Re: NumPy 1.12.0b1 released

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Re: NumPy 1.12.0b1 released

matti picus
Congrats to all on the release.Two questions:

Is there a guide to building standard wheels for NumPy?

Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
OSX64, how can I get them blessed and uploaded to PyPI?

Matti


On 17/11/16 07:47, [hidden email] wrote:

> Date: Wed, 16 Nov 2016 22:47:39 -0700
> From: Charles R Harris<[hidden email]>
> To: numpy-discussion<[hidden email]>, SciPy Users List
> <[hidden email]>,  SciPy Developers List<[hidden email]>,
> [hidden email]
> Subject: [Numpy-discussion] NumPy 1.12.0b1 released.
>
> Hi All,
>
> I'm pleased to annouce the release of NumPy 1.12.0b1. This release
> supports  Python 2.7 and 3.4 - 3.6 and is the result of 388 pull requests
> submitted by 133 contributors. It is quite sizeable and rather than put the
> release notes inline I've attached them as a file and they may also be
> viewed at Github<https://github.com/numpy/numpy/releases/tag/v1.12.0b1>.
> Zip files and tarballs may also be found the Github link. Wheels and source
> archives may be downloaded from PyPI, which is the recommended method.
>
> This release is a large collection of fixes, enhancements, and improvements
> and it is difficult to select just a few as highlights. However, the
> following enhancements may be of particular interest
>
>     - Order of operations in ``np.einsum`` now can be optimized for large
>     speed improvements.
>     - New ``signature`` argument to ``np.vectorize`` for vectorizing with
>     core dimensions.
>     - The ``keepdims`` argument was added to many functions.
>     - Support for PyPy 2.7 v5.6.0 has been added. While not complete, this
>     is a milestone for PyPy's C-API compatibility layer.
>
> Thanks to all,
>
> Chuck

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Re: NumPy 1.12.0b1 released

Matthew Brett
Hi,

On Thu, Nov 17, 2016 at 3:24 PM, Matti Picus <[hidden email]> wrote:
> Congrats to all on the release.Two questions:
>
> Is there a guide to building standard wheels for NumPy?

I don't think so - there is a repository that we use to build the
wheels, that has the Windows, OSX and manyllinux recipes for the
standard CPython build:

https://github.com/MacPython/numpy-wheelso

If you can work out a way to automate the PyPy builds and tests -
especially using the same repo - that would be very useful.

> Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
> OSX64, how can I get them blessed and uploaded to PyPI?

If you can automate the build and tests, I'm guessing there will be no
objections - but it's not my call...

Cheers,

Matthew
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Re: NumPy 1.12.0b1 released

ralfgommers


On Fri, Nov 18, 2016 at 9:08 PM, Matthew Brett <[hidden email]> wrote:
Hi,

On Thu, Nov 17, 2016 at 3:24 PM, Matti Picus <[hidden email]> wrote:
> Congrats to all on the release.Two questions:
>
> Is there a guide to building standard wheels for NumPy?

I don't think so - there is a repository that we use to build the
wheels, that has the Windows, OSX and manyllinux recipes for the
standard CPython build:

https://github.com/MacPython/numpy-wheelso

If you can work out a way to automate the PyPy builds and tests -
especially using the same repo - that would be very useful.

> Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
> OSX64, how can I get them blessed and uploaded to PyPI?

If you can automate the build and tests, I'm guessing there will be no
objections - but it's not my call...

I'm in favor, assuming that the wheel tags and PyPy backwards compatibility situation is OK. Can't really find any examples. What I mean is that for CPython wheels contain tags like "cp27" or "cp35". PyPy wheels should have tags "pp<something>". Are the PyPy cpyext layer and the <something> defined such that a new PyPy release won't break older wheels?

