Description of problem: Python 2.7 deprecated the PyCObject API in favor of a new "capsule" API. http://docs.python.org/dev/whatsnew/2.7.html#capsules The deprecations are set to "ignore" by default, so in theory the API still works. However the deprecation has caused at least one app to fail (virt-manager, see bug 620216, due to it modifying the warning settings), so I've been doublechecking the scope of usage of the PyCObject API, and am filing bugs against components that are possibly affected. You can trigger a hard failure of the API via: >>> import warnings >>> warnings.filterwarnings('error') >>> import numpy python: /root/rpmbuild/BUILD/Python-2.7/Objects/dictobject.c:759: PyDict_SetItem: Assertion `value' failed. Aborted I'm not yet sure what the best approach is to fixing this, but this is a "heads up" to warn about changes to the default warning settings. Not touching the default warning settings may be one workaround. Version-Release number of selected component (if applicable): numpy-1.4.1-6.fc14.src.rpm Grepping through the source tree finds numerous uses of the API: ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:200: A :ctype:`PyCObject` whose :cdata:`voidptr` member contains a ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:202: for the structure is dynamically created and the :ctype:`PyCObject` ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:242: :ctype:`PyCObject` itself (do not confuse this with the "descr" member of ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:246: reference to the object when the :ctype:`PyCObject` is created using ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:247: :ctype:`PyCObject_FromVoidPtrAndDesc`. ./numpy-1.4.1/doc/source/reference/arrays.interface.rst:315:2. The desc member of the PyCObject returned from __array_struct__ was ./numpy-1.4.1/doc/source/reference/c-api.types-and-structures.rst:556: wrapped in a :ctype:`PyCObject *` and keyed by the data-type number. ./numpy-1.4.1/doc/source/reference/c-api.types-and-structures.rst:1066: :ctype:`PyCObject` that contains a pointer to a :ctype:`PyArrayInterface` ./numpy-1.4.1/numpy/numarray/_capi.c:3356: c_api_object = PyCObject_FromVoidPtr((void *)libnumarray_API, NULL); ./numpy-1.4.1/numpy/numarray/numpy/libnumarray.h:50: if (c_api_object && PyCObject_Check(c_api_object)) { \ ./numpy-1.4.1/numpy/numarray/numpy/libnumarray.h:51: libnumarray_API = (void **)PyCObject_AsVoidPtr(c_api_object); \ ./numpy-1.4.1/numpy/core/code_generators/generate_numpy_api.py:57: if (PyCObject_Check(c_api)) { ./numpy-1.4.1/numpy/core/code_generators/generate_numpy_api.py:58: PyArray_API = (void **)PyCObject_AsVoidPtr(c_api); ./numpy-1.4.1/numpy/core/code_generators/generate_ufunc_api.py:47: if (PyCObject_Check(c_api)) { ./numpy-1.4.1/numpy/core/code_generators/generate_ufunc_api.py:48: PyUFunc_API = (void **)PyCObject_AsVoidPtr(c_api); ./numpy-1.4.1/numpy/core/src/umath/ufunc_object.c:370: funcdata = (PyUFunc_Loop1d *)PyCObject_AsVoidPtr(obj); ./numpy-1.4.1/numpy/core/src/umath/ufunc_object.c:515: funcdata = (PyUFunc_Loop1d *)PyCObject_AsVoidPtr(obj); ./numpy-1.4.1/numpy/core/src/umath/ufunc_object.c:3926: cobj = PyCObject_FromVoidPtr((void *)funcdata, _loop1d_list_free); ./numpy-1.4.1/numpy/core/src/umath/ufunc_object.c:3944: current = (PyUFunc_Loop1d *)PyCObject_AsVoidPtr(cobj); ./numpy-1.4.1/numpy/core/src/umath/umathmodule.c.src:271: c_api = PyCObject_FromVoidPtr((void *)PyUFunc_API, NULL); ./numpy-1.4.1/numpy/core/src/multiarray/multiarraymodule.c:2942: c_api = PyCObject_FromVoidPtr((void *)PyArray_API, NULL); ./numpy-1.4.1/numpy/core/src/multiarray/convert_datatype.c:103: if (PyCObject_Check(cobj)) { ./numpy-1.4.1/numpy/core/src/multiarray/convert_datatype.c:104: castfunc = PyCObject_AsVoidPtr(cobj); ./numpy-1.4.1/numpy/core/src/multiarray/scalartypes.c.src:756: return PyCObject_FromVoidPtrAndDesc(inter, arr, gentype_struct_free); ./numpy-1.4.1/numpy/core/src/multiarray/getset.c:548: return PyCObject_FromVoidPtrAndDesc(inter, self, gentype_struct_free); ./numpy-1.4.1/numpy/core/src/multiarray/common.c:213: if (PyCObject_Check(ip)) { ./numpy-1.4.1/numpy/core/src/multiarray/common.c:214: inter=(PyArrayInterface *)PyCObject_AsVoidPtr(ip); ./numpy-1.4.1/numpy/core/src/multiarray/usertypes.c:207: cobj = PyCObject_FromVoidPtr((void *)castfunc, NULL); ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1107: if (PyCObject_Check(e)) { ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1109: inter = (PyArrayInterface *)PyCObject_AsVoidPtr(e); ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1530: if PyCObject_Check(func) { ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1533: cfunc = PyCObject_AsVoidPtr(func); ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1968: if (!PyCObject_Check(attr)) { ./numpy-1.4.1/numpy/core/src/multiarray/ctors.c:1971: inter = PyCObject_AsVoidPtr(attr); ./numpy-1.4.1/numpy/core/include/numpy/ndarrayobject.h:576:#define PyDataType_GetDatetimeMetaData(descr) ((descr->metadata == NULL) ? NULL : ((PyArray_DatetimeMetaData *)(PyCObject_AsVoidPtr(PyDict_GetItemString(descr->metadata, NPY_METADATA_DTSTR))))) ./numpy-1.4.1/numpy/core/include/numpy/ndarrayobject.h:1209: PyCObject attribute of an array __array_struct__. See ./numpy-1.4.1/numpy/f2py/src/fortranobject.c:232: PyObject *cobj = PyCObject_FromVoidPtr((void *)(fp->defs[0].data),NULL); ./numpy-1.4.1/numpy/f2py/cb_rules.py:64:\tif (PyCObject_Check(#name#_capi)) { ./numpy-1.4.1/numpy/f2py/cb_rules.py:66:\t#name#_cptr = PyCObject_AsVoidPtr(#name#_capi); ./numpy-1.4.1/numpy/f2py/cfuncs.py:1002:\t\telse if (PyCObject_Check(fun)) { ./numpy-1.4.1/numpy/f2py/rules.py:395: PyObject_SetAttrString(o,"_cpointer", PyCObject_FromVoidPtr((void*)#F_FUNC#(#name_lower#,#NAME#),NULL)); ./numpy-1.4.1/numpy/f2py/rules.py:689:if(PyCObject_Check(#varname#_capi)) { ./numpy-1.4.1/numpy/f2py/rules.py:690: #varname#_cptr = PyCObject_AsVoidPtr(#varname#_capi); ./numpy-1.4.1/numpy/lib/type_check.py:621: func = ctypes.pythonapi.PyCObject_AsVoidPtr ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:34: int PyCObject_Check(object p) ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:35: object PyCObject_FromVoidPtr(void* cobj, destructor1 destr) ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:36: object PyCObject_FromVoidPtrAndDesc(void* cobj, void* desc, ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:38: void* PyCObject_AsVoidPtr(object self) ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:39: void* PyCObject_GetDesc(object self) ./numpy-1.4.1/numpy/random/mtrand/Python.pxi:40: int PyCObject_SetVoidPtr(object self, void* cobj) ./numpy-1.4.1/numpy/random/mtrand/mtrand.c:244:#define __Pyx_ImportRefcountAPI(name) (__Pyx_RefnannyAPIStruct *) PyCObject_Import((char *)name, (char *)"RefnannyAPI")
The new version of numpy claims to work on python3, so that would solve this issue...
There seems to be some upstream discussion about this: http://www.mail-archive.com/numpy-discussion@scipy.org/msg26318.html In http://www.mail-archive.com/numpy-discussion@scipy.org/msg26669.html , Charles R Harris said: > ...I believe the Python devs reversed the full > deprecation before the final 2.7 release. > > So I think we should just stick with PyCObject on 2.x, as we have done so > far. I'll just bump the version checks so that PyCapsule is used only on > 3.x. My understanding is that although there was python-dev discussion of removing the deprecation warning, I don't think it's actually been removed in the upstream 2.7 branch yet. (In reply to comment #1) > The new version of numpy claims to work on python3, so that would solve this > issue... Not necessarily: python 3.0.*, 3.1.* and 3.2 releases prior to 3.2a2 (iirc) contain the PyCObject API. IIRC, it was removed altogether in 3.2a2
Numpy 1.5.x uses PyCapsule when compiled for Python > 3.0. However, we decided to stick with PyCObject for the Python 2.x series to maintain backward compatibility with other projects that depend on numpy. Modifying the codebase to use PyCObject for 2.7 isn't much work, you just need to change a couple of versions checks.
Fedora 14 is End-of-Life, please reopen against a current release if this bug is still occurring. Thank you!
Reopening, and updating version to "rawhide": I checked in numpy-1.6.1, and it still uses PyCObject for Python 2.x As noted in comment #3, we could port this for our Python 2.7 [BTW, why was closed with the resolution "ERRATA"? Surely "DEFERRED" would have been more appropriate for autoclosing bugs based on the reported version]
I'm not clear what changes need to be made. You're right, I should have used DEFERRED.
(In reply to comment #6) > I'm not clear what changes need to be made. > > You're right, I should have used DEFERRED. [Sorry if I came across as picky. I'm hoping to do a sweep through all of the remaining PyCObject code and actually port them at some point, but swamped with other stuff ATM]
No worries. :) If there's anything I can do, let me know.
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