Update dependency numpy to v2.1.2 #59

Merged
renovate_bot merged 1 commit from renovate/numpy-2.x into main 2024-10-05 12:00:43 -07:00
Collaborator

This PR contains the following updates:

Package Update Change
numpy (source, changelog) patch ==2.1.1 -> ==2.1.2

Release Notes

numpy/numpy (numpy)

v2.1.2: 2.1.2 (Oct 5, 2024)

Compare Source

NumPy 2.1.2 Release Notes

NumPy 2.1.2 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.1 release.

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

Contributors

A total of 11 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Charles Harris
  • Chris Sidebottom
  • Ishan Koradia +
  • João Eiras +
  • Katie Rust +
  • Marten van Kerkwijk
  • Matti Picus
  • Nathan Goldbaum
  • Peter Hawkins
  • Pieter Eendebak
  • Slava Gorloff +

Pull requests merged

A total of 14 pull requests were merged for this release.

  • #​27333: MAINT: prepare 2.1.x for further development
  • #​27400: BUG: apply critical sections around populating the dispatch cache
  • #​27406: BUG: Stub out get_build_msvc_version if distutils.msvccompiler...
  • #​27416: BUILD: fix missing include for std::ptrdiff_t for C++23 language...
  • #​27433: BLD: pin setuptools to avoid breaking numpy.distutils
  • #​27437: BUG: Allow unsigned shift argument for np.roll
  • #​27439: BUG: Disable SVE VQSort
  • #​27471: BUG: rfftn axis bug
  • #​27479: BUG: Fix extra decref of PyArray_UInt8DType.
  • #​27480: CI: use PyPI not scientific-python-nightly-wheels for CI doc...
  • #​27481: MAINT: Check for SVE support on demand
  • #​27484: BUG: initialize the promotion state to be weak
  • #​27501: MAINT: Bump pypa/cibuildwheel from 2.20.0 to 2.21.2
  • #​27506: BUG: avoid segfault on bad arguments in ndarray.__array_function__

