Re:Homogenization of scientific computing – Python is eating...
by epaladin on Thursday January 09, 2014 @07:30PM
(#7034253)
Once all of Bioconductor is ported to Julia, I will probably shed some joyous tears.
R is really nice for some things, because of how easy it is to work with table-like data, and operations like applying a function over a vector or a matrix, etc are cake. However, it's also slow, leaky (and sometime seems to use more memory after gc()), and often difficult to debug because so many things fail silently. If it wasn't for so many standard bioinformatics packages being available only for R, I'd probably be using Python. Once we stop running microarrays, I'll probably be using R much less.
R is really nice for some things, because of how easy it is to work with table-like data, and operations like applying a function over a vector or a matrix, etc are cake. However, it's also slow, leaky (and sometime seems to use more memory after gc()), and often difficult to debug because so many things fail silently. If it wasn't for so many standard bioinformatics packages being available only for R, I'd probably be using Python. Once we stop running microarrays, I'll probably be using R much less.