Sorry for this not very useful email, but I'd like to share a good piece of
news regarding PyPy.
I got a new PC at work, with modern hardware. I was surprised to see that a
PyPy build just took less than 8 minutes (using pypy2 of course), which is much
better than what I experienced before!
I
- Mail original -
> De: "Carl Friedrich Bolz-Tereick"
> À: "PIERRE AUGIER" , "PyPy Developer
> Mailing List"
> Envoyé: Jeudi 5 Juin 2025 09:53:42
> Objet: Re: [hpy-dev] Re: [pypy-dev] Re: [Numpy-discussion] Better
> compatibility of the
- Mail original -
> De: "matti picus via hpy-dev"
> À: "PyPy Developer Mailing List" , "Ralf Gommers"
> , "hpy-dev"
>
> Envoyé: Vendredi 2 Mai 2025 10:05:51
> Objet: [hpy-dev] Re: [pypy-dev] Re: [Numpy-discussion] Better compatibility
> of the Python scientific/data stack with
> fast
- Mail original -
> De: "Stefan Krah"
> À: "numpy-discussion"
> Envoyé: Mercredi 7 Mai 2025 18:17:38
> Objet: [Numpy-discussion] Re: Better compatibility of the Python
> scientific/data stack with fast Python interpreters
> On Wed, May 07, 2025
Hi,
I try to write a text about what I understood on problems related to the
CPython C API, CPython performance, the scientific Python ecosystem and HPy
(see
https://discuss.python.org/t/c-api-working-group-and-plan-to-get-a-python-c-api-compatible-with-alternative-python-implementations/89477
Thanks Matti for this interesting and sad piece of news.
I also reply on numpy-discuss...@python.org since your message was not post on
this list and take the opportunity to signal another important post about his
subject on discuss.python.org by Stepan Sindelar:
https://discuss.python.org/t/c-
Re: Better compatibility of the Python
> scientific/data stack with fast Python interpreters
> On Tue, Apr 29, 2025 at 11:24 AM PIERRE AUGIER < [
> mailto:pierre.aug...@univ-grenoble-alpes.fr |
> pierre.aug...@univ-grenoble-alpes.fr ] > wrote:
>
>
> Dear Numpy co
and fast Python interpreters?
- Do you have points of view on how this should be done, technically (HPy?,
something else?) and on other aspects (community, NEP?, founding, ...).
- Anything else interesting on this subject?
Best regards,
Pierre
--
Pierre Augier - CR CNRS http://ww
g possible at a lower abstraction level.
- Mail original -
> De: "PIERRE AUGIER"
> À: "hpy-dev"
> Envoyé: Vendredi 25 Avril 2025 22:35:58
> Objet: FYI: question related to HPy on discuss.python.org
> FYI, I asked a question related to HPy on discuss.pytho
Hi,
With 3.13, CPython now has an experimental free-threaded mode (PEP 703). I
understood from the PEP that the free-threaded mode is pushed in particular by
some people working in AI/deep learning (for example with a team working at
Meta on PyTorch). I also see that some work is being done in
Hi PyPy developers and users,
Out of curiosity, are you aware of users of PyPy2.7 not related to RPython and
internal PyPy ? Do you have stats about such usage ?
Best regards,
Pierre
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Hi,
HPy becomes somehow usable :-) I investigated what could give HPy with
something similar to Numpy (piconumpy, a C extension providing an array class).
