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That's fair. And, certainly, there's nothing wrong with a glue language geared toward computation. Then, from my perspective, the question for me becomes whether Julia provides an good resources for the end application. Stuff like good plotting, reading from databases and diverse file formats, easy to generate GUIs, etc. Honestly, that's part of why I think Python became popular in the computation world. Personally, I dislike the language, but I support it because there's code floating around to do just about anything for the end application and that's hugely useful. There's one other domain that, depending, Julia may fit well. At the moment, I prototype everything in MATLAB/Octave because the debugger drops us into a REPL where we can perform arbitrary computations on terms easily. Technically, this is possible in something like Python, but it's moderately hateful compared to MATLAB/Octave because factorizing, spectral analysis, and plotting can be done extremely easily in MATLAB/Octave. That said, I tend not to keep my codes there since MATLAB/Octave are not good, in my opinion, for developing large, deliverable applications. As such, in my business where I quickly develop one off prototype codes on a tight deadline, maybe it would be a reasonable choice. Though, thinking about it, there may be licensing problems. The value in MATLAB is that they provide the appropriate commercial license for codes like FFTW and the good routines out of SuiteSparse rather than the default GPL. I'm looking now and it's not clear to me Julia provides the same kind of cover. This complicates the prototyping angle. |