Rcpp 1.0.13 on CRAN: Some Updates
The Rcpp Core Team is once again pleased to announce a new release
(now at 1.0.13) of the Rcpp package.
It arrived on CRAN earlier
today, and has since been uploaded to Debian. Windows and macOS builds
should appear at CRAN in the next few days, as will builds in different
Linux distribution–and of course r2u should catch up
tomorrow too. The release was uploaded last week, but not only does Rcpp always gets flagged because of the
grandfathered .Call(symbol) but CRAN also found two packages
‘regressing’ which then required them to take five days to get back to
us. One issue was known; another
did not reproduce under our tests against over 2800 reverse dependencies
leading to the eventual release today. Yay. Checks are good and
appreciated, and it does take time by humans to review them.
This release continues with the six-months January-July cycle started with release 1.0.5 in July 2020. As a reminder, we do of course make interim snapshot ‘dev’ or ‘rc’ releases available via the Rcpp drat repo as well as the r-universe page and repo and strongly encourage their use and testing—I run my systems with these versions which tend to work just as well, and are also fully tested against all reverse-dependencies.
Rcpp has long established itself as the most popular way of enhancing R with C or C++ code. Right now, 2867 packages on CRAN depend on Rcpp for making analytical code go faster and further, along with 256 in BioConductor. On CRAN, 13.6% of all packages depend (directly) on Rcpp, and 59.9% of all compiled packages do. From the cloud mirror of CRAN (which is but a subset of all CRAN downloads), Rcpp has been downloaded 86.3 million times. The two published papers (also included in the package as preprint vignettes) have, respectively, 1848 (JSS, 2011) and 324 (TAS, 2018) citations, while the the book (Springer useR!, 2013) has another 641.
This release is incremental as usual, generally preserving existing capabilities faithfully while smoothing our corners and / or extending slightly, sometimes in response to changing and tightened demands from CRAN or R standards. The move towards a more standardized approach for the C API of R leads to a few changes; Kevin did most of the PRs for this. Andrew Johnsom also provided a very nice PR to update internals taking advantage of variadic templates.
The full list below details all changes, their respective PRs and, if applicable, issue tickets. Big thanks from all of us to all contributors!
Changes in Rcpp release version 1.0.13 (2024-07-11)
Changes in Rcpp API:
Set R_NO_REMAP if not already defined (Dirk in #1296)
Add variadic templates to be used instead of generated code (Andrew Johnson in #1303)
Count variables were switches to
size_tto avoid warnings about conversion-narrowing (Dirk in #1307)Rcpp now avoids the usage of the (non-API) DATAPTR function when accessing the contents of Rcpp Vector objects where possible. (Kevin in #1310)
Rcpp now emits an R warning on out-of-bounds Vector accesses. This may become an error in a future Rcpp release. (Kevin in #1310)
Switch
VECTOR_PTRandSTRING_PTRto new API-compliantROvariants (Kevin in #1317 fixing #1316)Changes in Rcpp Deployment:
- Small updates to the CI test containers have been made (#1304)
Thanks to my CRANberries, you can also look at a diff to the previous release Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page. Bugs reports are welcome at the GitHub issue tracker as well (where one can also search among open or closed issues).
If you like this or other open-source work I do, you can sponsor me at GitHub.
This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.
