谢谢大家。

我想知道什么是 #include 的正确方法所有 numpy header 以及使用 Cython 和 C++ 解析 numpy 数组的正确方法是什么。下面是尝试:

// cpp_parser.h 
#ifndef _FUNC_H_
#define _FUNC_H_

#include <Python.h>
#include <numpy/arrayobject.h>

void parse_ndarray(PyObject *);

#endif

// cpp_parser.cpp
#include "cpp_parser.h"
#include <iostream>

using namespace std;

void parse_ndarray(PyObject *obj) {
    if (PyArray_Check(obj)) { // this throws seg fault
        cout << "PyArray_Check Passed" << endl;
    } else {
        cout << "PyArray_Check Failed" << endl;
    }
}

# parser.pxd
cdef extern from "cpp_parser.h": 
    cdef void parse_ndarray(object)

# parser.pyx
import numpy as np
cimport numpy as np

def py_parse_array(object x):
    assert isinstance(x, np.ndarray)
    parse_ndarray(x)

# setup.py
from distutils.core import setup, Extension
from Cython.Build import cythonize

import numpy as np

ext = Extension(
    name='parser',
    sources=['parser.pyx', 'cpp_parser.cpp'],
    language='c++',
    include_dirs=[np.get_include()],
    extra_compile_args=['-fPIC'],
)

setup(
    name='parser',
    ext_modules=cythonize([ext])
    )

# run_test.py
import numpy as np
from parser import py_parse_array

x = np.arange(10)
py_parse_array(x)

最佳答案

快速修复 (阅读更多细节和更复杂的方法):

您需要初始化变量PyArray_API通过调用 import_array() 在您使用 numpy-stuff 的每个 cpp 文件中:

//it is only a trick to ensure import_array() is called, when *.so is loaded
//just called only once
int init_numpy(){
     import_array(); // PyError if not successful
     return 0;
}

const static int numpy_initialized =  init_numpy();

void parse_ndarraray(PyObject *obj) { // would be called every time
    if (PyArray_Check(obj)) {
        cout << "PyArray_Check Passed" << endl;
    } else {
        cout << "PyArray_Check Failed" << endl;
    }
}

//use_numpy.h

//your fancy name for the dedicated PyArray_API-symbol
#define PY_ARRAY_UNIQUE_SYMBOL MY_PyArray_API 

//this macro must be defined for the translation unit              
#ifndef INIT_NUMPY_ARRAY_CPP 
    #define NO_IMPORT_ARRAY //for usual translation units
#endif

//now, everything is setup, just include the numpy-arrays:
#include <numpy/arrayobject.h>

//init_numpy_api.cpp

//first make clear, here we initialize the MY_PyArray_API
#define INIT_NUMPY_ARRAY_CPP

//now include the arrayobject.h, which defines
//void **MyPyArray_API
#inlcude "use_numpy.h"

//now the old trick with initialization:
int init_numpy(){
     import_array();// PyError if not successful
     return 0;
}
const static int numpy_initialized =  init_numpy();

//example
#include "use_numpy.h"

...
PyArray_Check(obj); // works, no segmentation error

extra_compile_args=['-fPIC', '-O0', '-g'],
extra_link_args=['-O0', '-g'],

 gdb --args python run_test.py
 (gdb) run
  --- Segmentation fault
 (gdb) disass

   0x00007ffff1d2a6d9 <+20>:    mov    0x203260(%rip),%rax       
       # 0x7ffff1f2d940 <_ZL11PyArray_API>
   0x00007ffff1d2a6e0 <+27>:    add    $0x10,%rax
=> 0x00007ffff1d2a6e4 <+31>:    mov    (%rax),%rax
   ...
   (gdb) print $rax
   $1 = 16

#define PyArray_Check(op) PyObject_TypeCheck(op, &PyArray_Type)

 static void **PyArray_API= __null
 ...
 static int
_import_array(void)
{
  PyArray_API = (void **)PyCapsule_GetPointer(c_api,...

关于python - PyArray_Check 使用 Cython/C++ 给出段错误，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/47026900/