Checksums

MD5
4aae28b7919b126485c1aaccee37a6ba  numpy-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl
172614423a82ef73d8752ad8a59cbafc  numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl
5ee5e7a8a892cbe96ee228ca5fe7546b  numpy-2.1.2-cp310-cp310-macosx_14_0_arm64.whl
9ce6f9222dfabd32e66b883f1fe015aa  numpy-2.1.2-cp310-cp310-macosx_14_0_x86_64.whl
291da8bfeb7c9a3491ec35ecb2596335  numpy-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
9317d9b049f09c0193f074a6458cf79b  numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
1f2c121533715d8b099d6498e4498f81  numpy-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl
2834df46e2cb2e81cbe4fd1ce9b96b4b  numpy-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl
cbc3ae2c176324fe2a9c04ec0aff181f  numpy-2.1.2-cp310-cp310-win32.whl
e4d74f9d188dc3fe7a65adf8c01e98cc  numpy-2.1.2-cp310-cp310-win_amd64.whl
cbcece9c21ed1daf60f3729a37b32266  numpy-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl
0e62474993ff6faca9c467f68cc16ceb  numpy-2.1.2-cp311-cp311-macosx_11_0_arm64.whl
8747e85e09b2000a0af5a8226740dc92  numpy-2.1.2-cp311-cp311-macosx_14_0_arm64.whl
34e7f3591ce81926518a36c92038a056  numpy-2.1.2-cp311-cp311-macosx_14_0_x86_64.whl
0ec3e617161b42d643aaa4b8d3e477f5  numpy-2.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
e2a6a419b4672bfb4f3f6a98c0e575bb  numpy-2.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
8c14b4d03fc8672e43eddd3ede89be09  numpy-2.1.2-cp311-cp311-musllinux_1_1_x86_64.whl
dc183e12b24317bf210fb093da598d29  numpy-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl
4918f2c32ca3be20c7c5d8551e649757  numpy-2.1.2-cp311-cp311-win32.whl
a8991919b6fae3c7a77c260f60a5e2e2  numpy-2.1.2-cp311-cp311-win_amd64.whl
879f307d16f9222c49508be5ea6491fc  numpy-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl
fe9dfac7bee0cff178737e1706aee61a  numpy-2.1.2-cp312-cp312-macosx_11_0_arm64.whl
1f0c671db3294f4df8bffedc41a2e37f  numpy-2.1.2-cp312-cp312-macosx_14_0_arm64.whl
d131c4bd6ba29b05a5b7fa74e87a0506  numpy-2.1.2-cp312-cp312-macosx_14_0_x86_64.whl
8f9cca33590be334d44cc026a3716966  numpy-2.1.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
3692a9290dd430e56e1b15387c25b7af  numpy-2.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
3549439284dbb1a05785b535c3de60d9  numpy-2.1.2-cp312-cp312-musllinux_1_1_x86_64.whl
b9934410f20505e5c4b70974cd8fdc26  numpy-2.1.2-cp312-cp312-musllinux_1_2_aarch64.whl
96759e3380e4893b9b88d5d498d856b2  numpy-2.1.2-cp312-cp312-win32.whl
f94c7405ed72a136e374ab82400fefdc  numpy-2.1.2-cp312-cp312-win_amd64.whl
2ea775cb4da02f39edf3089af60bddd5  numpy-2.1.2-cp313-cp313-macosx_10_13_x86_64.whl
354d0970154dd002573f4291e0e9de76  numpy-2.1.2-cp313-cp313-macosx_11_0_arm64.whl
bbfee75640b337e12f894d0b54727d66  numpy-2.1.2-cp313-cp313-macosx_14_0_arm64.whl
a443fff50571df87f687ad55c9060d25  numpy-2.1.2-cp313-cp313-macosx_14_0_x86_64.whl
9f8cd7de5b5aa5ad8ba52608a4b0a3b8  numpy-2.1.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
c198fe3deaa77fb94d15284b4e26b875  numpy-2.1.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
0a59171c983fc2d8ea599bdf382c3d6a  numpy-2.1.2-cp313-cp313-musllinux_1_1_x86_64.whl
5ba974cd59fb8c9fc94787c754a5f636  numpy-2.1.2-cp313-cp313-musllinux_1_2_aarch64.whl
93d5c642606fe8abeff0e6db31ebe88f  numpy-2.1.2-cp313-cp313-win32.whl
f6455bb4311ddde071a5ea2e14016003  numpy-2.1.2-cp313-cp313-win_amd64.whl
d2a21857c924d4b1b3c8ae8a9e9b9bb4  numpy-2.1.2-cp313-cp313t-macosx_10_13_x86_64.whl
cd6afcbd05835255750a2fba6012c565  numpy-2.1.2-cp313-cp313t-macosx_11_0_arm64.whl
d2fab663ea84f1cfe13dfc00dae74fb6  numpy-2.1.2-cp313-cp313t-macosx_14_0_arm64.whl
9477b923000d63617324c487a4ce0e28  numpy-2.1.2-cp313-cp313t-macosx_14_0_x86_64.whl
84b621a2c9a8c077bc9c471abd2b3933  numpy-2.1.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