Ralf



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Re: NumPy 1.12.0b1 released

Peter Cock
In reply to this post by matti picus
I have a related question to Matti's,

Do you have any recommendations for building standard wheels
for 3rd party Python libraries which use both the NumPy Python
and C API?

e.g. Do we need to do anything special given the NumPy C API
itself is versioned? Does it matter compiler chain should we use?

Thanks

Peter

On Thu, Nov 17, 2016 at 11:24 PM, Matti Picus <[hidden email]> wrote:

> Congrats to all on the release.Two questions:
>
> Is there a guide to building standard wheels for NumPy?
>
> Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
> OSX64, how can I get them blessed and uploaded to PyPI?
>
> Matti
>
>
> On 17/11/16 07:47, [hidden email] wrote:
>>
>> Date: Wed, 16 Nov 2016 22:47:39 -0700
>> From: Charles R Harris<[hidden email]>
>> To: numpy-discussion<[hidden email]>, SciPy Users List
>>         <[hidden email]>,  SciPy Developers
>> List<[hidden email]>,
>>         [hidden email]
>> Subject: [Numpy-discussion] NumPy 1.12.0b1 released.
>>
>> Hi All,
>>
>> I'm pleased to annouce the release of NumPy 1.12.0b1. This release
>> supports  Python 2.7 and 3.4 - 3.6 and is the result of 388 pull requests
>> submitted by 133 contributors. It is quite sizeable and rather than put
>> the
>> release notes inline I've attached them as a file and they may also be
>> viewed at Github<https://github.com/numpy/numpy/releases/tag/v1.12.0b1>.
>> Zip files and tarballs may also be found the Github link. Wheels and
>> source
>> archives may be downloaded from PyPI, which is the recommended method.
>>
>> This release is a large collection of fixes, enhancements, and
>> improvements
>> and it is difficult to select just a few as highlights. However, the
>> following enhancements may be of particular interest
>>
>>     - Order of operations in ``np.einsum`` now can be optimized for large
>>     speed improvements.
>>     - New ``signature`` argument to ``np.vectorize`` for vectorizing with
>>     core dimensions.
>>     - The ``keepdims`` argument was added to many functions.
>>     - Support for PyPy 2.7 v5.6.0 has been added. While not complete, this
>>     is a milestone for PyPy's C-API compatibility layer.
>>
>> Thanks to all,
>>
>> Chuck
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> [hidden email]
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
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Re: NumPy 1.12.0b1 released

Nathan Goldbaum
Since the NumPy API is forwards compatible, you should use the oldest version of NumPy you would like to support to build your wheels with. The wheels will then work with any future NumPy versions.

On Fri, Nov 18, 2016 at 9:30 AM Peter Cock <[hidden email]> wrote:
I have a related question to Matti's,

Do you have any recommendations for building standard wheels
for 3rd party Python libraries which use both the NumPy Python
and C API?

e.g. Do we need to do anything special given the NumPy C API
itself is versioned? Does it matter compiler chain should we use?

Thanks

Peter

On Thu, Nov 17, 2016 at 11:24 PM, Matti Picus <[hidden email]> wrote:
> Congrats to all on the release.Two questions:
>
> Is there a guide to building standard wheels for NumPy?
>
> Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
> OSX64, how can I get them blessed and uploaded to PyPI?
>
> Matti
>
>
> On 17/11/16 07:47, [hidden email] wrote:
>>
>> Date: Wed, 16 Nov 2016 22:47:39 -0700
>> From: Charles R Harris<[hidden email]>
>> To: numpy-discussion<[hidden email]>, SciPy Users List
>>         <[hidden email]>,  SciPy Developers
>> List<[hidden email]>,
>>         [hidden email]
>> Subject: [Numpy-discussion] NumPy 1.12.0b1 released.
>>
>> Hi All,
>>
>> I'm pleased to annouce the release of NumPy 1.12.0b1. This release
>> supports  Python 2.7 and 3.4 - 3.6 and is the result of 388 pull requests
>> submitted by 133 contributors. It is quite sizeable and rather than put
>> the
>> release notes inline I've attached them as a file and they may also be
>> viewed at Github<https://github.com/numpy/numpy/releases/tag/v1.12.0b1>.
>> Zip files and tarballs may also be found the Github link. Wheels and
>> source
>> archives may be downloaded from PyPI, which is the recommended method.
>>
>> This release is a large collection of fixes, enhancements, and
>> improvements
>> and it is difficult to select just a few as highlights. However, the
>> following enhancements may be of particular interest
>>
>>     - Order of operations in ``np.einsum`` now can be optimized for large
>>     speed improvements.
>>     - New ``signature`` argument to ``np.vectorize`` for vectorizing with
>>     core dimensions.
>>     - The ``keepdims`` argument was added to many functions.
>>     - Support for PyPy 2.7 v5.6.0 has been added. While not complete, this
>>     is a milestone for PyPy's C-API compatibility layer.
>>
>> Thanks to all,
>>
>> Chuck
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> [hidden email]
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
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Re: NumPy 1.12.0b1 released

