Passing a list and numpy.matrix to a python function from a C ++ application

Question

I have a bunch of functions written in python (for quick prototyping). My main project is in C ++, and I want to call these functions from my C ++ program. These functions use some specialized python modules such as numpy, pyside, etc.

For starters, I have one function that takes 4 arguments. The first is a numpy.matrix object, and the other three are simple python lists. The function returns a numpy.matrix object.

I know that I should use a combination of the Python / C API and the Numpy / C API, but for life I can’t find suitable documentation or examples for those who do something like this.

Is it possible?

Answer 1

This is a very big question, I suggest starting with Extending and Embedding the Python Interpreter in the Python Guide and then Using the NumPy C / API .

Using the Python C / API without crashes or memory requires a good understanding of the Python reference account and C / API.

I prepared a small example that includes Python Interpreter, creates a NumPy array, creates a Python list, and then calls two Python Functions with an array and a list as arguments. This can serve as a starting point that you could expand.

Python functions first:

import numpy def print_matrix(M): print (M) def transform_matrix(M, L): for x in L: M = M*x return M 

Then C ++ code:

 // Python headers #include <Python.h> #include <abstract.h> // NumPy C/API headers #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION // remove warnings #include <numpy/ndarrayobject.h> #include <vector> int main() { // initialize python Py_InitializeEx(1); // import our test module PyObject* numpy_test_module = PyImport_ImportModule("numpy_test"); // retrieve 'print_matrix(); from our module PyObject* print_matrix = PyObject_GetAttrString(numpy_test_module, "print_matrix"); // retrieve 'some_function' from our module PyObject* transform_matrix = PyObject_GetAttrString(numpy_test_module, "transform_matrix"); // no longer need to reference the module directly Py_XDECREF(numpy_test_module); // initialize numpy array library import_array1(-1); // returns -1 on failure // create a new numpy array // array dimensions npy_intp dim[] = {5, 5}; // array data std::vector<double> buffer(25, 1.0); // create a new array using 'buffer' PyObject* array_2d = PyArray_SimpleNewFromData(2, dim, NPY_DOUBLE, &buffer[0]); // print the array by calling 'print_matrix' PyObject* return_value1 = PyObject_CallFunction(print_matrix, "O", array_2d); // we don't need the return value, release the reference Py_XDECREF(return_value1); // create list PyObject* list = PyList_New(3); PyList_SetItem(list, 0, PyLong_FromLong(2)); PyList_SetItem(list, 1, PyLong_FromLong(3)); PyList_SetItem(list, 2, PyLong_FromLong(4)); // call the function with the array as its parameter PyObject* transformed_matrix = PyObject_CallFunction(transform_matrix, "OO", array_2d, list); // no longer need the list, free the reference Py_XDECREF(list); // print the returned array by calling 'print_matrix' PyObject* return_value2 = PyObject_CallFunction(print_matrix, "O", transformed_matrix); // no longer need the 'return_value2', release the reference Py_XDECREF(return_value2); // no longer need 'transformed_matrix' Py_XDECREF(transformed_matrix); // no longer need the array Py_XDECREF(array_2d); // no longer need the reference to transform_matrix Py_XDECREF(transform_matrix); // no longer need the reference to 'print_matrix' Py_XDECREF(print_matrix); // clean up python Py_Finalize(); return 0; }