Data Science. TileDB. Open Source. Quant Research. R. C++. Debian. Linux. Adjunct Clinical Professor, University of Illinois. Lots of coffee. And some running.
Yeppers. I usually google something like 'meme generator' along with some terms of the meme in question. Earlier 'meme generator one million', here 'meme generator drake'.
Hm, my "cost", if any, is on the "production". The "distribution" happens via a VM kindly hosted by Liberal Arts & Sciences tech services thanks to @IllinoisStat -- and the local benchmark always was a busy local CTAN mirror. I asked CRAN to consider mirroring but ... 🦗so far.
#r2u is breaking all the records today as two European data centers appear to do *a lot* of batch testing or building. It is midafternoon and we just broke *one million packages* for today which is orders of magnitude higher than usual.
#r2u: Fast. Easy. Reliable.
Got daughter two to do this via quarto in rstudio, using a standard templates for a personal site. Easy peasy. It is now hosted on github via github pages using our custom domain (which I've had for a long time). Hugo templates are good too. Whatever floats your boat!
You can follow the R sources directly which will provide the usual solid and tested (if terse) guides. But usually life is too short and I just rely on (Rcpp)Armadillo doing the BLAS/LAPACK interfacing for me.
This first part of "Zero Gravity" was excellent. Strongly recommended. About Wayne. The music. His music. The bands. The times.
And happy (posthumous) birthday to Wayne Shorter, born ninety years ago today, and gone too sone earlier this year.
youtube.com/watch?app=deskto…
I got kiddo two to do her website in it (landing + research pages, pdf cv) and if she can do it (and I taught her sufficient git to do) so can you. Using github pages to serve, we used a custom eponomymous domain with it too as I own the domain. So no fear, go ahead in RStudio.
Evergreen tweet: when you use `r2u` together with a stateful `apt` client like `wajig`, then the `wajig new` command can tell you about new #rstats package on CRAN (when they are new in #r2u about a day later).
#r2u: fast, easy, reliable.
I am starting to settle on "fast, easy, reliable" to describe the *magic* that is r2u with full and complete resolution of *all* system dependencies. Plus binaries from r-universe as an extra bonus for non CRAN binaries like rpolars. or tiledbsoma and cellxgene.census here.
The other *very important* aspect is that r2u wins big by giving you binaries right away--instead of wasting *billed* (!!) time on building from source. I still need to write a post on that in the CI/CD context: why run longer/slower jobs that will cost more or may hit a limit?