Python numpy库的ndarray数据结构使用很方便，这里记录一下如何将其传递给C/C++代码，
直接上答案：
使用到的库：ctypes
C++代码部分（toPython.cpp)：
#include extern "C" void showNdarray(int* data, int rows, int cols) {
for (int i = 0;
i < rows;
i++) {
for (int j = 0;
j < cols;
j++) {
printf("data[%d][%d] = %d\n", i,j,data[i * rows + j]);
}
}
}将C++代码编译成动态链接库:
g++ -o topython.so -shared -fPIC toPython.cppPython代码部分：
import ctypes
import numpy as np# 加载动态库
lcpp = ctypes.cdll.LoadLibrary
cpplib = lcpp("./topython.so")def transfer_array_to_cpp() :
data = https://www.it610.com/article/np.array([[1,2,3,4,5],
[2,4,6,8,0]])
dataptr = data.ctypes.data_as(ctypes.c_char_p)
rows, cols = data.shape
# 调用C++函数，将ndarray数据传递给C++
cpplib.showNdarray(dataptr, rows, cols)if __name__ =='__main__' :
transfer_array_to_cpp()【Python:将ndarray数据传递给C++】Python代码放在和C++链接库同一个目录下，运行即可：
data[0][0] = 1
data[0][1] = 0
data[0][2] = 2
data[0][3] = 0
data[0][4] = 3
data[1][0] = 2
data[1][1] = 0
data[1][2] = 3
data[1][3] = 0
data[1][4] = 4
