Download and install packages from CRAN-like repositories or from local files.
install.packages(pkgs, lib, repos = getOption("repos"), contriburl = contrib.url(repos, type), method, available = NULL, destdir = NULL, dependencies = NA, type = getOption("pkgType"), configure.args = getOption("configure.args"), configure.vars = getOption("configure.vars"), clean = FALSE, Ncpus = getOption("Ncpus", 1L), verbose = getOption("verbose"), libs_only = FALSE, INSTALL_opts, quiet = FALSE, keep_outputs = FALSE, …)
character vector of the names of packages whose current versions should be downloaded from the repositories.
repos = NULL, a character vector of file paths,
file paths of
.zip files containing binary builds of
file:// URLs are also accepted
and the files will be downloaded and installed from local copies.)
Source directories or file paths or URLs of archives may be
type = "source", but some packages need
suitable tools installed (see the ‘Details’ section).
these file paths can be source directories or archives
or binary package archive files (as created by
R CMD build
file:// URLs are also
accepted and the files will be downloaded and installed from local
copies.) On a CRAN build of R for macOS these can be
files containing binary package archives.
Tilde-expansion will be done on file paths.
If this is missing, a listbox of available packages is presented where possible in an interactive R session.
character vector giving the library directories where to
install the packages. Recycled as needed. If missing, defaults to
the first element of
character vector, the base URL(s) of the repositories
to use, e.g., the URL of a CRAN mirror such as
"https://cloud.r-project.org". For more details on
supported URL schemes see
NULL to install from local files, directories or URLs:
this will be inferred by extension from
pkgs if of length one.
URL(s) of the contrib sections of the repositories. Use this
argument if your repository mirror is incomplete, e.g., because
you burned only the
contrib section on a CD, or only have
binary packages. Overrides argument
type = "both".
download method, see
download.file. Unused if
available is supplied.
a matrix as returned by
listing packages available at the repositories, or
the function makes an internal call to
type = "both".
directory where downloaded packages are stored. If it is
NULL (the default) a subdirectory
downloaded_packages of the session temporary
directory will be used (and the files will be deleted
at the end of the session).
logical indicating whether to also install
uninstalled packages which these packages depend on/link
to/import/suggest (and so on recursively).
Not used if
repos = NULL.
Can also be a character vector, a subset of
c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances").
Only supported if
lib is of length one (or missing),
so it is unambiguous where to install the dependent packages. If
this is not the case it is ignored, with a warning.
c("Depends", "Imports", "LinkingTo").
TRUE means to use
c("Depends", "Imports", "LinkingTo", "Suggests") for
c("Depends", "Imports", "LinkingTo") for added dependencies:
this installs all the packages needed to run
examples, tests and vignettes (if the package author specified them
In all of these,
"LinkingTo" is omitted for binary packages.
character, indicating the type of package to download and
install. Will be
"source" except on Windows and some macOS
builds: see the section on ‘Binary packages’ for those.
(Used only for source installs.) A character vector or a named list.
If a character vector with no names is supplied, the elements are
concatenated into a single string (separated by a space) and used as
the value for the --configure-args flag in the call to
R CMD INSTALL. If the character vector has names these
are assumed to identify values for --configure-args for
individual packages. This allows one to specify settings for an
entire collection of packages which will be used if any of those
packages are to be installed. (These settings can therefore be
re-used and act as default settings.)
A named list can be used also to the same effect, and that allows multi-element character strings for each package which are concatenated to a single string to be used as the value for --configure-args.
(Used only for source installs.) Analogous to
for flag --configure-vars, which is used to set environment
variables for the
a logical value indicating whether to add the
--clean flag to the call to
R CMD INSTALL.
This is sometimes used to perform additional operations at the end
of the package installation in addition to removing intermediate files.
the number of parallel processes to use for a parallel
install of more than one source package. Values greater than one
are supported if the
make command specified by
Sys.getenv("MAKE", "make") accepts argument
-k -j Ncpus.
a logical indicating if some “progress report” should be given.
a logical value: should the --libs-only option be used to
install only additional sub-architectures for source installs? (See also
INSTALL_opts.) This can also be used on Windows to install
just the DLL(s) from a binary package, e.g.to add 64-bit
DLLs to a 32-bit install.
an optional character vector of additional option(s) to be passed to
R CMD INSTALL for a source package install. E.g.,
c("--html", "--no-multiarch", "--no-test-load").
Can also be a named list of character vectors to be used as additional options, with names the respective package names.
logical: if true, reduce the amount of output.
a logical: if true, keep the outputs from installing source packages
in the current working directory, with the names of the output files
the package names with
.out appended. Alternatively, a
character string giving the directory in which to save the outputs.
Ignored when installing from local files.
Arguments to be passed to
download.file or to the
functions for binary installs on macOS and Windows (which accept
"lock": see the section on ‘Locking’).
This section applies only to platforms where binary packages are available: Windows and CRAN builds for macOS.
