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Showing content from https://mail.python.org/pipermail/python-dev/2005-November/058171.html below:

[Python-Dev] Problems with the Python Memory Manager

[Python-Dev] Problems with the Python Memory ManagerRobert Kern robert.kern at gmail.com
Wed Nov 16 21:41:00 CET 2005
Josiah Carlson wrote:
> Travis Oliphant <oliphant at ee.byu.edu> wrote:

>>I think definitely, his usage pattern represented a "bad" corner case.  
>>An unusable "corner" case in fact.   At any rate, moving to use the 
>>system free and malloc fixed the immediate problem.  I mainly wanted to 
>>report the problem here just as another piece of anecdotal evidence.
> 
> On the one hand, using PyObjects embedded in an array in scientific
> Python is a good idea; you can use all of the standard Python
> manipulations on them.  On the other hand, other similar projects have
> found it more efficient to never embed PyObjects in their arrays, and
> just allocate them as necessary on access.

That's not what we're doing[1]. The scipy_core arrays here are just
blocks of C doubles. However, the offending code (I believe Chris
Fonnesbeck's PyMC, but I could be mistaken) frequently indexes into
these arrays to get scalar values. In scipy_core, we've defined a set of
numerical types that generally behave like Python ints and floats but
have the underlying storage of the appropriate C data type and have the
various array attributes and methods. When the result of an indexing
operation is a scalar (e.g., arange(10)[0]), it always returns an
instance of the appropriate scalar type. We are "just allocat[ing] them
as necessary on access."

[1] There *is* an array type for general PyObjects in scipy_core, but
that's not being used in the code that blows up and has nothing to do
with the problem Travis is talking about.

-- 
Robert Kern
robert.kern at gmail.com

"In the fields of hell where the grass grows high
 Are the graves of dreams allowed to die."
  -- Richard Harter

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