As some of you will know Python is big in bioinformatics, HEP, finance, signal processing and many other computational areas. Originally (and still to some extent) Python was (and still is) used for coordination of Fortran and C++ computations, and for rendering the visualizations. Mathematica, R, Julia, Maple, etc. also have roles in this game.
Those in the Python side of the game disliked C and C++ co much they created abstractions, ending up with NumPy, Cython, ShedSkin, Numba, SciPy and also PyPy to replace CPython. All attempts to write Python and gain native code speed of computation. C is definitely not the right tool for this. C++14 however may give a new impetus especially using Boost.Python. The question is whether the anti-C/C++ mindset, pro NumPy/Cython midset is now so embedded there is no other alternative. It would have been really nice to have had a D option since writing D makes writing C++ look like a labour of Sisyphus. I think it might be a very good idea to ensure that D is a really good tool for native code sub-systems within a Python system. Basically to try and remove the NumPy component, and also the Cython, ShedSkin and Numba ones. As we know from recent little experiments and email list threads, D can create C linkage shared libraries which is exactly what is needed for CPython usage (as PyPy sort of), and there is PyD for create CPython extensions. With a little tidying via "annotations" all the runtime initialization can be handled for C linkage shared libraries, PyD already handles all that for extensions. In a sense all that is needed is some good examples and thence marketing. However I think std.parallelism needs some work: the data parallelism offered is not yet low enough in overhead to really offer argument-free competition to NumPy. The goal needs to be for D + std.parallelism to be as fast of execution as C++ + TBB. Currently it is far from that. Also we need good ARM support so we can run D on RaspberryPis. OK so the GPU of a RaspberryPi is great and the CPU dreadful, but they are the platform of fashion just now. Python is the language of choice, except for those using Java or C and C++. So I suggest two directions to go: 1. Create a NumPy replacement. 2. Ensure D can be used on Raspberry Pis. If there is interest and resource for this then last year was the time to implement, so time is of the essence ;-) -- Russel. ============================================================================= Dr Russel Winder t: +44 20 7585 2200 voip: sip:russel.win...@ekiga.net 41 Buckmaster Road m: +44 7770 465 077 xmpp: rus...@winder.org.uk London SW11 1EN, UK w: www.russel.org.uk skype: russel_winder