概述
编写 c => python 的接口文件
// vectory_py.c extern "C" { vector* new_vector(){ return new vector ; } void delete_vector(vector * v){ cout << "destructor called in C++ for " << v << endl; delete v; } int vector_size(vector * v){ return v->size(); } point_t vector_get(vector * v,int i){ return v->at(i); } void vector_push_back(vector * v,point_t i){ v->push_back(i); } }
编译: gcc -fPIC -shared -lpython3.6m -o vector_py.so vectory_py.c
编写 ctypes 类型文件
from ctypes import * class c_point_t(Structure): _fields_ = [("x",c_int),("y",c_int)] class Vector(object): lib = cdll.LoadLibrary('./vector_py_lib.so') # class level loading lib lib.new_vector.restype = c_void_p lib.new_vector.argtypes = [] lib.delete_vector.restype = None lib.delete_vector.argtypes = [c_void_p] lib.vector_size.restype = c_int lib.vector_size.argtypes = [c_void_p] lib.vector_get.restype = c_point_t lib.vector_get.argtypes = [c_void_p,c_int] lib.vector_push_back.restype = None lib.vector_push_back.argtypes = [c_void_p,c_point_t] lib.foo.restype = None lib.foo.argtypes = [] def __init__(self): self.vector = Vector.lib.new_vector() # pointer to new vector def __del__(self): # when reference count hits 0 in Python,Vector.lib.delete_vector(self.vector) # call C++ vector destructor def __len__(self): return Vector.lib.vector_size(self.vector) def __getitem__(self,i): # access elements in vector at index if 0 <= i < len(self): return Vector.lib.vector_get(self.vector,c_int(i)) raise IndexError('Vector index out of range') def __repr__(self): return '[{}]'.format(','.join(str(self[i]) for i in range(len(self)))) def push(self,i): # push calls vector's push_back Vector.lib.vector_push_back(self.vector,i) def foo(self): # foo in Python calls foo in C++ Vector.lib.foo(self.vector)
然后才是调用
from vector import * a = Vector() b = c_point_t(10,20) a.push(b) a.foo() for i in range(len(a)) : print(a[i].x) print(a[i].y)
为Python写扩展
完成上述的操作后,我头很大,很难想象当项目稍微修改后,我们要跟随变化的代码量有多大!于是换了一种思路,为Python写扩展。
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安装Python开发包
yum install -y python36-devel
#includePyObject* foo() { PyObject* result = PyList_New(0); int i = 0,j = 0; for (j = 0; j < 2; j++) { PyObject* sub = PyList_New(0); for (i = 0; i < 100; ++i) { PyList_Append(sub,Py_BuildValue("{s:i,s:i}","x",i,"y",100 - i)); } PyList_Append(result,sub); } return result; }
from ctypes import * lib = cdll.LoadLibrary('./extlist.so') # class level loading lib lib.foo.restype = py_object b = lib.foo() for i in range(len(b)) : for j in range(len(b[i])) : d = b[i][j] print(d['x'])
很显然,第二种方式中,我已经封装了很复杂的结构了,如果用 c++ 来表示的话,将是:
vector
遇到的问题
Python C 混编时 Segment
这个问题困扰了我有一段时间,开始一直在纠结是代码哪错了,后来恍然大悟,Python 和 C 的堆栈是完全不同的,而当我在交互大量数据的时候,Python GC 可能会把 C 的内存当作未使用,直接给释放了(尤其是上述第二种方案),这就是问题所在。(Python GC 中使用的代龄后续专门开文章来说明,欢迎关注公众号 cn_isnap)
这里的解决方案其实有很多,内存能撑过Python前两代的检查就可了,或者是纯C管理。在这里我推荐一种粗暴的解决方案:
对于任何调用Python对象或Python C API的C代码,确保你首先已经正确地获取和释放了GIL。 这可以用 PyGILState_Ensure() 和 PyGILState_Release() 来做到,如下所示:
... /* Make sure we own the GIL */ PyGILState_STATE state = PyGILState_Ensure(); /* Use functions in the interpreter */ ... /* Restore prevIoUs GIL state and return */ PyGILState_Release(state);
总结
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