Peter Cock
Thanks Nathan,

That makes sense (compile using the oldest version of NumPy
we wish to support).

The information on https://github.com/MacPython/numpy-wheels
will probably be very useful too (I've been meaning to try out
appveyor at some point for Windows builds/testing).

Regards,

Peter

On Fri, Nov 18, 2016 at 2:46 PM, Nathan Goldbaum <[hidden email]> wrote:

> Since the NumPy API is forwards compatible, you should use the oldest
> version of NumPy you would like to support to build your wheels with. The
> wheels will then work with any future NumPy versions.
>
> On Fri, Nov 18, 2016 at 9:30 AM Peter Cock <[hidden email]>
> wrote:
>>
>> I have a related question to Matti's,
>>
>> Do you have any recommendations for building standard wheels
>> for 3rd party Python libraries which use both the NumPy Python
>> and C API?
>>
>> e.g. Do we need to do anything special given the NumPy C API
>> itself is versioned? Does it matter compiler chain should we use?
>>
>> Thanks
>>
>> Peter
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Re: NumPy 1.12.0b1 released

Nathaniel Smith
In reply to this post by ralfgommers

On Nov 18, 2016 01:14, "Ralf Gommers" <[hidden email]> wrote:
>
>
>
> On Fri, Nov 18, 2016 at 9:08 PM, Matthew Brett <[hidden email]> wrote:
>>
>> Hi,
>>
>> On Thu, Nov 17, 2016 at 3:24 PM, Matti Picus <[hidden email]> wrote:
>> > Congrats to all on the release.Two questions:
>> >
>> > Is there a guide to building standard wheels for NumPy?
>>
>> I don't think so - there is a repository that we use to build the
>> wheels, that has the Windows, OSX and manyllinux recipes for the
>> standard CPython build:
>>
>> https://github.com/MacPython/numpy-wheelso
>>
>> If you can work out a way to automate the PyPy builds and tests -
>> especially using the same repo - that would be very useful.
>>
>> > Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
>> > OSX64, how can I get them blessed and uploaded to PyPI?
>>
>> If you can automate the build and tests, I'm guessing there will be no
>> objections - but it's not my call...
>
>
> I'm in favor, assuming that the wheel tags and PyPy backwards compatibility situation is OK. Can't really find any examples. What I mean is that for CPython wheels contain tags like "cp27" or "cp35". PyPy wheels should have tags "pp<something>". Are the PyPy cpyext layer and the <something> defined such that a new PyPy release won't break older wheels?

Another thing to think about is that 1.12 on pypy won't pass its test suite (though it's close), and we're not yet testing new PRs on pypy, so no guarantees about 1.13 yet. I think on balance these probably aren't reasons *not* to upload wheels, but it's a funny place where we're talking about providing "official" builds even though it's not an "officially supported platform". So we will at least want to be clear about that. And someone will have to handle the bug reports about the test suite failing :-).

-n


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