buckbanzai/seattlecitylight-mastodon-bot
1
0
Fork 0
Code Issues 7 Pull requests Projects Releases Packages Wiki Activity

Update dependency numpy to v2.1.3 #66

Merged
buckbanzai merged 1 commit from renovate/numpy-2.x into main 2024-11-20 11:14:23 -08:00
Conversation 0 Commits 1 Files changed 1 +1 -1
renovate_bot commented 2024-11-06 11:16:35 -08:00
Collaborator
Copy link

This PR contains the following updates:

Package Update Change
numpy (changelog) patch ==2.1.2 -> ==2.1.3

Release Notes

numpy/numpy (numpy)

v2.1.3: 2.1.3 (Nov 2, 2024)

Compare Source

NumPy 2.1.3 Release Notes

NumPy 2.1.3 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.2 release. This release also adds support
for free threaded Python 3.13 on Windows.

The Python versions supported by this release are 3.10-3.13.

Improvements

  • Fixed a number of issues around promotion for string ufuncs with
    StringDType arguments. Mixing StringDType and the fixed-width DTypes
    using the string ufuncs should now generate much more uniform
    results.

    (gh-27636)

Changes

  • numpy.fix now won't perform casting to a floating
    data-type for integer and boolean data-type input arrays.

    (gh-26766)

Contributors

A total of 15 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Abhishek Kumar +
  • Austin +
  • Benjamin A. Beasley +
  • Charles Harris
  • Christian Lorentzen
  • Marcel Telka +
  • Matti Picus
  • Michael Davidsaver +
  • Nathan Goldbaum
  • Peter Hawkins
  • Raghuveer Devulapalli
  • Ralf Gommers
  • Sebastian Berg
  • dependabot[bot]
  • kp2pml30 +

Pull requests merged

A total of 21 pull requests were merged for this release.

  • #​27512: MAINT: prepare 2.1.x for further development
  • #​27537: MAINT: Bump actions/cache from 4.0.2 to 4.1.1
  • #​27538: MAINT: Bump pypa/cibuildwheel from 2.21.2 to 2.21.3
  • #​27539: MAINT: MSVC does not support #warning directive
  • #​27543: BUG: Fix user dtype can-cast with python scalar during promotion
  • #​27561: DEV: bump python to 3.12 in environment.yml
  • #​27562: BLD: update vendored Meson to 1.5.2
  • #​27563: BUG: weighted quantile for some zero weights (#​27549)
  • #​27565: MAINT: Use miniforge for macos conda test.
  • #​27566: BUILD: satisfy gcc-13 pendantic errors
  • #​27569: BUG: handle possible error for PyTraceMallocTrack
  • #​27570: BLD: start building Windows free-threaded wheels [wheel build]
  • #​27571: BUILD: vendor tempita from Cython
  • #​27574: BUG: Fix warning "differs in levels of indirection" in npy_atomic.h...
  • #​27592: MAINT: Update Highway to latest
  • #​27593: BUG: Adjust numpy.i for SWIG 4.3 compatibility
  • #​27616: BUG: Fix Linux QEMU CI workflow
  • #​27668: BLD: Do not set __STDC_VERSION__ to zero during build
  • #​27669: ENH: fix wasm32 runtime type error in numpy._core
  • #​27672: BUG: Fix a reference count leak in npy_find_descr_for_scalar.
  • #​27673: BUG: fixes for StringDType/unicode promoters

