Dear Vince,
You probably have heard better solutions but I think what I do works and
is simple to learn. When I need to call C++ code from Python, I write a
wrapper extern "C" function that calls the C++ function that returns the
result. Then I just use ctypes to call the extern "C" function from Python.
C++/C:
extern "C" {
double *get_result(double *input, int n) {
return CPlusPlusFunction::GetResult(input, n);
}
}
Python:
import ctypes
mylib = ctypes.CDLL('libmylib')
def get_result(A):
return mylib.get_result(input.ctypes.data)
I hope this helps.
Damian
> Vince Fulco <vfulco1 <at> gmail.com> writes:
>
> Dear Numpy Experts- I find myself working with Numpy arrays and
> wanting to access *simple* C++ functions for time series returning the
> results to Numpy. As I am a relatively new user of Python/Numpy, the
> number of paths to use in incorporating C++ code into one's scripts is
> daunting. I've attempted the Weave app but can not get past the
> examples. I've also looked at all the other choices out there such as
> Boost, SIP, PyInline, etc. Any trailheads for the simplest approach
> (assuming a very minimal understanding of C++) would be much
> appreciated. At this point, I can't release the code however for
> review. Thank you.
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