Re: [Numpy-discussion] segfault when pickling PyObject arrays

[Paul F. D. <du...@ll...>]

Travis:
Works for me ....using either dump or dumps, load or loads
I used Numeric 20.1.0b1 / Python 2.1 / RedHat 6.2

On Tue, 05 Jun 2001, Tavis Rudd wrote:
> Hi,
> I've been having difficultly pickling arrays with the
> type PyObject using Numeric.  I haven't tried it with
> MA but I assume the same problem exists.
>=20
> This script works
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> from cPickle import dump, load
> from Numeric import array, PyObject
>=20
> def pickleIt(obj, fileName):
>     fp =3D open(fileName, 'w')
>     dump(obj, fp)
>     fp.close
>=20
> def loadIt(fileName):
>     fp =3D open(fileName, 'r')
>     obj =3D load(fp)
>     fp.close()
>     return obj
>=20
> a =3D array(['abc', 'def', 'ghi'], PyObject)
> pickleIt(a, 'test.pickle')
>=20
> This script segfaults
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> #  ... same imports and func defs as above
> b =3D loadIt()
> print b
>=20
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>=20
> I first noticed this when trying to pickle arrays constructed
> from lists of mx.DateTime objects.
>=20
> Numeric 19.1.0
> Python 2.1 final
> Linux 2.2.18
>=20
> Is this a reproduceable bug or something unique to my=20
> setup?
> Tavis
>=20
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