how to return numpy.array from boost::python?

Another interface between Boost.Python and NumPy can be found here:

https://github.com/ndarray/Boost.NumPy

It's a moderately complete wrapper of the NumPy C-API into a Boost.Python interface, with the intention of eventually submitting it to Boost. I'm not sure the documentation is any better overall than boost::python::numeric at this point, but there are a lot of code examples and at least it's under active development. It's pretty low-level, and mostly focused on how to address the more difficult problem of how to pass C++ data to and from NumPy without copying, but here's how you'd do a copied std::vector return with that:

#include "boost/numpy.hpp"

namespace bp = boost::python;
namespace bn = boost::numpy;

std::vector<double> myfunc(...);

bn::ndarray mywrapper(...) {
    std::vector<double> v = myfunc(...);
    Py_intptr_t shape[1] = { v.size() };
    bn::ndarray result = bp::zeros(1, shape, bn::dtype::get_builtin<double>());
    std::copy(v.begin(), v.end(), reinterpret_cast<double*>(result.get_data()));
    return result;
}

BOOST_PYTHON_MODULE(example) {
    bn::initialize();
    bp::def("myfunc", mywrapper);
}

Doing it using the numpy api directly is not necessarily difficult, but I use boost::multiarray regularly for my projects and find it convenient to transfer the shapes of the array between the C++/Python boundary automatically. So, here is my recipe. Use http://code.google.com/p/numpy-boost/, or better yet, this version of the numpy_boost.hpp header; which is a better fit for multi-file boost::python projects, although it uses some C++11. Then, from your boost::python code, use something like this:

PyObject* myfunc(/*....*/)
{
   // If your data is already in a boost::multiarray object:
   // numpy_boost< double, 1 > to_python( numpy_from_boost_array(result_cm) );
   // otherwise:
   numpy_boost< double, 1> to_python( boost::extents[n] );
   std::copy( my_vector.begin(), my_vector.end(), to_python.begin() );

   PyObject* result = to_python.py_ptr();
   Py_INCREF( result );

   return result;
}

A solution that doesn't require you to download any special 3rd party C++ library (but you need numpy).

#include <numpy/ndarrayobject.h> // ensure you include this header

boost::python::object stdVecToNumpyArray( std::vector<double> const& vec )
{
      npy_intp size = vec.size();

     // const_cast is rather horrible but we need a writable pointer
      double * data = size ? const_cast<double *>(&vec[0]) : static_cast<double *>(NULL);
    // create a PyObject * from pointer and data 
      PyObject * pyObj = PyArray_SimpleNewFromData( 1, &size, NPY_DOUBLE, data );
      boost::python::handle<> handle( pyObj );
      boost::python::numeric::array arr( handle );

    /* The problem of returning arr is twofold: firstly the user can modify
      the data which will betray the const-correctness 
      Secondly the lifetime of the data is managed by the C++ API and not the lifetime
      of the numpy array whatsoever. But we have a simply solution..
     */

       return arr.copy(); // copy the object. numpy owns the copy now.
  }

Of course you might write a function from double * and size, which is generic then invoke that from the vector by extracting this info. You could also write a template but you'd need some kind of mapping from data type to the NPY_TYPES enum.