Often, R packages will have other R packages as dependencies. For
this, one must declare their R package dependencies within the package
DESCRIPTION
file. If you want to prepare your environment
for package development, you can use:
renv::install()
to install the packages as declared in the package’s
DESCRIPTION
file. This action is roughly analogous to
remotes::install_deps()
.
If you’re developing a package that you intend to release to CRAN, then you likely want to build and test your package against the latest versions of your dependencies as available on CRAN. For this, you should consider using:
renv::update()
to ensure your package dependencies are up-to-date, as appropriate.
Normally, a package under development should be tested against the latest-available versions of its dependencies on CRAN. However, in some cases, you may need to ensure your package is compatible with other packages also currently under development.
In these cases, the renv project library can be useful – you can install the development version(s) of your dependencies into the project library, without worrying about clobbering any packages already installed in your system library.
In these cases, you can declare your development dependencies using
the Remotes
field of the DESCRIPTION
file;
e.g.
Remotes:
r-lib/ggplot2
and renv::install()
will parse that remotes declaration
and retrieve the requested package. See the remotes vignette, Dependency
resolution for R package development, for more details.
For package projects using renv, a library path outside of the project directory will be used instead. As an example, on macOS, this might look like:
> .libPaths()
[1] "/Users/kevin/Library/Caches/org.R-project.R/R/renv/library/example-552f6e80/R-4.3/aarch64-apple-darwin20"
[2] "/Users/kevin/Library/Caches/org.R-project.R/R/renv/sandbox/R-4.3/aarch64-apple-darwin20/ac5c2659"
This is done to avoid issues with R CMD build
, which can
become very slow if your project contains a large number of files – as
can happen if the project library is located in
renv/library
(the typical location). Note that even though
the library is located outside of the project, the library path
generated will still be unique to that project, and so the project is
still effectively isolated in the same way as other renv projects
normally are.
If you want to customize the location where renv
places
project libraries in this scenario, you can use the
RENV_PATHS_LIBRARY_ROOT
environment variable. For
example:
RENV_PATHS_LIBRARY_ROOT = ~/.renv/library
If you’d still prefer to keep your project library within the project directory, you can set:
RENV_PATHS_LIBRARY = renv/library
within an appropriate .Renviron
start-up profile – but
please be aware of the caveats to doing this, as the performance of
R CMD build
will be affected.
While developing your package, you may want to use a continuous integration service (such as Travis CI) to build and test your package remotely. You can use renv to help facilitate this testing – see the Continuous Integration vignette for more information. In particular, clever use of the renv cache can help save time that might normally be spent on package installation. See https://github.com/rstudio/renv/blob/main/.github/workflows/R-CMD-check.yaml for an example of how renv uses itself for package management in its own CI tests.
Note that packages submitted to CRAN should be designed to work with
the other R packages currently available on CRAN. For that reason, when
preparing your package for submission, you’ll need to ensure your source
package tarball does not include any renv
infrastructure.
renv
makes this easy by automatically including
^renv$
^renv\.lock$
in your package’s .Rbuildignore
file. This instructs
R CMD build
to not include these files and folders in the
generated package tarball. Through this, even if renv
is
used during package development, it’s still easy to build and publish
your package to CRAN as you would when developing packages without
renv
.