Checksums

MD5
3f2f22827dd321ae86b5ab4fa888d0db  numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl
13da2761d1abe71731a2806537369115  numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl
5aef4a78b69cd90d0f6fff8f88817991  numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl
12da7f09cd5707634878f85845c9de10  numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl
5b999693362815b56855533469aea0ca  numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
8c49f457127bfb4f167c91583e5167af  numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
f31c0e80b18afc0c04cada401cbe0358  numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl
2c0709812e27bcaf74d75ac8ed45614b  numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl
a65b28800e78942b9e60e03e96cfd0c0  numpy-2.1.3-cp310-cp310-win32.whl
d8358545732fe4ee1ecf407b06567d81  numpy-2.1.3-cp310-cp310-win_amd64.whl
34942f9a1391532e2c3168043c0021d5  numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl
0d69ec06e303b5112788db68a8fdde1b  numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl
da1988c8d3a9db5947a2bd51290b8b95  numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl
b5eba73c2abaf5a81535f4b1034fe8d2  numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl
63cc090209718aa1d0f0fbd3fd03bc0b  numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
55f14ca7b55554d4a043369ae5f1837f  numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
4e58e0645d81ff84c0fb75311d2a97d6  numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl
30235088a5f86d1f343bfec458f6292d  numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl
c80a03952b2f4950f1eb9d1656413fec  numpy-2.1.3-cp311-cp311-win32.whl
d8c1a5a441b89591af8f09dfa0b2d4d5  numpy-2.1.3-cp311-cp311-win_amd64.whl
2cebcea71e71e8b09a25179b240ee240  numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl
faf5df4bd35ca362795cda193da49591  numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl
573f195910fc3b3e9ac5379816280f89  numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl
900548b2acb82ed0e306943fb68de802  numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl
81cded28bb87c4987b1d975fe768c3a1  numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2b83cb346bca97475fa5e39e704c45f1  numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
06d8593cb7a2aae157e028c3d4cb3c96  numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl
eea8b148a6a2fee37b87291043e00bda  numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl
d407b7c48457789914f28004f41d6ea2  numpy-2.1.3-cp312-cp312-win32.whl
117574ee1a645e63a6d69e20c8673665  numpy-2.1.3-cp312-cp312-win_amd64.whl
0c9ffd1f1f1e96186f30a578b85da653  numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl
cd430b2caf09d21680616aef5d4a439d  numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl
b431935148221b79bda9490b1d069e3c  numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl
b3ff577c78097b187bd58f20b6e88642  numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl
8186f86f8d94a5505e6dcebe6c056ab7  numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2c5b2381a4a4e3d9865ccb346d44a7ed  numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
85786d12388d60b904c02eb12df55b37  numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl
da68282c0418a22730643906e5dd58a1  numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl
fe47e181a70d3e865e5d6a27e5fa71cd  numpy-2.1.3-cp313-cp313-win32.whl
8b7f290784c95cf620e0ac1af5470f1d  numpy-2.1.3-cp313-cp313-win_amd64.whl
4f0c3f8c81cb6bd43a9f1f7bef7db82d  numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl
133905fd003c9504fc5bb9ce71e4103b  numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl
12fe4f265dbda251309f109cbcd46f07  numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl
b60e418506b969e6df2c0d600bf3c6d4  numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl
c2b7160b748f4c1c483a7954e5024250  numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
8097ddb45c8c821085c19d940bcbe6de  numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
209f55dc1ed6da23a5ea3e11ca962308  numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl
06a1792849b601c7bdd38e39bc5cb5f1  numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl
86630bf207e8cbe6933232cb2a47a6c0  numpy-2.1.3-cp313-cp313t-win32.whl
6af9109b82c0acdcf8b0e81dc0e4c517  numpy-2.1.3-cp313-cp313t-win_amd64.whl
c7e821e086346afc0078acb237f30431  numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
5b938b2da78b1c84044df8cdb2e8e63a  numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
ef251f3b6aa022b1c2fac14889d6d9d3  numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
356c7bb6067ae0dccc4a54efc1879e74  numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl
11096358375945114577a0c82b2c6038  numpy-2.1.3.tar.gz
SHA256
c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff  numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl
b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5  numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl
825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1  numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl
6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd  numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl
e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3  numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098  numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c  numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl
fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4  numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl
