Python segfaults when printing array in IPython

[beojan]

The code

x = np.linspace(0,10,10000)
x

causes a segfault when run in IPython.

This appears to be caused by numpy/core/src/umath/ufunc_object.c line 272:

if (_extract_pyvals(extobj, ufunc_name,
                        buffersize, errormask, NULL) < 0) 

where _extract_pyvals begins

static int
_extract_pyvals(PyObject *ref, char *name, int *bufsize,
                int *errmask, PyObject **errobj)
{
    PyObject *retval;

    if (ref == NULL) {
        *errmask = UFUNC_ERR_DEFAULT;
        *errobj = Py_BuildValue("NO", PyBytes_FromString(name), Py_None);
        *bufsize = NPY_BUFSIZE;
        return 0;
    }

specifically, the *errobj line causes the segfault

[pv]

6d6dc6d ; only in master, not in 1.8.x

[charris]

Works here:

In [1]: x = np.linspace(0,10,10000)

In [2]: x
Out[2]: 
array([  0.00000000e+00,   1.00010001e-03,   2.00020002e-03, ...,
         9.99799980e+00,   9.99899990e+00,   1.00000000e+01])

In [3]: np.__version__
Out[3]: '1.9.0.dev-18acfa4'

Python 2.7, Fedora 19 x86_64.

[seberg]

My guess is that it has something to do with newer Ipython versions (under certain settings) calling some own ufuncs for printing. Maybe @juliantaylor has a quick idea whats going on, I bet it just a missing NULL check.

[juliantaylor]

if one disables setting the default errobj (or somehow manages to set it to NULL?) it crashes,
_extract_pyvals function is inconsistent in handling its arguments, I'll fix it.

[beojan]

As I said before, it does the same thing with the debian packaged IPython 0.13.2-2

[rjurney]

I just checked out master and built from source, installed... I get the same segfault in ipython using pandas.

[juliantaylor]

whats the output of:

numpy.__version__

[rjurney]

'1.9.0.dev-54d3559'

[juliantaylor]

thats a commit before this issue was fixed, please update to the latest head and try again.

[seberg]

That commit looks like just before the fix was merged.

[rjurney]

I have 'git pull origin master' on the master branch from https://github.com/numpy/numpy.git

What other mechanism is there to get to the latest commit?