b1c341c7192d03e8f0f5e7c4b9b6f894  numpy-2.1.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
b59750ea55cf274854f64109bf67a112  numpy-2.1.2-cp313-cp313t-musllinux_1_1_x86_64.whl
33f4d63f81ad85c1ea873197f2189d89  numpy-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl
f26a9ac42953c84c94f8203b2dbc61c0  numpy-2.1.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
e7cf2857582d507dfa3e8644dd3562a6  numpy-2.1.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
9e3d44cb302c629c00fde8f25809b04d  numpy-2.1.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
3f97ee2d9962cf9d84624f725bdd2a8f  numpy-2.1.2-pp310-pypy310_pp73-win_amd64.whl
3d92e07d34f60dbac6b82a0982a98757  numpy-2.1.2.tar.gz
SHA256
30d53720b726ec36a7f88dc873f0eec8447fbc93d93a8f079dfac2629598d6ee  numpy-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl
e8d3ca0a72dd8846eb6f7dfe8f19088060fcb76931ed592d29128e0219652884  numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl
fc44e3c68ff00fd991b59092a54350e6e4911152682b4782f68070985aa9e648  numpy-2.1.2-cp310-cp310-macosx_14_0_arm64.whl
7c1c60328bd964b53f8b835df69ae8198659e2b9302ff9ebb7de4e5a5994db3d  numpy-2.1.2-cp310-cp310-macosx_14_0_x86_64.whl
6cdb606a7478f9ad91c6283e238544451e3a95f30fb5467fbf715964341a8a86  numpy-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d666cb72687559689e9906197e3bec7b736764df6a2e58ee265e360663e9baf7  numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c6eef7a2dbd0abfb0d9eaf78b73017dbfd0b54051102ff4e6a7b2980d5ac1a03  numpy-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl
12edb90831ff481f7ef5f6bc6431a9d74dc0e5ff401559a71e5e4611d4f2d466  numpy-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl
a65acfdb9c6ebb8368490dbafe83c03c7e277b37e6857f0caeadbbc56e12f4fb  numpy-2.1.2-cp310-cp310-win32.whl
860ec6e63e2c5c2ee5e9121808145c7bf86c96cca9ad396c0bd3e0f2798ccbe2  numpy-2.1.2-cp310-cp310-win_amd64.whl
b42a1a511c81cc78cbc4539675713bbcf9d9c3913386243ceff0e9429ca892fe  numpy-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl
faa88bc527d0f097abdc2c663cddf37c05a1c2f113716601555249805cf573f1  numpy-2.1.2-cp311-cp311-macosx_11_0_arm64.whl
c82af4b2ddd2ee72d1fc0c6695048d457e00b3582ccde72d8a1c991b808bb20f  numpy-2.1.2-cp311-cp311-macosx_14_0_arm64.whl
13602b3174432a35b16c4cfb5de9a12d229727c3dd47a6ce35111f2ebdf66ff4  numpy-2.1.2-cp311-cp311-macosx_14_0_x86_64.whl
1ebec5fd716c5a5b3d8dfcc439be82a8407b7b24b230d0ad28a81b61c2f4659a  numpy-2.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
e2b49c3c0804e8ecb05d59af8386ec2f74877f7ca8fd9c1e00be2672e4d399b1  numpy-2.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
2cbba4b30bf31ddbe97f1c7205ef976909a93a66bb1583e983adbd155ba72ac2  numpy-2.1.2-cp311-cp311-musllinux_1_1_x86_64.whl
8e00ea6fc82e8a804433d3e9cedaa1051a1422cb6e443011590c14d2dea59146  numpy-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl
5006b13a06e0b38d561fab5ccc37581f23c9511879be7693bd33c7cd15ca227c  numpy-2.1.2-cp311-cp311-win32.whl
f1eb068ead09f4994dec71c24b2844f1e4e4e013b9629f812f292f04bd1510d9  numpy-2.1.2-cp311-cp311-win_amd64.whl
d7bf0a4f9f15b32b5ba53147369e94296f5fffb783db5aacc1be15b4bf72f43b  numpy-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl
b1d0fcae4f0949f215d4632be684a539859b295e2d0cb14f78ec231915d644db  numpy-2.1.2-cp312-cp312-macosx_11_0_arm64.whl
f751ed0a2f250541e19dfca9f1eafa31a392c71c832b6bb9e113b10d050cb0f1  numpy-2.1.2-cp312-cp312-macosx_14_0_arm64.whl
bd33f82e95ba7ad632bc57837ee99dba3d7e006536200c4e9124089e1bf42426  numpy-2.1.2-cp312-cp312-macosx_14_0_x86_64.whl
1b8cde4f11f0a975d1fd59373b32e2f5a562ade7cde4f85b7137f3de8fbb29a0  numpy-2.1.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
6d95f286b8244b3649b477ac066c6906fbb2905f8ac19b170e2175d3d799f4df  numpy-2.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