72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23  numpy-2.1.3-cp310-cp310-win32.whl
ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0  numpy-2.1.3-cp310-cp310-win_amd64.whl
4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d  numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl
c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41  numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl
576a1c1d25e9e02ed7fa5477f30a127fe56debd53b8d2c89d5578f9857d03ca9  numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl
973faafebaae4c0aaa1a1ca1ce02434554d67e628b8d805e61f874b84e136b09  numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl
762479be47a4863e261a840e8e01608d124ee1361e48b96916f38b119cfda04a  numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
bc6f24b3d1ecc1eebfbf5d6051faa49af40b03be1aaa781ebdadcbc090b4539b  numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
17ee83a1f4fef3c94d16dc1802b998668b5419362c8a4f4e8a491de1b41cc3ee  numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl
15cb89f39fa6d0bdfb600ea24b250e5f1a3df23f901f51c8debaa6a5d122b2f0  numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl
d9beb777a78c331580705326d2367488d5bc473b49a9bc3036c154832520aca9  numpy-2.1.3-cp311-cp311-win32.whl
d89dd2b6da69c4fff5e39c28a382199ddedc3a5be5390115608345dec660b9e2  numpy-2.1.3-cp311-cp311-win_amd64.whl
f55ba01150f52b1027829b50d70ef1dafd9821ea82905b63936668403c3b471e  numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl
13138eadd4f4da03074851a698ffa7e405f41a0845a6b1ad135b81596e4e9958  numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl
a6b46587b14b888e95e4a24d7b13ae91fa22386c199ee7b418f449032b2fa3b8  numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl
0fa14563cc46422e99daef53d725d0c326e99e468a9320a240affffe87852564  numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl
8637dcd2caa676e475503d1f8fdb327bc495554e10838019651b76d17b98e512  numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2312b2aa89e1f43ecea6da6ea9a810d06aae08321609d8dc0d0eda6d946a541b  numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
a38c19106902bb19351b83802531fea19dee18e5b37b36454f27f11ff956f7fc  numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl
02135ade8b8a84011cbb67dc44e07c58f28575cf9ecf8ab304e51c05528c19f0  numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl
e6988e90fcf617da2b5c78902fe8e668361b43b4fe26dbf2d7b0f8034d4cafb9  numpy-2.1.3-cp312-cp312-win32.whl
0d30c543f02e84e92c4b1f415b7c6b5326cbe45ee7882b6b77db7195fb971e3a  numpy-2.1.3-cp312-cp312-win_amd64.whl
96fe52fcdb9345b7cd82ecd34547fca4321f7656d500eca497eb7ea5a926692f  numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl
f653490b33e9c3a4c1c01d41bc2aef08f9475af51146e4a7710c450cf9761598  numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl
dc258a761a16daa791081d026f0ed4399b582712e6fc887a95af09df10c5ca57  numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl
016d0f6f5e77b0f0d45d77387ffa4bb89816b57c835580c3ce8e099ef830befe  numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl
c181ba05ce8299c7aa3125c27b9c2167bca4a4445b7ce73d5febc411ca692e43  numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
5641516794ca9e5f8a4d17bb45446998c6554704d888f86df9b200e66bdcce56  numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
ea4dedd6e394a9c180b33c2c872b92f7ce0f8e7ad93e9585312b0c5a04777a4a  numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl
b0df3635b9c8ef48bd3be5f862cf71b0a4716fa0e702155c45067c6b711ddcef  numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl
50ca6aba6e163363f132b5c101ba078b8cbd3fa92c7865fd7d4d62d9779ac29f  numpy-2.1.3-cp313-cp313-win32.whl
747641635d3d44bcb380d950679462fae44f54b131be347d5ec2bce47d3df9ed  numpy-2.1.3-cp313-cp313-win_amd64.whl
996bb9399059c5b82f76b53ff8bb686069c05acc94656bb259b1d63d04a9506f  numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl
45966d859916ad02b779706bb43b954281db43e185015df6eb3323120188f9e4  numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl
baed7e8d7481bfe0874b566850cb0b85243e982388b7b23348c6db2ee2b2ae8e  numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl
a9f7f672a3388133335589cfca93ed468509cb7b93ba3105fce780d04a6576a0  numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl
d7aac50327da5d208db2eec22eb11e491e3fe13d22653dce51b0f4109101b408  numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
4394bc0dbd074b7f9b52024832d16e019decebf86caf909d94f6b3f77a8ee3b6  numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
50d18c4358a0a8a53f12a8ba9d772ab2d460321e6a93d6064fc22443d189853f  numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl
14e253bd43fc6b37af4921b10f6add6925878a42a0c5fe83daee390bca80bc17  numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl
08788d27a5fd867a663f6fc753fd7c3ad7e92747efc73c53bca2f19f8bc06f48  numpy-2.1.3-cp313-cp313t-win32.whl
2564fbdf2b99b3f815f2107c1bbc93e2de8ee655a69c261363a1172a79a257d4  numpy-2.1.3-cp313-cp313t-win_amd64.whl
4f2015dfe437dfebbfce7c85c7b53d81ba49e71ba7eadbf1df40c915af75979f  numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
3522b0dfe983a575e6a9ab3a4a4dfe156c3e428468ff08ce582b9bb6bd1d71d4  numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
c006b607a865b07cd981ccb218a04fc86b600411d83d6fc261357f1c0966755d  numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e14e26956e6f1696070788252dcdff11b4aca4c3e8bd166e0df1bb8f315a67cb  numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl
aa08e04e08aaf974d4458def539dece0d28146d866a39da5639596f4921fd761  numpy-2.1.3.tar.gz

