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MAINT: 1.13.0rc1 prep [wheel build] #20279

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tylerjereddy
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  • A few more version-related changes, and some chance of screw up here given special circumstances of a
    new major NumPy release, but have to continue at it.

  • mixed in with our own version-related changes here are adjustments to avoid some of the "nightly" shims for NumPy pre-release in wheel build infrastructure itself, which perhaps also makes sense to happen on main now that the NumPy 2 beta is on PyPI (depends what you want to test though...);
    I was somewhat concerned this may otherwise lead to us getting nightly NumPy builds off of main instead of more official builds from PyPI (in theory, we're supposed to support 2.1.0 as well, but that seems like an extra degree of confusion and not our desired build target for immediate RC1 wheels...)

  • start probing the wheel builds to see what goes wrong as we look to RC1 and building alongside NumPy 2

[wheel build]

* A few more version-related changes, and some chance
of screw up here given special circumstances of a
new major NumPy release, but have to continue at it.

* mixed in with our own
version-related changes here are adjustments to avoid
some of the "nightly" shims for NumPy pre-release in wheel build
infrastructure itself, which perhaps also makes sense
to happen on `main` now that the NumPy 2 beta is on PyPI (depends
what you want to test though...);
I was somewhat concerned this may otherwise lead to us getting
nightly NumPy builds off of `main` instead of more official
builds from PyPI (in theory, we're supposed to support `2.1.0`
as well, but that seems like an extra degree of confusion
and not our desired build target for immediate RC1 wheels...)

* start probing the wheel builds to see what goes
wrong as we look to RC1 and building alongside NumPy 2

[wheel build]
@tylerjereddy tylerjereddy added the maintenance Items related to regular maintenance tasks label Mar 18, 2024
@tylerjereddy tylerjereddy added this to the 1.13.0 milestone Mar 18, 2024
@github-actions github-actions bot added the CI Items related to the CI tools such as CircleCI, GitHub Actions or Azure label Mar 18, 2024
@tylerjereddy
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@h-vetinari how do things stand on your end re: major concerns?

@lucascolley
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start probing the wheel builds to see what goes wrong

nothing apparently!

@h-vetinari
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@h-vetinari how do things stand on your end re: major concerns?

I haven't tested the 1.13 branch yet, but from my POV I don't have concerns with tagging the release candidate. I'll build that in conda-forge and report back on any issues. I've marked one fix as a backport candidate that would be nice to have for 1.13.0 GA, but not necessary for rc1.

@andyfaff
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These changes look ok to me.

@tylerjereddy tylerjereddy changed the title WIP, MAINT: 1.13.0rc1 prep [wheel build] MAINT: 1.13.0rc1 prep [wheel build] Mar 19, 2024
@tylerjereddy
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Feels like I'm a bit too lucky here, but ok CI is green and folks are happy so in it goes.

@tylerjereddy tylerjereddy merged commit 38fdb9a into scipy:maintenance/1.13.x Mar 19, 2024
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@tylerjereddy tylerjereddy deleted the treddy_1_13_rc1_prep branch March 19, 2024 01:48
@rgommers
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I had a scroll through the logs, it all looks ready for RC1.

This was the one warning that should out; not an immediate problem, but may break the Windows builds once MinGW-w64 reaches 14.0 I suspect:

    [262/1477] Compiling C++ object scipy/sparse/sparsetools/_sparsetools.cp312-win_amd64.pyd.p/sparsetools.cxx.obj
    In file included from ../scipy/sparse/sparsetools/complex_ops.h:9,
                     from ../scipy/sparse/sparsetools/sparsetools.h:10,
                     from ../scipy/sparse/sparsetools/sparsetools.cxx:36:
    C:\Users\runneradmin\AppData\Local\Temp\pip-build-env-zvp86mh4\overlay\Lib\site-packages\numpy\_core\include/numpy/npy_math.h: In function 'npy_longdouble npy_creall(npy_clongdouble)':
    C:\Users\runneradmin\AppData\Local\Temp\pip-build-env-zvp86mh4\overlay\Lib\site-packages\numpy\_core\include/numpy/npy_math.h:405:13: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
      405 |     return ((longdouble_t *) &z)[0];
          |            ~^~~~~~~~~~~~~~~~~~~~

I'll have a long at that later, looks like a minor issue in NumPy.

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5 participants