Francesc Altet wrote:
> Hi,
>
> I was tracking down a memory leak in PyTables and it boiled down to a problem
> in the array protocol. The issue is easily exposed by:
>
> for i in range(1000000):
> numarray.array(numpy.zeros(dtype=numpy.float64, shape=3))
>
> and looking at the memory consumption of the process. The same happens with:
>
> for i in range(1000000):
> numarray.asarray(numpy.zeros(dtype=numpy.float64, shape=3))
>
> However, the numpy<--numarray sense seems to work well.
>
> for i in range(1000000):
> numpy.array(numarray.zeros(type="Float64", shape=3))
>
> Using numarray 1.5.1 and numpy 1.0b1
>
> I think this is a relatively important problem, because it somewhat prevents
> a
> smooth transition from numarray to NumPy.
>
>
I tracked the leak to the numarray function
NA_FromDimsStridesDescrAndData
This function calls NA_NewAllFromBuffer with a brand-new buffer object
when data is passed in (like in the case with the array protocol). That
function then takes a reference to the buffer object but then the
calling function never releases the reference it already holds. This
creates the leak.
I added the line
if (data) {Py_DECREF(buf);}
right after the call to NA_NewAllFromBuffer and the leak disappeared.
For what it's worth, I also think the base object for the new numarray
object should be the object passed in and not the C-object that is
created from it.
In other words in the NA_FromArrayStruct function
a->base = cobj
should be replaced with
Py_INCREF(obj)
a->base = obj
Py_DECREF(cobj)
Best,
-Travis
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