Scott, You shouldn't take my reply personal. It wasn't really about the specific string case you mentioned but more in general about Python julia performance comparisons.
On Friday, May 1, 2015 at 3:10:14 PM UTC+2, Scott Jones wrote: > > > On May 1, 2015, at 8:23 AM, Steven Sagaert <[email protected] > <javascript:>> wrote: > > > > On Friday, May 1, 2015 at 12:26:54 PM UTC+2, Scott Jones wrote: >> >> >> >> On Friday, May 1, 2015 at 4:25:50 AM UTC-4, Steven Sagaert wrote: >>> >>> I think the performance comparisons between Julia & Python are flawed. >>> They seem to be between standard Python & Julia but since Julia is all >>> about scientific programming it really should be between SciPi & Julia. >>> Since SciPi uses much of the same underlying libs in Fortran/C the >>> performance gap will be much smaller and to be really fair it should be >>> between numba compiled SciPi code & julia. I suspect the performance will >>> be very close then (and close to C performance). >>> >> >> Why should Julia be limited to scientific programming? >> I think it can be a great language for general programming, >> > > I agree but for now & the short time future I think the core domain of > julia is scientific computing/data science and so to have fair comparisons > one should not just compare julia to vanilla Python but especially scipi & > numba. > > > I stated that my comparisons were of string processing… what’s unfair > about that? I have no expertise to compare Julia to any scientific > computing system, I’ll leave that to the people here that do (and there are > many, very highly qualified). > Also, even in technical computing, the performance issues I raise may be > of some importance, for example, issues about performance connection to a > database… I assume that sometimes you need to read scientific data from a > database, and store results to one? > > Scott > >
