Hi all, as some of you know, I'm a big fan of weave.inline() for the ease of development it offers. Essentially C++ becomes a scripting part of python, with only the occasional recompile overhead (but this is transparent to the users). inline() makes heavy use of the blitz++ library, to represent numpy arrays as blitz arrays and therefore index them as Arr(i,j,k...). This seems to me like a very sound decision, as the blitz library was specifically written to provide simultaneously fortran-like performance with high-level object orientation. With this in mind, I have a few questions: - Is there anything in Numarray's design which prevents this same trick from being used? The core of getting a Numpy array into a blitz one is simply a call to: // Convert a Numpy array to a blitz one, using the original's data (no copy) template<class T, int N> static blitz::Array<T,N> py_to_blitz(PyArrayObject *arr_obj) { blitz::TinyVector<int,N> shape(0); blitz::TinyVector<int,N> strides(0); for (int i=0;i<N;i++) { shape[i] = arr_obj->dimensions[i]; strides[i] = arr_obj->strides[i]/sizeof(T); } return blitz::Array<T,N>((T*) arr_obj->data,shape,strides, blitz::neverDeleteData); } I would not be surprised if something much like this would work for Numarrays, but I'd like to know for sure. - If the above is indeed possible for Numarray, do you guys feel that blitz should be considered an integral part of python's low-level arsenal, or not? I view its advantages especially in the field of an extremely clean, simple syntax (compared to the low-level Numpy API, I'm not familiar with Numarray yet). I've seen examples where a numpy algorithm can be recoded using blitz in a _far_ smaller amount of code, and with performance gains to boot (in some cases, not all). Please note that I am NOT second-guessing any of the design decisions made by the Numarray crowd. I just want to clarify if it's possible to have a C++ API which gives access to numarray with the simplest, highest-level syntax and behavior which is reasonable. This is important for teams where not everyone is an expert on C pointer manipulation details, but they may be perfectly ok with writing loops over things which can be indexed as A(i,j,k). - If any of this seems worthy of more detailed discussion, I told Eric Jones that I'd be happy to coordinate something along these lines at Scipy'03. If there's time in the schedule I'd be glad to do it officially, otherwise we can just try to keep it in mind for a lunch/dinner meeting. Documenting a 'Best Practices for low-level numerical work in python' would probably be a beneficial thing to do for the community. Right now there are so many options that I'm sure I'm not the only one to feel a bit confused. - If Blitz++ is indeed deemed a worthy piece of this puzzle, I wonder if we could contact some of its developers to bring them into this discussion. I worry a bit that activity on its mailing lists seems rather slow, but I noticed that an apparently central guy, Julian C. Cummings, is at CACR/Caltech. Perhaps he could stop by and let us know what the future for blitz looks like. I can fire off an email to him if there is interest in the blitz thing. Anyway, I'm just trying to 'pre-soak' a few ideas for discussion at scipy'03 on these topics. Best regards, Fernando.