Segmentation Fault with PyArg_ParseTuple when passing string from Python

Question

I'm trying to write a C extension that accepts numpy arrays as inputs. Everything works fine except when I pass in a string as an argument.

#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include "../../include/Python.h"
#include "../../include/arrayobject.h"

static PyObject *max(PyObject *self, PyObject *args)
{
    PyArrayObject *arr;
    long i, n, strides;

    if (PyArg_ParseTuple(args, "O!", &PyArray_Type, &arr)){
        /* Get some info about the data. */
        n           = PyArray_DIMS(arr)[0];
        strides     = PyArray_STRIDES(arr)[0];
        void *data0 = PyArray_DATA(arr);
        int typenum = PyArray_TYPE(arr);

        if (typenum == NPY_DOUBLE){
            double max = *(double *)data0;
            for (i=0; i<n; ++i){
                if (*(double *)data0 > max){
                    max = *(double *)data0;
                }
                data0 += strides;
            }
            return Py_BuildValue("d", max);
        }
        else if (typenum == NPY_LONG){
            long max = *(long *)data0;
            for (i=0; i<n; ++i){
                if (*(long *)data0 > max){
                    max = *(long *)data0;
                }
                data0 += strides;
            }
            return Py_BuildValue("l", max);
        }
        else {
            PyErr_Format(
                PyExc_TypeError, "\rInput should be a numpy array of numbers."
            );
            return NULL;
        }
    }
    else{
        PyErr_Format(
            PyExc_TypeError, "\rInput should be a numpy array of numbers."
        );
        return NULL;
    }
}

static PyMethodDef DiffMethods[] =
{
    {"max", max, METH_VARARGS, "Compute the maximum of a numpy array."},
    {NULL, NULL, 0, NULL}
};

static struct PyModuleDef cModPyDem =
    {PyModuleDef_HEAD_INIT, "_math_functions", "", -1, DiffMethods};

PyMODINIT_FUNC PyInit__math_functions(void)
{
    import_array();
    return PyModule_Create(&cModPyDem);
}

I then run this setup.py script:

def configuration(parent_package=None, top_path=None):
    import numpy
    from numpy.distutils.misc_util import Configuration
    config.add_extension('_math_functions', ['_math_functions.c'])

    return config

if __name__ == "__main__":
    from numpy.distutils.core import setup
    setup(configuration=configuration)

With these commands:

python setup.py config --compiler=gnu99 build_ext --inplace
rm -rf build/

And that works nicely. The function works for the most part:

In [1]: import _math_functions as mf

In [2]: import numpy as np

In [3]: x = np.random.randint(-1e3, 1e3, size=100)

In [4]: np.max(x), mf.max(x)
Out[4]: (998, 998)

In [5]: x = np.random.rand(100)

In [6]: np.max(x), mf.max(x)
Out[6]: (0.9962604850115798, 0.9962604850115798)

It can also handle inappropriate inputs, somewhat:

In [7]: x = np.array([1,2,"bob"])

In [8]: mf.max(x)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-8-7ced17af9505> in <module>()
----> 1 mf.max(x)

Input should be a numpy array of numbers.

In [9]: mf.max("bob")
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-a656f60cf00d> in <module>()
----> 1 mf.max("bob")

Input should be a numpy array of numbers.

The problem occurs with the following input:

In [10]: x = np.array("Bob")

In [11]: mf.max(x)
Segmentation fault: 11

EDIT: Some things I've tried. Using:

PyArg_ParseTuple(args, "O", &arr)

Instead, this still gave a seg fault. I also put printf("i") before every line (With i=1, 2, ...), so I'm sure the segfault happens at PyArg_ParseTuple.

I read through the documentation and found the "O&" option, but could not get that to work. Any advice on how to properly use that is welcome.

I've also gone through these relevant posts: PyArg_ParseTuple causing segmentation fault

PyArg_ParseTuple SegFaults in CApi (Not sure how the solution to this one would apply...)

Crash when calling PyArg_ParseTuple on a Numpy array

Any clues on how to properly handle this? The output I want is a TypeError being raised.

Thanks!

Sergio Pulgarin · Accepted Answer · 2019-08-11 02:02:56Z

1

Have you tried adding debug statements to figure out exactly where in the code is the segmentation fault happening?.