Configuration

📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).

🚦 Automerge: Enabled.

♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.

🔕 Ignore: Close this PR and you won't be reminded about this update again.

  • If you want to rebase/retry this PR, check this box

This PR has been generated by Renovate Bot.

This PR contains the following updates: | Package | Update | Change | |---|---|---| | [numpy](https://github.com/numpy/numpy) ([changelog](https://numpy.org/doc/stable/release)) | patch | `==2.1.2` -> `==2.1.3` | --- ### Release Notes <details> <summary>numpy/numpy (numpy)</summary> ### [`v2.1.3`](https://github.com/numpy/numpy/releases/tag/v2.1.3): 2.1.3 (Nov 2, 2024) [Compare Source](https://github.com/numpy/numpy/compare/v2.1.2...v2.1.3) ### NumPy 2.1.3 Release Notes NumPy 2.1.3 is a maintenance release that fixes bugs and regressions discovered after the 2.1.2 release. This release also adds support for free threaded Python 3.13 on Windows. The Python versions supported by this release are 3.10-3.13. #### Improvements - Fixed a number of issues around promotion for string ufuncs with StringDType arguments. Mixing StringDType and the fixed-width DTypes using the string ufuncs should now generate much more uniform results. ([gh-27636](https://github.com/numpy/numpy/pull/27636)) #### Changes - `numpy.fix` now won't perform casting to a floating data-type for integer and boolean data-type input arrays. ([gh-26766](https://github.com/numpy/numpy/pull/26766)) #### Contributors A total of 15 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Abhishek Kumar + - Austin + - Benjamin A. Beasley + - Charles Harris - Christian Lorentzen - Marcel Telka + - Matti Picus - Michael Davidsaver + - Nathan Goldbaum - Peter Hawkins - Raghuveer Devulapalli - Ralf Gommers - Sebastian Berg - dependabot\[bot] - kp2pml30 + #### Pull requests merged A total of 21 pull requests were merged for this release. - [#&#8203;27512](https://github.com/numpy/numpy/pull/27512): MAINT: prepare 2.1.x for further development - [#&#8203;27537](https://github.com/numpy/numpy/pull/27537): MAINT: Bump actions/cache from 4.0.2 to 4.1.1 - [#&#8203;27538](https://github.com/numpy/numpy/pull/27538): MAINT: Bump pypa/cibuildwheel from 2.21.2 to 2.21.3 - [#&#8203;27539](https://github.com/numpy/numpy/pull/27539): MAINT: MSVC does not support #warning directive - [#&#8203;27543](https://github.com/numpy/numpy/pull/27543): BUG: Fix user dtype can-cast with python scalar during promotion - [#&#8203;27561](https://github.com/numpy/numpy/pull/27561): DEV: bump `python` to 3.12 in environment.yml - [#&#8203;27562](https://github.com/numpy/numpy/pull/27562): BLD: update vendored Meson to 1.5.2 - [#&#8203;27563](https://github.com/numpy/numpy/pull/27563): BUG: weighted quantile for some zero weights ([#&#8203;27549](https://github.com/numpy/numpy/issues/27549)) - [#&#8203;27565](https://github.com/numpy/numpy/pull/27565): MAINT: Use miniforge for macos conda test. - [#&#8203;27566](https://github.com/numpy/numpy/pull/27566): BUILD: satisfy gcc-13 pendantic errors - [#&#8203;27569](https://github.com/numpy/numpy/pull/27569): BUG: handle possible error for PyTraceMallocTrack - [#&#8203;27570](https://github.com/numpy/numpy/pull/27570): BLD: start building Windows free-threaded wheels \[wheel build] - [#&#8203;27571](https://github.com/numpy/numpy/pull/27571): BUILD: vendor tempita from Cython - [#&#8203;27574](https://github.com/numpy/numpy/pull/27574): BUG: Fix warning "differs in levels of indirection" in npy_atomic.h... - [#&#8203;27592](https://github.com/numpy/numpy/pull/27592): MAINT: Update Highway to latest - [#&#8203;27593](https://github.com/numpy/numpy/pull/27593): BUG: Adjust numpy.i for SWIG 4.3 compatibility - [#&#8203;27616](https://github.com/numpy/numpy/pull/27616): BUG: Fix Linux QEMU CI workflow - [#&#8203;27668](https://github.com/numpy/numpy/pull/27668): BLD: Do not set \__STDC_VERSION\_\_ to zero during build - [#&#8203;27669](https://github.com/numpy/numpy/pull/27669): ENH: fix wasm32 runtime type error in numpy.