras, -
"kknn"-> kknn, -
"nnet"-> nnet, -
"rpart"-> rpart, -
"spark"-> sparklyr, -
"stan"-> rstanarm. You can override the default mapping by setting therenv.parsnip.enginesoption to a named list.
-
A dependency on the xml2 package is inferred from using the "Junit" reporter (
JunitReporter) from the testthat package.A dependency on the ragg package is inferred from setting the default knitr device (
devoption) to"ragg_png".A dependency on the hexbin package is inferred from using
ggplot2::geom_hex().A custom symbol name to package name mapping can be defined in the
renv.dependencies.databaseoption. This must be a named list of named lists, where the outer names are package names, the inner names are function or object names, and the values are package names. E.g.options(renv.dependencies.database = list( ggplot2 = list(geom_hex = "hexbin"), testthat = list(JunitReporter = "xml2") ))
Dependency types
scan_deps() classifies package dependencies into three groups, based
on which files they were found:
Production dependencies:
"prod".Test dependencies:
"test".Development dependencies:
"dev".
Examples
scan_deps("myproject")
scan_deps("myproject")[]
Check if installed packages have all their system requirements
Description
sysreqs_check_installed() checks if the system requirements of all
packages (or a subset of packages) are installed.
sysreqs_fix_installed() installs the missing system packages.
Usage
sysreqs_check_installed(packages = NULL, library = .libPaths()[1])
sysreqs_fix_installed(packages = NULL, library = .libPaths()[1])
Arguments
packages |
If not |
library |
Library or libraries to check. |
Details
These functions use the sysreqs_platform configuration option,
see man_config_link("Configuration"). Set this if
pak does not detect your platform correctly.
Value
Data frame with a custom print and format method, and a
pkg_sysreqs_check_result class. Its columns are:
-
system_package: string, name of the required system package. -
installed: logical, whether the system package is correctly installed. -
packages: list column of character vectors. The names of the installed R packages that need this system package. -
pre_install: list column of character vectors. Commands to run before the installation of the the system package. -
post_install: list column of character vectors. Commands to run after the installation of the system package.
The data frame also have two attributes with additional data:
-
sysreqs_records: the raw system requirements records, and -
system_packages: the list of the installed system packages.
sysreqs_fix_packages() returns the same value, but invisibly.
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Examples
# This only works on supported platforms
sysreqs_check_installed()
List contents of the system requirements DB, for a platform
Description
It also tries to update the system dependency database, if it is
outdated. (I.e. older than allowed in the metadata_update_after
man_config_link("configuration option").
Usage
sysreqs_db_list(sysreqs_platform = NULL)
Arguments
sysreqs_platform |
System requirements platform. If |
Value
Data frame with columns:
-
name: cross platform system dependency name in the database. -
patterns: one or more regular expressions to match toSystemRequirementsfields. -
packages: one or more system package names to install. -
pre_install: command(s) to run before installing the packages. -
post_install:: command(s) to run after installing the packages.
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Examples
sysreqs_db_list(sysreqs_platform = "ubuntu-22.04")
Match system requirement descriptions to the database
Description
In the usual workflow pak matches the
SystemRequirements fields of the DESCRIPTION files to the database.
Usage
sysreqs_db_match(specs, sysreqs_platform = NULL)
Arguments
specs |
Character vector of system requirements descriptions. |
sysreqs_platform |
System requirements platform. If |
Details
The sysreqs_db_match() function lets you match any string, and it is
mainly useful for debugging.
Value
Data frame with columns:
-
spec: the inputspecs. -
sysreq: name of the system library or tool. -
packages: system packages, list column of character vectors. Rarely it can be an empty string, e.g. if apre_installscript performs the installation. -
pre_install: list column of character vectors. Shell script(s) to run before the installation. -
post_install: list column of character vectors. Shell script(s) to run after the installation.
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Examples
sysreqs_db_match(
c("Needs libcurl", "Java, libssl"),
sysreqs_platform = "ubuntu-22.04"
)
Update the cached copy of the system requirements database
Description
Update the cached copy of the system requirements database
Usage
sysreqs_db_update()
Details
If the the cached copy is recent, then no update is attempted. See the
metadata_update_after man_config_link("configuration option").
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_is_supported(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Check if a platform has system requirements support
Description
Check if a platform has system requirements support
Usage
sysreqs_is_supported(sysreqs_platform = NULL)
Arguments
sysreqs_platform |
System requirements platform. If |
Value
Logical scalar.
See Also
The sysreqs_platform
man_config_link("configuration option").
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_list_system_packages(),
sysreqs_platforms()
Examples
sysreqs_is_supported()
List installed system packages
Description
List installed system packages
Usage
sysreqs_list_system_packages()
Details
This function uses the sysreqs_platform configuration option,
see man_config_link("Configuration"). Set this if
pak does not detect your platform correctly.
Value
Data frame with columns:
-
status. two or three characters, the notation ofdpkgon Debian based systems."ii"means the package is correctly installed. OnRPMbased systems it is always"ii"currently. -
package: name of the system package. -
version: installed version of the system package. -
capabilities: list column of character vectors, the capabilities provided by the package.
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_platforms()
Examples
sysreqs_list_system_packages()[1:10,]
List platforms with system requirements support
Description
List platforms with system requirements support
Usage
sysreqs_platforms()
Value
Data frame with columns:
-
name: human readable OS name. -
os: OS name, e.g.linux. -
distribution: OS id, e.g.ubuntuorredhat. -
version: distribution version. A star means that all versions are supported, that are also supported by the vendor. -
update_command: command to run to update the system package metadata. -
install_command: command to run to install packages. -
query_command: name of the tool to use to query system package information.
See Also
Other system requirements functions:
pkg_sysreqs(),
sysreqs_check_installed(),
sysreqs_db_list(),
sysreqs_db_match(),
sysreqs_db_update(),
sysreqs_is_supported(),
sysreqs_list_system_packages()
Examples
sysreqs_platforms()
R platforms
Description
R platforms
Usage
system_r_platform()
system_r_platform_data()
Details
system_r_platform() detects the platform of the current R version.
system_r_platform_data() is similar, but returns the raw data instead
of a character scalar.
By default pak works with source packages and binary packages for
the current platform. You can change this, by providing different
platform names in the pkg.platforms option or the
PKG_PLATFORMS environment variable.
This option may contain the following platform names:
-
"source"for source packages, -
"macos"for macOS binaries that are appropriate for the R versions pak 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 toi386+x86_64-w64-mingw32currently. 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.
-
Value
system_r_platform() returns a character scalar.
system_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.
See Also
These function call pkgcache::current_r_platform() and
pkgcache::current_r_platform_data().
Examples
system_r_platform()
system_r_platform_data()