This will be fixed in the coming release of Mercurial, version 6.0. This
is a client side issue.
In the meantime you can work around the issue by adding `--config
storage.revlog.issue6528.fix-incoming=False` to you clone call.
On 10/19/21 3:11 PM, M A wrote:
It is fixed? I tried using 'hg cl
It is fixed? I tried using 'hg clone https://foss.heptapod.net/pypy/pypy pypy'
again and saw the same error. Is there something else I need to do?
> On Oct 18, 2021, at 6:54 PM, Pierre-Yves David
> wrote:
>
> Yeah this was regression that we fixed today:
> https://bz.mercurial-scm.org/show_bu
Yeah this was regression that we fixed today:
https://bz.mercurial-scm.org/show_bug.cgi?id=6605 thanks for reporting it.
On 10/18/21 9:53 PM, M A wrote:
Hi Pierre-Yves. I tried using 'hg clone https://foss.heptapod.net/pypy/pypy'
and saw this error:
$ hg clone https://foss.heptapod.net/pypy/
Hi Pierre-Yves. I tried using 'hg clone https://foss.heptapod.net/pypy/pypy'
and saw this error:
$ hg clone https://foss.heptapod.net/pypy/pypy
destination directory: pypy
applying clone bundle from
https://cellar-c2.services.clever-cloud.com/heptapod-foss-clonebundles/pypy/pypy-2020-02-12-13-12
Can you try with the latest Mercurial release ? (5.9.2)
On 9/19/21 7:44 PM, M A wrote:
Hi I am interested in contributing to PyPy. I tried to clone the source code
repository using hg but saw errors. I then found this git repo:
https://github.com/mozillazg/pypy. I was actually able to clone it
Hi I am interested in contributing to PyPy. I tried to clone the source code
repository using hg but saw errors. I then found this git repo:
https://github.com/mozillazg/pypy. I was actually able to clone it
successfully. Could someone still contribute to PyPy using git instead of hg?
If you ar
Hi!
it's a bit hard to know what what to suggest to start with. Would you be
interested in setting up a Zoom call (eg next week, some evening CET) to
discuss a bit your concrete plans and timeline?
(I for one would be somewhat worried whether all that you are describing
is doable in the timing c
Hi, so to update you both I have decided to pursue this project after all, I'm
very excited to work on PyPy.
To reiterate my objective, I'll be trying to formulate a way to augment the JIT
optimiser to expose enough information such that more advanced optimisations
can be implemented, with Poly
Hi,
On Fri, 18 Dec 2020 at 19:15, muke101 wrote:
> Thanks both of you for getting back to me, these definitely seem like
> problems worth thinking about first. Looking into it, there has actually been
> some research already on implementing Polyhedral optimisations in a JIT
> optimiser, specif
Thanks both of you for getting back to me, these definitely seem like problems
worth thinking about first. Looking into it, there has actually been some
research already on implementing Polyhedral optimisations in a JIT optimiser,
specifically in JavaScript. It's paper
(http://impact.gforge.inr
Hi,
On Thu, 17 Dec 2020 at 23:48, William ML Leslie
wrote:
> The challenge with implementing this in the pypy JIT at this point is
> that the JIT only sees one control flow path. That is, one loop, and
> the branches taken within that loop. It does not find out about the
> outer loop usually un
On Fri, 18 Dec 2020 at 05:14, muke101 via pypy-dev wrote:
>
> I'm doing a computer science masters and am looking for an appropriate
> project to take on for a dissertation related to Polyhedral optimisations.
> Talking to my professor, we both think trying to implement the model and it's
> loo
I'm doing a computer science masters and am looking for an appropriate project
to take on for a dissertation related to Polyhedral optimisations. Talking to
my professor, we both think trying to implement the model and it's loop
transformations in PyPy's JIT optimiser could be a good project to
David,
I would like to ask You, if there is some chance to help with the PyPy
project. I am studying MS Computer Sciences at CTU FEE, Prague.
there is this:
https://doc.pypy.org/en/latest/contributing.html
and in particular the "Your first contribution" section.
Myself, I have only worked
Hello,
I would like to ask You, if there is some chance to help with the PyPy project.
I am studying MS Computer Sciences at CTU FEE, Prague. Thank You for answer
David Koleckar
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Greetings!
I'm very interested in contributing to pypy development. But I'm really not
sure how (or where) to start. So a little bit of a help would be great!
