[Python-Dev] Const access to CPython objects outside of GIL?

[Chris Barker]

On Tue, Jul 17, 2018 at 4:34 AM, Victor Stinner <vstinner at redhat.com> wrote:

>
> IMHO you need a different approach to implement optimizations. For
> example, use your objects which don't rely on the GIL to be
> consistent. Sadly, I have no experience with that and so cannot
> provide any example.
>

I DO NOT understand the technical details, but IIUC, numpy releases the GIL
while doing pure numpy operations.

(and I have experimented with it, and it does seem to be the case -- that
is, you can get enhanced performance with computationally heavy numpy code
an multiple threads)

So maybe some lessons learned there.

The key differences may be that numpy arrays are full-fledged python
objects, but they are not (generally) containers of python objects -- that
is, the actual values are i memory accessed via a C pointer. Whereas a
PyList holds pointers to Python objects, so even if are confident in the
stability of the list itself, the objects in the list may not be stable.

 For example, os.stat() writes into a memory block allocated
> by Python. But it's a raw memory block, it's much simpler than a
> Python object like a tuple.


exactly. -- so is a numpy .data element

-CHB




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