ab4754d432e3ac42d33a269c8567413bdb541689b02d93788af4131018cbf366  numpy-2.1.2-cp312-cp312-musllinux_1_1_x86_64.whl
e585c8ae871fd38ac50598f4763d73ec5497b0de9a0ab4ef5b69f01c6a046142  numpy-2.1.2-cp312-cp312-musllinux_1_2_aarch64.whl
9c6c754df29ce6a89ed23afb25550d1c2d5fdb9901d9c67a16e0b16eaf7e2550  numpy-2.1.2-cp312-cp312-win32.whl
456e3b11cb79ac9946c822a56346ec80275eaf2950314b249b512896c0d2505e  numpy-2.1.2-cp312-cp312-win_amd64.whl
a84498e0d0a1174f2b3ed769b67b656aa5460c92c9554039e11f20a05650f00d  numpy-2.1.2-cp313-cp313-macosx_10_13_x86_64.whl
4d6ec0d4222e8ffdab1744da2560f07856421b367928026fb540e1945f2eeeaf  numpy-2.1.2-cp313-cp313-macosx_11_0_arm64.whl
259ec80d54999cc34cd1eb8ded513cb053c3bf4829152a2e00de2371bd406f5e  numpy-2.1.2-cp313-cp313-macosx_14_0_arm64.whl
675c741d4739af2dc20cd6c6a5c4b7355c728167845e3c6b0e824e4e5d36a6c3  numpy-2.1.2-cp313-cp313-macosx_14_0_x86_64.whl
05b2d4e667895cc55e3ff2b56077e4c8a5604361fc21a042845ea3ad67465aa8  numpy-2.1.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
43cca367bf94a14aca50b89e9bc2061683116cfe864e56740e083392f533ce7a  numpy-2.1.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
76322dcdb16fccf2ac56f99048af32259dcc488d9b7e25b51e5eca5147a3fb98  numpy-2.1.2-cp313-cp313-musllinux_1_1_x86_64.whl
32e16a03138cabe0cb28e1007ee82264296ac0983714094380b408097a418cfe  numpy-2.1.2-cp313-cp313-musllinux_1_2_aarch64.whl
242b39d00e4944431a3cd2db2f5377e15b5785920421993770cddb89992c3f3a  numpy-2.1.2-cp313-cp313-win32.whl
f2ded8d9b6f68cc26f8425eda5d3877b47343e68ca23d0d0846f4d312ecaa445  numpy-2.1.2-cp313-cp313-win_amd64.whl
2ffef621c14ebb0188a8633348504a35c13680d6da93ab5cb86f4e54b7e922b5  numpy-2.1.2-cp313-cp313t-macosx_10_13_x86_64.whl
ad369ed238b1959dfbade9018a740fb9392c5ac4f9b5173f420bd4f37ba1f7a0  numpy-2.1.2-cp313-cp313t-macosx_11_0_arm64.whl
d82075752f40c0ddf57e6e02673a17f6cb0f8eb3f587f63ca1eaab5594da5b17  numpy-2.1.2-cp313-cp313t-macosx_14_0_arm64.whl
1600068c262af1ca9580a527d43dc9d959b0b1d8e56f8a05d830eea39b7c8af6  numpy-2.1.2-cp313-cp313t-macosx_14_0_x86_64.whl
a26ae94658d3ba3781d5e103ac07a876b3e9b29db53f68ed7df432fd033358a8  numpy-2.1.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
13311c2db4c5f7609b462bc0f43d3c465424d25c626d95040f073e30f7570e35  numpy-2.1.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
2abbf905a0b568706391ec6fa15161fad0fb5d8b68d73c461b3c1bab6064dd62  numpy-2.1.2-cp313-cp313t-musllinux_1_1_x86_64.whl
ef444c57d664d35cac4e18c298c47d7b504c66b17c2ea91312e979fcfbdfb08a  numpy-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl
bdd407c40483463898b84490770199d5714dcc9dd9b792f6c6caccc523c00952  numpy-2.1.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
da65fb46d4cbb75cb417cddf6ba5e7582eb7bb0b47db4b99c9fe5787ce5d91f5  numpy-2.1.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
1c193d0b0238638e6fc5f10f1b074a6993cb13b0b431f64079a509d63d3aa8b7  numpy-2.1.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
a7d80b2e904faa63068ead63107189164ca443b42dd1930299e0d1cb041cec2e  numpy-2.1.2-pp310-pypy310_pp73-win_amd64.whl
13532a088217fa624c99b843eeb54640de23b3414b14aa66d023805eb731066c  numpy-2.1.2.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://numpy.org) ([source](https://github.com/numpy/numpy), [changelog](https://numpy.org/doc/stable/release)) | patch | `==2.1.1` -> `==2.1.2` | --- ### Release Notes <details> <summary>numpy/numpy (numpy)</summary> ### [`v2.1.2`](https://github.com/numpy/numpy/releases/tag/v2.1.2): 2.1.2 (Oct 5, 2024) [Compare Source](https://github.com/numpy/numpy/compare/v2.1.1...v2.1.2) ### NumPy 2.1.2 Release Notes NumPy 2.1.2 is a maintenance release that fixes bugs and regressions discovered after the 2.1.1 release. The Python versions supported by this release are 