I'm not sure what to do next.
- i'm quite interested in jit development and i'd be very excited to work
there.
- i use Golang in my work a
On 10/17/2011 01:26 PM Alex Gaynor wrote:
On Mon, Oct 17, 2011 at 6:12 AM, Bengt Richter wrote:
On 10/17/2011 12:10 AM Armin Rigo wrote:
Hi,
On Sun, Oct 16, 2011 at 23:41, David Cournapeau
wrote:
Interesting to know. But then, wouldn't this limit the speed gains to
be expected from the
On Mon, Oct 17, 2011 at 6:12 AM, Bengt Richter wrote:
> On 10/17/2011 12:10 AM Armin Rigo wrote:
>
>> Hi,
>>
>> On Sun, Oct 16, 2011 at 23:41, David Cournapeau
>> wrote:
>>
>>> Interesting to know. But then, wouldn't this limit the speed gains to
>>> be expected from the JIT ?
>>>
>>
>> Yes, to
On 10/17/2011 12:10 AM Armin Rigo wrote:
Hi,
On Sun, Oct 16, 2011 at 23:41, David Cournapeau wrote:
Interesting to know. But then, wouldn't this limit the speed gains to
be expected from the JIT ?
Yes, to some extent. It cannot give you the last bit of performance
improvements you could exp
On Mon, Oct 17, 2011 at 10:16 AM, Stefan Behnel wrote:
> Maciej Fijalkowski, 17.10.2011 09:34:
>>
>> On Mon, Oct 17, 2011 at 12:10 AM, Armin Rigo wrote:
>>>
>>> On Sun, Oct 16, 2011 at 23:41, David Cournapeau wrote:
Interesting to know. But then, wouldn't this limit the speed gains to
>>
Maciej Fijalkowski, 17.10.2011 09:34:
On Mon, Oct 17, 2011 at 12:10 AM, Armin Rigo wrote:
On Sun, Oct 16, 2011 at 23:41, David Cournapeau wrote:
Interesting to know. But then, wouldn't this limit the speed gains to
be expected from the JIT ?
Yes, to some extent. It cannot give you the last b
On Mon, Oct 17, 2011 at 12:10 AM, Armin Rigo wrote:
> Hi,
>
> On Sun, Oct 16, 2011 at 23:41, David Cournapeau wrote:
>> Interesting to know. But then, wouldn't this limit the speed gains to
>> be expected from the JIT ?
>
> Yes, to some extent. It cannot give you the last bit of performance
> im
On Sun, Oct 16, 2011 at 10:21 PM, Armin Rigo wrote:
> Hi David,
>
> On Sun, Oct 16, 2011 at 19:13, David Cournapeau wrote:
>> (...) and there is also the issue
>> of correctness in floating point code generation. Given that
>> decade-old compilers get it wrong, I would expect pypy jit to have
>>
Hi,
On Sun, Oct 16, 2011 at 23:41, David Cournapeau wrote:
> Interesting to know. But then, wouldn't this limit the speed gains to
> be expected from the JIT ?
Yes, to some extent. It cannot give you the last bit of performance
improvements you could expect from arithmetic optimizations, but (a
On Sun, Oct 16, 2011 at 5:21 PM, Armin Rigo wrote:
> Hi David,
>
> On Sun, Oct 16, 2011 at 19:13, David Cournapeau
> wrote:
> > (...) and there is also the issue
> > of correctness in floating point code generation. Given that
> > decade-old compilers get it wrong, I would expect pypy jit to hav
Hi David,
On Sun, Oct 16, 2011 at 19:13, David Cournapeau wrote:
> (...) and there is also the issue
> of correctness in floating point code generation. Given that
> decade-old compilers get it wrong, I would expect pypy jit to have
> quite a few funky corner cases as well.
No, we should not hav
On Sun, Oct 16, 2011 at 5:34 PM, Stefan Behnel wrote:
>
> I wasn't comparing a JIT to another compiler. I was comparing it to a human
> programmer. A JIT, just like any other compiler, will never be able to
> *understand* the code it compiles, and it can only apply the optimisations
> that it was
Maciej Fijalkowski, 16.10.2011 20:01:
On Sun, Oct 16, 2011 at 6:34 PM, Stefan Behnel wrote:
Maciej Fijalkowski, 16.10.2011 17:50:
We have proven
already that we can perform several optimizations that are very hard
to perform at the C level. And indeed, while you can always argue
"well, you can
On Sun, Oct 16, 2011 at 2:03 PM, Maciej Fijalkowski wrote:
> On Sun, Oct 16, 2011 at 6:41 PM, Samuel Vaiter
> wrote:
> > Hi,
> >
> > Thanks for you answer.
