python-c-api

问题 I am having problems using the Embedded Python for C as per the Documentation - Whenever I try using imported modules I get an : Unhandled exception at 0x1e089e85 in PythonIncl.exe: 0xC0000005: Access violation reading location 0x00000004. The error occurs in the PyObject_GetAttrString() method and the documentation isn't much help. I have also tried using tutorials as in an Example from IBM, but always get the same access violation. The following is the example code from one of the tutorials

问题 I have an if clause within a for loop in which I have defined state_out beforehand with: state_out = (PyArrayObject *) PyArray_FromDims(1,dims_new,NPY_BOOL); And the if conditions are like this: if (conn_ctr<sum*2){ *(state_out->data + i*state_out->strides[0]) = true; } else { *(state_out->data + i*state_out->strides[0]) = false; } When commenting these out, state_out returns as an all-False Numpy array. There is a problem with this assignment that I fail to see. As far as I know, all within

问题 I'm writing an implementation of the in-place add operation. But, for some reason, I sometimes get a read-only buffer as result(while I'm adding a custom extension class and an integer...). The relevant code is: static PyObject * ModPoly_InPlaceAdd(PyObject *self, PyObject *other) { if (!ModPoly_Check(self)) { //Since it's in-place addition the control flow should never // enter here(I suppose) if (!ModPoly_Check(other)) { PyErr_SetString(PyExc_TypeError, "Neither argument is a ModPolynomial.

问题 As I understand the relationship between C and C++, the latter is essentially an extension of the former and retains a certain degree of backwards compatibility. Is it safe to assume that the python C API can be called with C++ code? More to the point, I notice that the official python documentation bundles C and C++ extensions together on the same page. Nowhere am I able to find a C++ API. This leads me to believe that the same API is safe to use in both languages. Can someone confirm or

问题 I have a few values defined as symbolic constants in my header file: #define NONE 0x00 #define SYM 0x11 #define SEG 0x43 ... The names of these values represent a certain type of data. Now in my current implementation of my module I put all these symbolic links into an array static unsigned char TYPES[] = { NONE, SYM, SEG, ...} And add the positions of the types in the array as int constants in the module. PyMODINIT_FUNC initShell(void) { PyObject *m; m= Py_InitModule3("Sample", sample

问题 I have a few values defined as symbolic constants in my header file: #define NONE 0x00 #define SYM 0x11 #define SEG 0x43 ... The names of these values represent a certain type of data. Now in my current implementation of my module I put all these symbolic links into an array static unsigned char TYPES[] = { NONE, SYM, SEG, ...} And add the positions of the types in the array as int constants in the module. PyMODINIT_FUNC initShell(void) { PyObject *m; m= Py_InitModule3("Sample", sample

问题 I have a scipy CSR matrix that was constructed from a COO matrix as follows: coord_mat = coo_matrix((data, (row, col)), dtype=np.float64) It is being used as an input to a library with an underlying C implementation, and I believe that the dtype of my matrix is double(np.float64) . However, I'm encountering the following error: ValueError: Buffer dtype mismatch, expected 'flt' but got 'double' I went to do some research and found the scipy C-api, which informed me that the NPY_FLOAT data type

问题 Using the C API, I would like to create a numpy array containing objects of type Quaternion , which is a class I've written in C++. I already have an array of these (actually a std::vector ), and I want to make a copy -- or use the same memory if possible. Since this isn't a basic type, I need to use Py_Object types, and can't use PyArray_SimpleNew or anything easy like that. I'm guessing I might want to use PyArray_NewFromDescr or even PyArray_SimpleNewFromDescr , but I am completely and

问题 The function PyObject* PyArray_TypeObjectFromType(int); converts the type number for a NumPy scalar type (NPY_BOOL, NPY_BYTE, ...) to the corresponding type object. How do you do the opposite conversion, from the type object for a NumPy scalar type to the corresponding type number? Edit: The following code is based on kwatford's answer. It accepts both type objects such as int and numpy.int16, and strings such as "int", u"int" and "int16". int numpyScalarTypeNumber(PyObject* obj) { PyArray

问题 I have a Python extension module which creates a tuple as an attribute of another object, and sets items in the tuple. Whenever I execute this module in Python, I keep getting the error SystemError: bad argument to internal function After reading over the docs for PyTuple , and debugging my program for a few hours, I still couldn't figure out what the hell was going on. Running my program through a debugger indicated the problem was occurring within a library call inside the Python