It is with a mix of pride and joy, but also some genuine astonishment and amazement, that we can share that the counter of reverse dependencies at CRAN for our RcppArmadillo package for R just crossed 1000 packages :
Conrad actually posted this a few weeks ago, by my count we were then still a few packages shy. In any event, having crossed this marker this summer, either then or now, and after more than a dozen years of working on the package is a really nice moment. Google Scholar counts nearly 500 citations for our CSDA paper (also this vignette), and that ratio of nearly a citation for every two packages used is certainly impressive. We have had the pleasure of working with so many other researchers and scientists using RcppArmadillo. Its combination of performance (C++, after all, and heavily tuned) and ease-of-use (inspired by ‘another popular flavour for matrix computing’ that is however mostly interpreted) makes for a powerful package, and we are delighted to see it used so widely.
Working on this with Conrad has been excellent. The (upstream) package (now at this GitLab repo) has received numerous releases at a rate that is in fact so high that we now ‘slow it down’ to not exceed a monthly cadence of uploads to CRAN. But the package should always be in release condition at its GitHub repo, and is frequently also installable in ‘rc’ versions via the Rcpp drat repo.
So with that, a big Thank You! to Conrad, to Romain for all the early work laying the package foundations, and to all the users of (Rcpp)Armadillo for helping us along with testing, suggestions, extensions, and bug reports. Keep’em coming!
If you like this or other open-source work I do, you can now sponsor me at GitHub.
 The code snippet shows that we remove some possible duplicates in the count (mostly for the total of packages). This is a correction we use across packages for consistency. It does not have an effect for RcppArmadillo.