On 4/19/07, Matthieu Brucher <[EMAIL PROTECTED]> wrote: > > > I forgot you are using C++. > > > Yes, all my code is in C++, and in fact the code I use in Python should be > object-oriented as well, that's why it is not that easy to define how I'm > going to do this... Doing the wrapping in an object oriented way is difficult, and maybe not that useful. This does not prevent the API exposed to python to be OO, of course. > > > Using C++ with ctypes makes the wrapping > > more difficult, I think, specially since you are using templates: you > > would have to write a C wrapper around your classes, and then using > > ctypes on the wrapper (there may be better ways, but I don't see an > > obvious one). Basically, using ctypes is like using code from a > > dynamically loaded library (ala VST :) ). > > > That works great for C then, not that well for C++... Well, this is an inherent problem of C++ when you try to use it from other languages, but let's not start this (again :) ), > > Yes, but even with SWIG, I think I'll have to write wrapper in C or in SWIG > to transform one array in my matrix and vice versa. Well, that should be a > great example for my book ;) > > > I have attached a simplistic example which show how to wrap some > functions. > > > Many thanks, it is simple, I only have to provide the wrappers :| and I have > to do something with the class instance :| I'll think a little bit about how > to do this properly and efficiently > The example shows basic wrapping, and some facilities provided by numpy to help. Again, ctype is pretty efficient as long as you do not need to do convertion. If you call it thousand of times, it will be slow, but this is more or less inherent to python (function calls are nowhere near as fast as in a compiled language, at least for now).
SWIG may be better in your case because it is aware of C++ classes, and is *compiling* an extension, whereas ctypes does not compile anything. This means that you do not have to care about binary interfaces problemes between foreign object codes. SWIG parses a prett good deal of C++, and is aware of classes (template is another matter, obviously). numpy sources contain swig code to process automatically numpy arrays (that is convert C representation of a numpy array to a simple C array and vice et versa), if I remember correctly. There is also boost.python, but I don't know if its situation towards numpy array has changed (eg there was some code lying around to represent numpy arrays in C++). If I were you, and if there are only a few classes and a few member functions, I would try the C wrapper called from python first. David _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