Some very simple preliminary results:
https://github.com/hpyproject/piconumpy/tree/microbench_loop_sum/bench/microbench_loop_sum
Just an ex
Thank a lot Matti and all PyPy developers for the work done on this release,
Two small remarks on the sentence in the release note: "There are also some
significant performance improvements around maps (dictionaries), ints, strings,
btyes and more. These were done as users reported reproducible
- Mail original -
> De: "Carl Friedrich Bolz-Tereick"
> À: "PIERRE AUGIER" , "pypy-dev"
>
> Envoyé: Mardi 26 Janvier 2021 09:10:20
> Objet: Re: [pypy-dev] Results NBabel benchmark CO2 production versus time:
> good new for PyPy map-improv
Hi,
I did some timing and energy consumption measurements with
https://www.grid5000.fr/w/Energy_consumption_monitoring_tutorial
I think the results tend to validate the approach used in the branch
map-improvements
(https://foss.heptapod.net/pypy/pypy/-/tree/branch/map-improvements). I attach
- Mail original -
> De: "Carl Friedrich Bolz-Tereick"
> À: "pypy-dev" , "PIERRE AUGIER"
> , "pypy-dev"
>
> Envoyé: Mercredi 20 Janvier 2021 12:33:43
> Objet: Re: [pypy-dev] Freelist in PyPy? Reuse short lived objects?
> On
Hello,
I was still playing with the idea to speedup codes using small numerical
objects.
I wrote a Cython extension which defines a Point (3d) cdef class and a Points
cdef class (a vector of points). Both classes contain a pointer towards a
point_ C struct:
ctypedef struct point_:
float x
Hello,
I thought again about this performance issue and this possible extension. One
very important point is to be able to define immutable structures (like Julia
struct) in Python and vectors of such structures. This is really a big
advantage of Julia which makes it much more efficient (see
h
- Mail original -
> De: "Yury V. Zaytsev"
> À: "PIERRE AUGIER"
> Cc: "pypy-dev"
> Envoyé: Mardi 5 Janvier 2021 15:06:02
> Objet: Re: [pypy-dev] New Python/PyPy extension for object oriented
> numerically intensive codes ?
> On Tu
Hello,
I wish you a Happy New Year.
I would be very interested in using PyPy for numerically intensive scientific
codes. I conclude from my experiments that PyPy could potentially be a great
tool but that it is strongly limited in this area by the lack of some features
in Python. For example:
- Mail original -
> De: "Carl Friedrich Bolz-Tereick"
> À: "PIERRE AUGIER" , "pypy-dev"
>
> Envoyé: Jeudi 24 Décembre 2020 07:06:43
> Objet: Re: [pypy-dev] Differences performance Julia / PyPy on very similar
> codes
> On 23.12.20
/microbench_sum_x.py
Is there a better way to store Python objects (homogeneous in type) to be able
to loop over them more efficiency?
Would it be possible to store them in a contiguous array (if it makes sense for
Python objects)?
- Mail original -
> De: "David Edelsohn"
> À: "
- Mail original -
> De: "David Edelsohn"
> À: "PIERRE AUGIER"
> Cc: "pypy-dev"
> Envoyé: Lundi 21 Décembre 2020 23:47:22
> Objet: Re: [pypy-dev] Differences performance Julia / PyPy on very similar
> codes
> You did not state on exac
- Mail original -
> De: "David Edelsohn"
> À: "PIERRE AUGIER"
> Cc: "pypy-dev"
> Envoyé: Lundi 21 Décembre 2020 23:47:22
> Objet: Re: [pypy-dev] Differences performance Julia / PyPy on very similar
> codes
> You did not state on exac
- Mail original -
> De: "David Edelsohn"
> À: "PIERRE AUGIER"
> Cc: "pypy-dev"
> Envoyé: Vendredi 18 Décembre 2020 21:00:42
> Objet: Re: [pypy-dev] Differences performance Julia / PyPy on very similar
> codes
> Does Julia based on LL
Hi,
I post on this list a message written in PyPy issue tracker
(https://foss.heptapod.net/pypy/pypy/-/issues/3349#note_150255). It is about
some experiments I did on writing efficient implementations of the NBody
problem https://github.com/paugier/nbabel to potentially answer to this article
ed to be able to use
Heptapod.
What is the current status of these issues for PyPy? Have you already decided
what to do?
Best regards,
Pierre
--
Pierre Augier - CR CNRS http://www.legi.grenoble-inp.fr
LEGI (UMR 5519) Laboratoire des Ecoulements Geophysiques et Industriels
BP53,
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