3.10-3.13. #### Contributors A total of 11 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Charles Harris - Chris Sidebottom - Ishan Koradia + - João Eiras + - Katie Rust + - Marten van Kerkwijk - Matti Picus - Nathan Goldbaum - Peter Hawkins - Pieter Eendebak - Slava Gorloff + #### Pull requests merged A total of 14 pull requests were merged for this release. - [#&#8203;27333](https://github.com/numpy/numpy/pull/27333): MAINT: prepare 2.1.x for further development - [#&#8203;27400](https://github.com/numpy/numpy/pull/27400): BUG: apply critical sections around populating the dispatch cache - [#&#8203;27406](https://github.com/numpy/numpy/pull/27406): BUG: Stub out get_build_msvc_version if distutils.msvccompiler... - [#&#8203;27416](https://github.com/numpy/numpy/pull/27416): BUILD: fix missing include for std::ptrdiff_t for C++23 language... - [#&#8203;27433](https://github.com/numpy/numpy/pull/27433): BLD: pin setuptools to avoid breaking numpy.distutils - [#&#8203;27437](https://github.com/numpy/numpy/pull/27437): BUG: Allow unsigned shift argument for np.roll - [#&#8203;27439](https://github.com/numpy/numpy/pull/27439): BUG: Disable SVE VQSort - [#&#8203;27471](https://github.com/numpy/numpy/pull/27471): BUG: rfftn axis bug - [#&#8203;27479](https://github.com/numpy/numpy/pull/27479): BUG: Fix extra decref of PyArray_UInt8DType. - [#&#8203;27480](https://github.com/numpy/numpy/pull/27480): CI: use PyPI not scientific-python-nightly-wheels for CI doc... - [#&#8203;27481](https://github.com/numpy/numpy/pull/27481): MAINT: Check for SVE support on demand - [#&#8203;27484](https://github.com/numpy/numpy/pull/27484): BUG: initialize the promotion state to be weak - [#&#8203;27501](https://github.com/numpy/numpy/pull/27501): MAINT: Bump pypa/cibuildwheel from 2.20.0 to 2.21.2 - [#&#8203;27506](https://github.com/numpy/numpy/pull/27506): BUG: avoid segfault on bad arguments in ndarray.\__array_function\_\_ #### Checksums ##### MD5 4aae28b7919b126485c1aaccee37a6ba numpy-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl 172614423a82ef73d8752ad8a59cbafc numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl 5ee5e7a8a892cbe96ee228ca5fe7546b numpy-2.1.2-cp310-cp310-macosx_14_0_arm64.whl 9ce6f9222dfabd32e66b883f1fe015aa numpy-2.1.2-cp310-cp310-macosx_14_0_x86_64.whl 291da8bfeb7c9a3491ec35ecb2596335 numpy-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 9317d9b049f09c0193f074a6458cf79b numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 1f2c121533715d8b099d6498e4498f81 numpy-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl 2834df46e2cb2e81cbe4fd1ce9b96b4b numpy-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl cbc3ae2c176324fe2a9c04ec0aff181f numpy-2.1.2-cp310-cp310-win32.whl e4d74f9d188dc3fe7a65adf8c01e98cc numpy-2.1.2-cp310-cp310-win_amd64.whl cbcece9c21ed1daf60f3729a37b32266 numpy-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl 0e62474993ff6faca9c467f68cc16ceb numpy-2.1.2-cp311-cp311-macosx_11_0_arm64.whl 8747e85e09b2000a0af5a8226740dc92 numpy-2.1.2-cp311-cp311-macosx_14_0_arm64.whl 34e7f3591ce81926518a36c92038a056 numpy-2.1.2-cp311-cp311-macosx_14_0_x86_64.whl 0ec3e617161b42d643aaa4b8d3e477f5 numpy-2.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl e2a6a419b4672bfb4f3f6a98c0e575bb numpy-2.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 8c14b4d03fc8672e43eddd3ede89be09 numpy-2.1.2-cp311-cp311-musllinux_1_1_x86_64.whl dc183e12b24317bf210fb093da598d29 numpy-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl 4918f2c32ca3be20c7c5d8551e649757 numpy-2.1.2-cp311-cp311-win32.whl a8991919b6fae3c7a77c260f60a5e2e2 numpy-2.1.2-cp311-cp311-win_amd64.whl 879f307d16f9222c49508be5ea6491fc numpy-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl fe9dfac7bee0cff178737e1706aee61a numpy-2.1.2-cp312-cp312-macosx_11_0_arm64.whl 1f0c671db3294f4df8bffedc41a2e37f numpy-2.1.2-cp312-cp312-macosx_14_0_arm64.whl d131c4bd6ba29b05a5b7fa74e87a0506 numpy-2.1.2-cp312-cp312-macosx_14_0_x86_64.whl 8f9cca33590be334d44cc026a3716966 numpy-2.1.