> >
> >> Yes, there are definitely small things that you can work on.
> >>
> >> A good start would be to pick a missing feature from numpy an
On Sun, Oct 16, 2011 at 6:41 PM, Samuel Vaiter wrote:
> Hi,
>
> Thanks for you answer.
>
>> Yes, there are definitely small things that you can work on.
>>
>> A good start would be to pick a missing feature from numpy and start
>> implementing it. There is usually someone on IRC who can help if yo
On Sun, Oct 16, 2011 at 6:34 PM, Stefan Behnel wrote:
> Maciej Fijalkowski, 16.10.2011 17:50:
>>
>> On Sun, Oct 16, 2011 at 2:29 PM, Stefan Behnel wrote
>>>
>>> Samuel Vaiter, 14.10.2011 17:59:
The main
reason why Numpy is my main interest is that as Ph.D student in
Applied Mat
Hi,
Thanks for you answer.
> Yes, there are definitely small things that you can work on.
>
> A good start would be to pick a missing feature from numpy and start
> implementing it. There is usually someone on IRC who can help if you
> have some immediate questions.
>
> Do you want me to find you
Maciej Fijalkowski, 16.10.2011 17:50:
On Sun, Oct 16, 2011 at 2:29 PM, Stefan Behnel wrote
Samuel Vaiter, 14.10.2011 17:59:
The main
reason why Numpy is my main interest is that as Ph.D student in
Applied Mathematics, I really hope one day we will be able to perform
numerical computation withou
On Sun, Oct 16, 2011 at 11:50 AM, Maciej Fijalkowski wrote:
> On Sun, Oct 16, 2011 at 2:29 PM, Stefan Behnel wrote
> > Samuel Vaiter, 14.10.2011 17:59:
> >>
> >> The main
> >> reason why Numpy is my main interest is that as Ph.D student in
> >> Applied Mathematics, I really hope one day we will b
On Sun, Oct 16, 2011 at 2:29 PM, Stefan Behnel wrote
> Samuel Vaiter, 14.10.2011 17:59:
>>
>> The main
>> reason why Numpy is my main interest is that as Ph.D student in
>> Applied Mathematics, I really hope one day we will be able to perform
>> numerical computation without using heavy binding in
Samuel Vaiter, 14.10.2011 17:59:
The main
reason why Numpy is my main interest is that as Ph.D student in
Applied Mathematics, I really hope one day we will be able to perform
numerical computation without using heavy binding in C/Fortran or
intermediate solution like Cython.
I guess you didn't
On Fri, Oct 14, 2011 at 5:59 PM, Samuel Vaiter wrote:
> Hi,
>
> I am willing to contribute to PyPy, especially on Numpy port. The main
> reason why Numpy is my main interest is that as Ph.D student in
> Applied Mathematics, I really hope one day we will be able to perform
> numerical computation w
Hi,
I am willing to contribute to PyPy, especially on Numpy port. The main
reason why Numpy is my main interest is that as Ph.D student in
Applied Mathematics, I really hope one day we will be able to perform
numerical computation without using heavy binding in C/Fortran or
intermediate solution l
On Thu, Oct 6, 2011 at 10:23 AM, Jez wrote:
> Hi all,
>
> I am a college student interested in contributing to PyPy. I am not too sure
> exactly what I would like to work on, but I would ultimately like to get
> involved with the core JIT code, and I would prefer to work on improving the
> generat
Hi all,
I am a college student interested in contributing to PyPy. I am not too sure
exactly what I would like to work on, but I would ultimately like to get
involved with the core JIT code, and I would prefer to work on improving the
generated code rather than working on tools like the jitviewer.
You didn't say what sort of work you are looking for. Here are some
ideas that I've had on my TODO (at some point) list:
-contribute to micronumpy
-astype
-scalar types like numpy.int8
-a ufunc that isn't implemented yet
-speed up json module by adapting simplejson's pypy-support bran
Hello,
I'd like to contribute to pypy. I've been following the project for a
while but don't know much about the internals apart from reading the
docs. Does anyone have an idea for a good place to start?
-kans
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