rversions 1.1.0 is on CRAN!
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Version 1.1.0 of the rversions
package has been released on CRAN! rversions
queries the main R SVN repository to find the versions r-release and r-oldrel refer to, and also all previous R versions and their release dates.
Get rversions
’s latest version from
a safe CRAN mirror near
you:
install.packages("rversions")
This release, compared to rversions
1.0.3, brings
✨ caching ✨ of the R versions within each R session (less useless queries!) thanks to a contribution by Rich FitzJohn;
✨ version nicknames ✨ information to the output of
rversions
functions;a documentation website built with
pkgdown
;and a new home for
rversions
’ source from METACRAN to R-hub! ????
That’s it, but since it’s the first time we blog about rversions
, we’ll use the release as an opportunity to introduce it with all due respect! How does rversions
work and what is it useful for?
Where does rversions
get its information from?
As you might have guessed, R is developed under version control. The R Core team uses SVN, i.e. Apache Subversion. The versions rversions
outputs are derived from SVN tags in the main R SVN repository. In SVN lingo, “tagging refers to labeling the repository at a certain point in time so that it can be easily found in the future.” so it might remind you of git tags (or of GitHub releases). In more details,
head(rversions::r_versions()) ## version date nickname ## 1 0.60 1997-12-04T08:47:58.000000Z <NA> ## 2 0.61 1997-12-21T13:09:22.000000Z <NA> ## 3 0.61.1 1998-01-10T00:31:55.000000Z <NA> ## 4 0.61.2 1998-03-14T19:25:55.000000Z <NA> ## 5 0.61.3 1998-05-02T07:58:17.000000Z <NA> ## 6 0.62 1998-06-14T12:56:20.000000Z <NA>
- r-release is the latest SVN tag
rversions::r_release() ## version date nickname ## 112 3.5.3 2019-03-11T08:04:49.379300Z Great Truth
- r-oldrel is the latest of the previous minor version
rversions::r_oldrel() ## version date nickname ## 108 3.4.4 2018-03-15T08:04:27.234564Z Someone to Lean On
- r-release-tarball is the latest SVN tag that has a corresponding tar.gz to download
rversions::r_release_tarball() ## version date ## 112 3.5.3 2019-03-11T08:04:49.379300Z ## URL nickname ## 112 https://cran.r-project.org/src/base/R-3/R-3.5.3.tar.gz Great Truth
- Windows, macOS are the same: latest SVN tag that has a file to download
rversions::r_release_win() ## version date ## 112 3.5.3 2019-03-11T08:04:49.379300Z ## URL ## 112 https://cran.r-project.org/bin/windows/base/R-3.5.3-win.exe ## nickname ## 112 Great Truth rversions::r_release_macos() ## version date ## 112 3.5.3 2019-03-11T08:04:49.379300Z ## URL nickname ## 112 https://cran.r-project.org/bin/macosx/R-3.5.3.pkg Great Truth
Version nicknames are extracted from specific files from R 2.15.1, e.g. https://svn.r-project.org/R/tags/R-2-15-1/VERSION-NICK. Before that there were only 3 version nicknames, which we got from Lucy D’Agostino McGowan’s excellent blog post about R release names, where you can also read about their meaning.
Where is rversions
used?
rversions
is used in R packages but also public services for R package developers, including R-hub of course!
In R packages
rversions
is used indevtools
, indr_devtools()
to compare the installed R version to the current R release version.provisionr
importsrversions
and uses it incheck_r_version()
, a function that checks and coerces something into an R version.
In other tools
In the tools mentioned below, rversions
is used via its very own web service.
r-appveyor service uses
rversions
to determine what versions r-release and r-oldrel are.R-hub’s Windows install script uses it as well, to decide what versions of R to install.
Can we also play with rversions
data?
At this point, you have no doubt rversions
is useful, but what about we use it to get a glimpse at R’s release schedule over time?
library("ggplot2") versions <- rversions::r_versions() versions <- dplyr::mutate(versions, date = anytime::anytime(date)) versions <- tidyr::separate(versions, version, into = c("major", "minor", "patch")) ## Warning: Expected 3 pieces. Missing pieces filled with `NA` in 13 rows [1, ## 2, 6, 11, 15, 18, 20, 22, 23, 25, 27, 31, 33]. versions <- dplyr::mutate(versions, patch = ifelse(is.na(patch), 0, patch)) versions <- dplyr::mutate(versions, release = dplyr::case_when( major != dplyr::lag(major) ~ "major", minor != dplyr::lag(minor) ~ "minor", TRUE ~ "patch" )) ggplot(versions) + geom_segment(aes(x = date, xend = date, col = release), y = 0, yend = 1) + viridis::scale_colour_viridis(discrete = TRUE) + theme_minimal() + hrbrthemes::theme_ipsum(base_size = 16, axis_title_size = 16) + xlab("Time") + theme( axis.text.y = element_blank(), axis.ticks.y = element_blank(), axis.title.y = element_blank(), legend.position = "bottom") + ggtitle("R releases over time", subtitle = "Data obtained via the R-hub rversions R package")
With the R version being x.y.z, we define a major release as a change in x, a minor release as a change in y and a patch release as a change in z. The figure above shows that the frequency of minor releases decreased in 2013, from twice to once a year. The frequency of patch releases seems irregular, as is the frequency of major releases: not sure when we should expect R 4.0.0!
Conclusion
The best place to get to know rversions
is its brand-new documentation website built with pkgdown
, and the best place to provide feedback or contribute is its GitHub repo. Thanks to all folks who chimed in in the issue tracker and pull request tab!
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