Well, I do think there is a lot special about Julia's design that could not be added on to Python - the macro programming, multiple dispatch capabilities and the powerful type system (hopefully with traits built into the language in the future!) are what most set it apart from other languages, in my mind. Those characteristics make it possible to write a very small amount of code, but have the compiler do the work of making highly optimized versions of a function - and do so at compile-time, not run-time (and if a function is called with types that it hasn't seen before, well, it's JITed, so you still have the dynamic nature that makes languages like Python so appealing to people). Best of both worlds, IMO. Keno's work is also making it more and more easy to directly call into C++, so if you have big libraries of optimized C++ code, you can just use them.
All good! (Yes, there's a lot more work that needs to be done, but the fundamentals of Julia are superb). Scott On Tuesday, September 29, 2015 at 2:12:17 PM UTC-4, Christoph Ortner wrote: > > > I prefer Julia to Python for many reasons, not only performance, but > purely regarding performance I often wondered: > > How much is the poor Python performance just a current state. In fact > NUMBA can often take care if it in a very low-effort way. > (a) What is numba lacking now, compared to Julia (performance-wise) > (b) Would it be realistic to assume that a "Python 4" might be built on > top of similar architecture as Julia and hence yield similar performance? > Or is there something special about Julia's design? > > Thanks, > Christoph > >
