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

Chris Barker chris.barker at noaa.gov
Tue Jul 17 12:09:20 EDT 2018

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



Christopher Barker, Ph.D.

Emergency Response Division
NOAA/NOS/OR&R            (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115       (206) 526-6317   main reception

Chris.Barker at noaa.gov
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/python-dev/attachments/20180717/b1c59c8a/attachment.html>

More information about the Python-Dev mailing list