I am involved in a Posit Team deployment, and one of the things that we are looking into is default R packages that should be made available to all users. We are looking to do this because we would like to avoid people installing, for example tidyverse, in their own local libraries in order to save on space and to make sure everyone is on the same version, at least for the packages that are considered to be a preferred default option for working with data in R.

In order to do this we wanted to collect all the packages that are currently used, their versions, source repository and similar information. That way we can see if anything else should be installed for all users, in addition to the best guess that we should have tidyverse, tidymodels, and shiny.

In order to do this we first have to get the list of installed packages, which is fairly simple to do:

installed_packages <- installed.packages()

Then, utils::packageDescription can be used to get the packagesdescriptions. For example for getting the package description fordplyr` we can run:

dplyr_pkg_desc <- utils::packageDescription('dplyr')

The result is a list, and it can be subsetted to see details, for example:

> dplyr_pkg_desc[1]
$Type
[1] "Package"
> dplyr_pkg_desc[2]
$Package
[1] "dplyr"
> dplyr_pkg_desc[3]
$Title
[1] "A Grammar of Data Manipulation"
> dplyr_pkg_desc[4]
$Version
[1] "1.1.4"

At this point, I am thinking that all these description files have the same structure. Therefore, if I want to get all packages’ version I need to lapply to get the fourth element and that’s that. It turns out this is not entirely true. Not all packages have the same structure of the description. See tydir:

> tidyr_pkg_desc[1]
$Package
[1] "tidyr"
> tidyr_pkg_desc[2]
$Title
[1] "Tidy Messy Data"
> tidyr_pkg_desc[3]
$Version
[1] "1.3.1"
> tidyr_pkg_desc[4]
$`Authors@R`
[1] "c(\n person(\"Hadley\", \"Wickham\", , \"[email protected]\", role = c(\"aut\", \"cre\")),\n person(\"Davis\", \"Vaughan\", , \"[email protected]\", role = \"aut\"),\n person(\"Maximilian\", \"Girlich\", role = \"aut\"),\n person(\"Kevin\", \"Ushey\", , \"[email protected]\", role = \"ctb\"),\n person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"))\n )"

Number four is the authors, and version is three. And these are two packages that are ultimately from the same author. Look at data.table:

> data.table_pkg_desc[1]
$Package
[1] "data.table"
> data.table_pkg_desc[2]
$Version
[1] "1.15.4"
> data.table_pkg_desc[3]
$Title
[1] "Extension of `data.frame`"
> data.table_pkg_desc[4]
$Depends
[1] "R (>= 3.1.0)"

Now, of course, subsetting works with using the name, instead of the position:

> dplyr_pkg_desc[["Version"]]
[1] "1.1.4"
> tidyr_pkg_desc[["Version"]]
[1] "1.3.1"
> data.table_pkg_desc[["Version"]]
[1] "1.15.4"

However, to be honest, it rarely comes to my mind to subset lists like this.

package_names <- installed.packages()[, 1]
all_packages_data <- lapply(package_names, utils::packageDescription)
version_number <-
lapply(1:length(package_names), function (x) {
all_packages_data[[x]][["Version"]]
})

The above is possible, and then to cbind all needed fields in a data.frame.

However, looking at the packageDescription documentation, it seems the best way is to use additional arguments the function. This is neat:

package_data <- lapply(
package_names,
utils::packageDescription,
fields = c("Package", "Version", "Built", "Repository")
)

And then there is another surprise. The results are with class packageDescription which makes getting to a data.frame, or tibble in this case, a bit complicated:

package_data <- purrr::map_df(
package_names,
utils::packageDescription,
fields = c("Package", "Version", "Built", "Repository")
)
Error in `as_tibble()`:
! All columns in a tibble must be vectors.
✖ Column `askpass` is a `packageDescription` object.

The full solution involves a step of changing the class of the object using as, and then reassigning the names of each element, because the previous step removes them:

package_data <- lapply(
package_names,
utils::packageDescription,
fields = c("Package", "Version", "Built", "Repository")
) |>
lapply(as, Class = "list") |>
lapply(setNames, c("Package", "Version", "Built", "Repository")) |>
dplyr::bind_rows()