\_core - [#&#8203;27672](https://github.com/numpy/numpy/pull/27672): BUG: Fix a reference count leak in npy_find_descr_for_scalar. - [#&#8203;27673](https://github.com/numpy/numpy/pull/27673): BUG: fixes for StringDType/unicode promoters #### Checksums ##### MD5 3f2f22827dd321ae86b5ab4fa888d0db numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl 13da2761d1abe71731a2806537369115 numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl 5aef4a78b69cd90d0f6fff8f88817991 numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl 12da7f09cd5707634878f85845c9de10 numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl 5b999693362815b56855533469aea0ca numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 8c49f457127bfb4f167c91583e5167af numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl f31c0e80b18afc0c04cada401cbe0358 numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl 2c0709812e27bcaf74d75ac8ed45614b numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl a65b28800e78942b9e60e03e96cfd0c0 numpy-2.1.3-cp310-cp310-win32.whl d8358545732fe4ee1ecf407b06567d81 numpy-2.1.3-cp310-cp310-win_amd64.whl 34942f9a1391532e2c3168043c0021d5 numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl 0d69ec06e303b5112788db68a8fdde1b numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl da1988c8d3a9db5947a2bd51290b8b95 numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl b5eba73c2abaf5a81535f4b1034fe8d2 numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl 63cc090209718aa1d0f0fbd3fd03bc0b numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 55f14ca7b55554d4a043369ae5f1837f numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 4e58e0645d81ff84c0fb75311d2a97d6 numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl 30235088a5f86d1f343bfec458f6292d numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl c80a03952b2f4950f1eb9d1656413fec numpy-2.1.3-cp311-cp311-win32.whl d8c1a5a441b89591af8f09dfa0b2d4d5 numpy-2.1.3-cp311-cp311-win_amd64.whl 2cebcea71e71e8b09a25179b240ee240 numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl faf5df4bd35ca362795cda193da49591 numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl 573f195910fc3b3e9ac5379816280f89 numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl 900548b2acb82ed0e306943fb68de802 numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl 81cded28bb87c4987b1d975fe768c3a1 numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 2b83cb346bca97475fa5e39e704c45f1 numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 06d8593cb7a2aae157e028c3d4cb3c96 numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl eea8b148a6a2fee37b87291043e00bda numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl d407b7c48457789914f28004f41d6ea2 numpy-2.1.3-cp312-cp312-win32.whl 117574ee1a645e63a6d69e20c8673665 numpy-2.1.3-cp312-cp312-win_amd64.whl 0c9ffd1f1f1e96186f30a578b85da653 numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl cd430b2caf09d21680616aef5d4a439d numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl b431935148221b79bda9490b1d069e3c numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl b3ff577c78097b187bd58f20b6e88642 numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl 8186f86f8d94a5505e6dcebe6c056ab7 numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 2c5b2381a4a4e3d9865ccb346d44a7ed numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 85786d12388d60b904c02eb12df55b37 numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl da68282c0418a22730643906e5dd58a1 numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl fe47e181a70d3e865e5d6a27e5fa71cd numpy-2.1.3-cp313-cp313-win32.whl 8b7f290784c95cf620e0ac1af5470f1d numpy-2.1.3-cp313-cp313-win_amd64.whl 4f0c3f8c81cb6bd43a9f1f7bef7db82d numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl 133905fd003c9504fc5bb9ce71e4103b numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl 12fe4f265dbda251309f109cbcd46f07 numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl b60e418506b969e6df2c0d600bf3c6d4 numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl c2b7160b748f4c1c483a7954e5024250 numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 8097ddb45c8c821085c19d940bcbe6de numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 