I work with Python but mainly with light statistics (numpy, scipy, pandas and some other libs), SAS is used to work with large datasets (mainly because that's t

I work with Python but mainly with light statistics (numpy, scipy, pandas and some other libs), SAS is used to work with large datasets (mainly because that's the policy of the bank I work). I do not work with CFD anymore, 5 years ago I left the field and returned to Brazil, CUDA/OpenCL was just a promise back them, it was fast but no one had included the technology in their solvers. The problem for CFD is that generally some simulations could take weeks to run, using python here would just add some more weeks just because of the overhead that the language have, if time or energy consumption is a problem people would just stay with what they have right now, for small stuff people use whatever they want (and I used Python back then, these days they use OpenFoam), for performance it will be C, Fortran or C++ compiled with the best optimizing compilers for at least a decade more. In these large problems data transportation and storage was a big problem. Generally people use C++ these days, Fortran is only important in old codebases (although Coarray Fortran was a buzzword just like CUDA when I left the field).