Assuming that the segmentation fault happens here:

if (PyArg_ParseTuple(args, "O!", &PyArray_Type, &arr)) {

Try adding a different parsing mechanism like "O" in order to not assume that a PyArrayObject instance was passed; then try using the resulting generic PyObject* and check for its type (see PyObject_TypeCheck) and control the flow of the program depending on the type. The way of raising exceptions from here is explained in the Extensions documentation, but I think it goes something like:

PyErr_SetString(PyExc_TypeError, "Input should be a numpy array of numbers.");
return NULL;

answered Aug 11, 2019 at 2:02

Sergio Pulgarin

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1 Comment

Ryan Maguire Over a year ago

Hello, sorry for the delayed response. This is, unfortunately, one of the things I've already tried. I also looked into the "O&" option, but couldn't get that to work. I'd imagine the source code for numpy's max function would suffice, but I couldn't find it. I'll update my post with things I've tried so far.

Ryan Maguire · Accepted Answer · 2019-08-13 16:12:18Z

Oh my, the problem had nothing to do with strings at all. If the input is zero-dimensional, PyArray_DIMS and PyArray_STRIDES return NULL, and therein lies the problem. I put more print statements and the program does indeed get past PyArg_ParseTuple. I truly am a fool. Here's a full working example, I simply added a check for those two pointers.

#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include "../../include/Python.h"
#include "../../include/arrayobject.h"

static PyObject *max(PyObject *self, PyObject *args)
{
    PyArrayObject *arr;
    npy_int i, n, strides;
    void *data0;

    if (PyArg_ParseTuple(args, "O!", &PyArray_Type, &arr)){

        // Check to make sure input isn't zero dimensional!
        if ((PyArray_DIMS(arr) == NULL) || (PyArray_STRIDES(arr) == NULL)){
            PyErr_Format(PyExc_TypeError,
                         "Input is zero-dimensional.");
            return NULL;
        }

        // Useful information about the data.
        int typenum = PyArray_TYPE(arr);
        n           = PyArray_DIMS(arr)[0];
        strides     = PyArray_STRIDES(arr)[0];
        data0       = PyArray_DATA(arr);

        if (typenum == NPY_DOUBLE){
            double max = *(double *)data0;
            for (i=0; i<n; ++i){
                if (*(double *)data0 > max){
                    max = *(double *)data0;
                }
                data0 += strides;
            }
            return Py_BuildValue("d", max);
        }
        else if (typenum == NPY_LONG){
            long max = *(long *)data0;
            for (i=0; i<n; ++i){
                if (*(long *)data0 > max){
                    max = *(long *)data0;
                }
                data0 += strides;
            }
            return Py_BuildValue("l", max);
        }
        else {
            PyErr_Format(PyExc_TypeError,
                         "Input should be a numpy array of numbers.");
            return NULL;
        }
    }
    else{
        PyErr_Format(PyExc_TypeError,
                     "Input should be a numpy array of numbers.");
        return NULL;
    }
}

static PyMethodDef DiffMethods[] =
{
    {"max", max, METH_VARARGS, "Compute the maximum of a numpy array."},
    {NULL, NULL, 0, NULL}
};

static struct PyModuleDef cModPyDem =
    {PyModuleDef_HEAD_INIT, "_math_functions", "", -1, DiffMethods};

PyMODINIT_FUNC PyInit__math_functions(void)
{
    import_array();
    return PyModule_Create(&cModPyDem);
}

Build is the same as before. This passed every test I threw at it thus far:

In [1]: import numpy as np                                                                                                                                  

In [2]: import _math_functions as mf                                                                                                                        

In [3]: for i in range(1000): 
   ...:     for j in range(10): 
   ...:         x = np.random.rand((i+1)*100) 
   ...:         if ((np.max(x) - mf.max(x)) != 0): 
   ...:             print(i, j) 
   ...:         x = np.random.randint(-1e13*(i+1), 1e13*(i+1), size=1000) 
   ...:         if ((np.max(x) - mf.max(x)) !=0): 
   ...:             print(i, j) 
   ...:                                                                                                                                                     
# Nothing prints, so np.max and mf.max are spitting out the same answer.
In [4]: mf.max("Bob")                                                                                                                                       
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-bc67f3e1c10d> in <module>
----> 1 mf.max("Bob")

TypeError: Input should be a numpy array of numbers.

In [5]: mf.max(np.array(1))                                                                                                                                 
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-1cb4380527fa> in <module>
----> 1 mf.max(np.array(1))

TypeError: Input is zero-dimensional.

In [6]: mf.max(np.array("Bob"))                                                                                                                             
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-6-47b1925b8c3c> in <module>
----> 1 mf.max(np.array("Bob"))

TypeError: Input is zero-dimensional.

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