209f55dc1ed6da23a5ea3e11ca962308 numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl 06a1792849b601c7bdd38e39bc5cb5f1 numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl 86630bf207e8cbe6933232cb2a47a6c0 numpy-2.1.3-cp313-cp313t-win32.whl 6af9109b82c0acdcf8b0e81dc0e4c517 numpy-2.1.3-cp313-cp313t-win_amd64.whl c7e821e086346afc0078acb237f30431 numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl 5b938b2da78b1c84044df8cdb2e8e63a numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl ef251f3b6aa022b1c2fac14889d6d9d3 numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 356c7bb6067ae0dccc4a54efc1879e74 numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl 11096358375945114577a0c82b2c6038 numpy-2.1.3.tar.gz ##### SHA256 c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5 numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl 825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1 numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl 6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3 numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098 numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4 numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl 72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23 numpy-2.1.3-cp310-cp310-win32.whl ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0 numpy-2.1.3-cp310-cp310-win_amd64.whl 4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41 numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl 576a1c1d25e9e02ed7fa5477f30a127fe56debd53b8d2c89d5578f9857d03ca9 numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl 973faafebaae4c0aaa1a1ca1ce02434554d67e628b8d805e61f874b84e136b09 numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl 762479be47a4863e261a840e8e01608d124ee1361e48b96916f38b119cfda04a numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl bc6f24b3d1ecc1eebfbf5d6051faa49af40b03be1aaa781ebdadcbc090b4539b numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 17ee83a1f4fef3c94d16dc1802b998668b5419362c8a4f4e8a491de1b41cc3ee numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl 15cb89f39fa6d0bdfb600ea24b250e5f1a3df23f901f51c8debaa6a5d122b2f0 numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl d9beb777a78c331580705326d2367488d5bc473b49a9bc3036c154832520aca9 numpy-2.1.3-cp311-cp311-win32.whl d89dd2b6da69c4fff5e39c28a382199ddedc3a5be5390115608345dec660b9e2 numpy-2.1.3-cp311-cp311-win_amd64.whl f55ba01150f52b1027829b50d70ef1dafd9821ea82905b63936668403c3b471e numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl 13138eadd4f4da03074851a698ffa7e405f41a0845a6b1ad135b81596e4e9958 numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl a6b46587b14b888e95e4a24d7b13ae91fa22386c199ee7b418f449032b2fa3b8 numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl 0fa14563cc46422e99daef53d725d0c326e99e468a9320a240affffe87852564 numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl 8637dcd2caa676e475503d1f8fdb327bc495554e10838019651b76d17b98e512 numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 2312b2aa89e1f43ecea6da6ea9a810d06aae08321609d8dc0d0eda6d946a541b numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl a38c19106902bb19351b83802531fea19dee18e5b37b36454f27f11ff956f7fc numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl 02135ade8b8a84011cbb67dc44e07c58f28575cf9ecf8ab304e51c05528c19f0 numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl e6988e90fcf617da2b5c78902fe8e668361b43b4fe26dbf2d7b0f8034d4cafb9 numpy-2.1.3-cp312-cp312-win32.whl 0d30c543f02e84e92c4b1f415b7c6b5326cbe45ee7882b6b77db7195fb971e3a numpy-2.1.3-cp312-cp312-win_amd64.whl 96fe52fcdb9345b7cd82ecd34547fca4321f7656d500eca497eb7ea5a926692f numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl f653490b33e9c3a4c1c01d41bc2aef08f9475af51146e4a7710c450cf9761598 numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl dc258a761a16daa791081d026f0ed4399b582712e6fc887a95af09df10c5ca57 numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl 016d0f6f5e77b0f0d45d77387ffa4bb89816b57c835580c3ce8e099ef830befe numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl c181ba05ce8299c7aa3125c27b9c2167bca4a4445b7ce73d5febc411ca692e43 numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 5641516794ca9e5f8a4d17bb45446998c6554704d888f86df9b200e66bdcce56 numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl ea4dedd6e394a9c180b33c2c872b92f7ce0f8e7ad93e9585312b0c5a04777a4a numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl b0df3635b9c8ef48bd3be5f862cf71b0a4716fa0e702155c45067c6b711ddcef numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl 50ca6aba6e163363f132b5c101ba078b8cbd3fa92c7865fd7d4d62d9779ac29f numpy-2.1.3-cp313-cp313-win32.whl 747641635d3d44bcb380d950679462fae44f54b131be347d5ec2bce47d3df9ed numpy-2.1.3-cp313-cp313-win_amd64.whl 996bb9399059c5b82f76b53ff8bb686069c05acc94656bb259b1d63d04a9506f numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl 45966d859916ad02b779706bb43b954281db43e185015df6eb3323120188f9e4 numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl baed7e8d7481bfe0874b566850cb0b85243e982388b7b23348c6db2ee2b2ae8e numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl a9f7f672a3388133335589cfca93ed468509cb7b93ba3105fce780d04a6576a0 numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl d7aac50327da5d208db2eec22eb11e491e3fe13d22653dce51b0f4109101b408 numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 4394bc0dbd074b7f9b52024832d16e019decebf86caf909d94f6b3f77a8ee3b6 numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 50d18c4358a0a8a53f12a8ba9d772ab2d460321e6a93d6064fc22443d189853f numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl 14e253bd43fc6b37af4921b10f6add6925878a42a0c5fe83daee390bca80bc17 numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl 08788d27a5fd867a663f6fc753fd7c3ad7e92747efc73c53bca2f19f8bc06f48 numpy-2.1.3-cp313-cp313t-win32.whl 2564fbdf2b99b3f815f2107c1bbc93e2de8ee655a69c261363a1172a79a257d4 numpy-2.1.3-cp313-cp313t-win_amd64.whl 4f2015dfe437dfebbfce7c85c7b53d81ba49e71ba7eadbf1df40c915af75979f numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl 3522b0dfe983a575e6a9ab3a4a4dfe156c3e428468ff08ce582b9bb6bd1d71d4 numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl c006b607a865b07cd981ccb218a04fc86b600411d83d6fc261357f1c0966755d numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl e14e26956e6f1696070788252dcdff11b4aca4c3e8bd166e0df1bb8f315a67cb numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl aa08e04e08aaf974d4458def539dece0d28146d866a39da5639596f4921fd761 numpy-2.1.3.tar.gz </details> --- ### Configuration 📅 **Schedule**: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined). 🚦 **Automerge**: Enabled. ♻ **Rebasing**: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox. 🔕 **Ignore**: Close this PR and you won't be reminded about this update again. --- - [ ] <!-- rebase-check -->If you want to rebase/retry this PR, check this box --- This PR has been generated by [Renovate Bot](https://github.com/renovatebot/renovate). <!--renovate-debug:eyJjcmVhdGVkSW5WZXIiOiIzOC4xMjQuMCIsInVwZGF0ZWRJblZlciI6IjM4LjEyNC4wIiwidGFyZ2V0QnJhbmNoIjoibWFpbiIsImxhYmVscyI6W119-->
renovate_bot added 1 commit 2024-11-06 11:16:35 -08:00
Update dependency numpy to v2.1.3
Some checks failed
ci/woodpecker/pr/lint Pipeline was successful
Details
ci/woodpecker/pr/vulnerability-scan Pipeline failed
Details
ci/woodpecker/pull_request_closed/lint Pipeline was successful
Details
ci/woodpecker/pull_request_closed/vulnerability-scan Pipeline was successful
Details
7f4e8232dc
renovate_bot scheduled this pull request to auto merge when all checks succeed 2024-11-06 11:16:36 -08:00
buckbanzai merged commit fbdc85bc29 into main 2024-11-20 11:14:23 -08:00
Sign in to join this conversation.
Reviewers
No reviewers
Labels
Clear labels
No items
No labels
Milestone
Clear milestone
No items
No milestone
Projects
Clear projects
No items
No project
Assignees
Clear assignees
No assignees
1 participant
Notifications
Due date
The due date is invalid or out of range. Please use the format "yyyy-mm-dd".

No due date set.

Dependencies

No dependencies set.

Reference: buckbanzai/seattlecitylight-mastodon-bot#66
No description provided.
Delete branch "renovate/numpy-2.x"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?