R packages are primarily distributed as source packages, but binary packages (a packaging up of the installed package) are also supported, and the type most commonly used on Windows and by the CRAN builds for macOS. This function can install either type, either by downloading a file from a repository or from a local file.
Possible values of
type are (currently)
"win.binary": the appropriate binary type where supported can
also be selected as
For a binary install from a repository, the function checks for the availability of a source package on the same repository, and reports if the source package has a later version, or is available but no binary version is. This check can be suppressed by using
options(install.packages.check.source = "no")
and should be if there is a partial repository containing only binary files.
An alternative (and the current default) is
"both" which means
‘use binary if available and current, otherwise try
source’. The action if there are source packages which are preferred
but may contain code which needs to be compiled is controlled by
type = "both" will be silently changed to
available is specified.
Using packages with
type = "source" always works provided the
package contains no C/C++/Fortran code that needs compilation.
you will need to have installed the Rtools
collection as described in the ‘R for Windows FAQ’ and
you must have the
PATH environment variable set up as required
For a 32/64-bit installation of R on Windows, a small minority of
packages with compiled code need either
INSTALL_opts = "--merge-multiarch" for a
source installation. (It is safe to always set the latter when
installing from a repository or tarballs, although it will be a little
When installing a binary package,
install.packages will abort
the install if it detects that the package is already installed and is
currently in use. In some circumstances (e.g., multiple instances of
R running at the same time and sharing a library) it will not detect a
problem, but the installation may fail as Windows locks files in use.
when the package contains C/C++/Fortran code that needs compilation, on macOS you need to have installed the ‘Command-line tools for Xcode’ (see the ‘R Installation and Administration Manual’) and if needed by the package a Fortran compiler, and have them in your path.
There are various options for locking: these differ between source and binary installs.
By default for a source install, the library directory is
‘locked’ by creating a directory
00LOCK within it. This
has two purposes: it prevents any other process installing into that
library concurrently, and is used to store any previous version of the
package to restore on error. A finer-grained locking is provided by
the option --pkglock which creates a separate lock for each
package: this allows enough freedom for parallel
installation. Per-package locking is the default when installing a
single package, and for multiple packages when
Ncpus > 1L.
Finally locking (and restoration on error) can be suppressed by
For a macOS binary install, no locking is done by default. Setting
TRUE (it defaults to the value of
getOption("install.lock", FALSE)) will use per-directory
locking as described for source installs. For Windows binary install,
per-directory locking is used by default (
lock defaults to the
getOption("install.lock", TRUE)). If the value is
"pkglock" per-package locking will be used.
If package locking is used on Windows with
libs_only = TRUE and
the installation fails, the package will be restored to its previous
Note that it is possible for the package installation to fail so badly
that the lock directory is not removed: this inhibits any further
installs to the library directory (or for
--pkglock, of the
package) until the lock directory is removed manually.
Parallel installs are attempted if
pkgs has length greater than
Ncpus > 1. It makes use of a parallel
make specified (default
make) when R was
built must be capable of supporting
make -j n: GNU make,
pmake do, but Solaris
make do not: if necessary environment variable
MAKE can be set for the current session to select a suitable
install.packages needs to be able to compute all the
available, including if one
pkgs depends indirectly on another. This means that
if for example you are installing CRAN packages which depend
on Bioconductor packages which in turn depend on CRAN
available needs to cover both CRAN and
A limit on the elapsed time for each call to
R CMD INSTALL
(so for source installs) can be set via environment variable
_R_INSTALL_PACKAGES_ELAPSED_TIMEOUT_: in seconds (or in minutes
or hours with optional suffix m or h, suffix s
being allowed for the default seconds) with
0 meaning no limit.
For non-parallel installs this is implemented via the
timeout argument of
system2: for parallel
installs via the OS's
timeout command. (The one
tested is from GNU coreutils, commonly available on Linux but
not other Unix-alikes. If no such command is available the timeout
request is ignored, with a warning.) For parallel installs a
Error 124 message from
make indicates that timeout
Timeouts during installation might leave lock directories behind and not restore previous versions.
This is the main function to install packages. It takes a vector of
names and a destination library, downloads the packages from the
repositories and installs them. (If the library is omitted it
defaults to the first directory in
.libPaths(), with a message
if there is more than one.) If
lib is omitted or is of length
one and is not a (group) writable directory, in interactive use the
code offers to create a personal library tree (the first element of
Sys.getenv("R_LIBS_USER")) and install there.
Detection of a writable directory is problematic on Windows: see the ‘Note’ section.
For installs from a repository an attempt is made to install the
packages in an order that respects their dependencies. This does
assume that all the entries in
lib are on the default library
path for installs (set by environment variable
You are advised to run
install.packages to ensure that any already installed
dependencies have their latest versions.
download.file for how to handle proxies and
other options to monitor file transfers.
untar for manually unpacking source package tarballs.
The ‘R Installation and Administration’ manual for how to set up a repository.