Each time we use R to analyze data, we rely on the assumption that functions used produce correct results. If we can’t make this assumption, we have to spend a lot of time validating every nitty detail. Luckily, we don’t have to do this. There are many reasons for why we can comfortably use R for our analyses and some of them are unique to R. Here are some I could think of while writing this blog post - I’m sure I forgot something:
Parallel ‘Digital Rain’ by Jahobr
After two-and-a-half months, future 1.19.1 is now on CRAN. As usual, there are some bug fixes and minor improvements here and there (NEWS), including things needed by the next version of furrr. For those of you who use Slurm or LSF/OpenLava as a scheduler on your high-performance compute (HPC) cluster, future::availableCores() will now do a better job respecting the CPU resources that those schedulers allocate for your R jobs.
