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Julia? Look, I enjoy playing with Julia, but have you actually used it? Because most of the people I meet who turn up their nose at Python and say nice things
by JPKab 10y ago
Julia? Look, I enjoy playing with Julia, but have you actually used it? Because most of the people I meet who turn up their nose at Python and say nice things about Julia haven't ever used Julia. It's got great potential but has some major gaps and warts, and is just plain dog shit slow for certain things compared to SciPy, which, you may not be aware, is basically C and Fortran code wrapped in Python API.
- pjmlp 10y agoI do follow Julia development and I am aware that it isn't quite there, but at least their community does embrace JIT compilation, not like Python that PyPy is just yet another project, ignored by the reference implementation. > SciPy, which, you may not be aware, is basically C and Fortran code wrapped in Python API. Which for me personally means, that I would rather C and Fortran directly or better yet, a C++, .NET or Java binding to them.
- orf 10y ago> Which for me personally means, that I would rather C and Fortran directly or better yet, a C++, .NET or Java binding to them. Being able to describe things with a syntax that looks almost like pseudocode and runs highly-optimized C/Fortran code to do heavy lifting has huge, huge advantages.
- pjmlp 10y agoScala, Clojure, F# also allow it, with the added benefit of industrial strength JIT/AOT compilers.
- orf 10y agoExcept without the great Python ecosystem and without great projects like Numpy/Scipy
- pjmlp 10y agoNumpy/Scipy are only relevant to a minor set of computer users, and even then, there are alternatives like LANPACK and BLAS. Also Java and .NET ecosystems are just a little bigger than Python.
- orf 10y ago> there are alternatives like LANPACK and BLAS. LANPACK + BLAS = scipy > Numpy/Scipy are only relevant to a minor set of computer users.. > ... Java and .NET ... Being able to describe things with a syntax that looks almost like pseudocode and runs highly-optimized C/Fortran code to do heavy lifting has huge, huge advantages.
- pjmlp 10y ago> LANPACK + BLAS = scipy Thanks, I already knew that. > Being able to describe things with a syntax that looks almost like pseudocode and runs highly-optimized C/Fortran code to do heavy lifting has huge, huge advantages. Hence we are back at Scala, Clojure, F#, enjoying the respective AOT/JIT native code compilers, and integrating with that highly-optimized C/Fortran code.
- orf 10y ago> Scala, Clojure, F# Functional languages. The "year of Linux on the desktop" of programming languages. Also none of those look like pseudocode (Scala does if you ignore bits and squint).
- tavert 10y ago> is just plain dog shit slow for certain things compared to SciPy Do you have real examples here or is this just FUD? SciPy is not known for using absolute state of the art algorithms or perfectly optimized implementations. It can be pretty easy to improve on the naively implemented or legacy pieces of SciPy, e.g. http://tullo.ch/articles/python-vs-julia/ http://tullo.ch/articles/python-vs-julia/