Python NumPy数组可增强::: multi_array numpy_boost设置以在C ++和NumPy之间建立接口

Question

I have a C/C++ DLL with libraries I need to call from NumPy, where the format inside the DLL is all boost::multi_array format. While I have seen some posts involving this project: https://github.com/mdboom/numpy-boost there really is very little documentation and examples from users out there on the steps required to wrap the boost::multi_array to NumPy interface with this library. My questions: while the examples are enough to guess the C++ part of the interface (other than strings, how is this handled? Q1), what do you have to do on the Python side to use the compiled DLL (Q2)? It seems Ctypes wouldn't work (correct me if I'm wrong) so does this have to be rewritten in Cython?

For reference, this is the C part with all the datatypes I'm trying to wrap:

extern "C"
{
    DECLDIR void Cfunction(
        boost::multi_array<double, 2>& p_result,
        const vector<string>&          p_calcType,
        const string&                  p_optionType,
        unsigned long                  p_nTimeStep = 50,
        const vector<double>&          p_premium = vector<double>());  

Answer 1

With ctypes you can load DLL dynamically and call functions from it. From my point of view, it's easiest way for using compiled code within Python code. Here is how: How can I use a DLL file from Python?

numpy allows you to get pointer to memory location. Look at that: http://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.ndarray.ctypes.html

If you don't have source code of your DLL and cannot change its interface, you create C++ wrapper (your own separate DLL) that accepts raw pointer from Python instead of boost::multi_array .