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 3692a9290dd430e56e1b15387c25b7af numpy-2.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 3549439284dbb1a05785b535c3de60d9 numpy-2.1.2-cp312-cp312-musllinux_1_1_x86_64.whl b9934410f20505e5c4b70974cd8fdc26 numpy-2.1.2-cp312-cp312-musllinux_1_2_aarch64.whl 96759e3380e4893b9b88d5d498d856b2 numpy-2.1.2-cp312-cp312-win32.whl f94c7405ed72a136e374ab82400fefdc numpy-2.1.2-cp312-cp312-win_amd64.whl 2ea775cb4da02f39edf3089af60bddd5 numpy-2.1.2-cp313-cp313-macosx_10_13_x86_64.whl 354d0970154dd002573f4291e0e9de76 numpy-2.1.2-cp313-cp313-macosx_11_0_arm64.whl bbfee75640b337e12f894d0b54727d66 numpy-2.1.2-cp313-cp313-macosx_14_0_arm64.whl a443fff50571df87f687ad55c9060d25 numpy-2.1.2-cp313-cp313-macosx_14_0_x86_64.whl 9f8cd7de5b5aa5ad8ba52608a4b0a3b8 numpy-2.1.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl c198fe3deaa77fb94d15284b4e26b875 numpy-2.1.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 0a59171c983fc2d8ea599bdf382c3d6a numpy-2.1.2-cp313-cp313-musllinux_1_1_x86_64.whl 5ba974cd59fb8c9fc94787c754a5f636 numpy-2.1.2-cp313-cp313-musllinux_1_2_aarch64.whl 93d5c642606fe8abeff0e6db31ebe88f numpy-2.1.2-cp313-cp313-win32.whl f6455bb4311ddde071a5ea2e14016003 numpy-2.1.2-cp313-cp313-win_amd64.whl d2a21857c924d4b1b3c8ae8a9e9b9bb4 numpy-2.1.2-cp313-cp313t-macosx_10_13_x86_64.whl cd6afcbd05835255750a2fba6012c565 numpy-2.1.2-cp313-cp313t-macosx_11_0_arm64.whl d2fab663ea84f1cfe13dfc00dae74fb6 numpy-2.1.2-cp313-cp313t-macosx_14_0_arm64.whl 9477b923000d63617324c487a4ce0e28 numpy-2.1.2-cp313-cp313t-macosx_14_0_x86_64.whl 84b621a2c9a8c077bc9c471abd2b3933 numpy-2.1.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl b1c341c7192d03e8f0f5e7c4b9b6f894 numpy-2.1.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl b59750ea55cf274854f64109bf67a112 numpy-2.1.2-cp313-cp313t-musllinux_1_1_x86_64.whl 33f4d63f81ad85c1ea873197f2189d89 numpy-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl f26a9ac42953c84c94f8203b2dbc61c0 numpy-2.1.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl e7cf2857582d507dfa3e8644dd3562a6 numpy-2.1.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl 9e3d44cb302c629c00fde8f25809b04d numpy-2.1.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 3f97ee2d9962cf9d84624f725bdd2a8f numpy-2.1.2-pp310-pypy310_pp73-win_amd64.whl 3d92e07d34f60dbac6b82a0982a98757 numpy-2.1.2.tar.gz ##### SHA256 30d53720b726ec36a7f88dc873f0eec8447fbc93d93a8f079dfac2629598d6ee numpy-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl e8d3ca0a72dd8846eb6f7dfe8f19088060fcb76931ed592d29128e0219652884 numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl fc44e3c68ff00fd991b59092a54350e6e4911152682b4782f68070985aa9e648 numpy-2.1.2-cp310-cp310-macosx_14_0_arm64.whl 7c1c60328bd964b53f8b835df69ae8198659e2b9302ff9ebb7de4e5a5994db3d numpy-2.1.2-cp310-cp310-macosx_14_0_x86_64.whl 6cdb606a7478f9ad91c6283e238544451e3a95f30fb5467fbf715964341a8a86 numpy-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl d666cb72687559689e9906197e3bec7b736764df6a2e58ee265e360663e9baf7 numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl c6eef7a2dbd0abfb0d9eaf78b73017dbfd0b54051102ff4e6a7b2980d5ac1a03 numpy-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl 12edb90831ff481f7ef5f6bc6431a9d74dc0e5ff401559a71e5e4611d4f2d466 numpy-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl a65acfdb9c6ebb8368490dbafe83c03c7e277b37e6857f0caeadbbc56e12f4fb numpy-2.1.2-cp310-cp310-win32.whl 860ec6e63e2c5c2ee5e9121808145c7bf86c96cca9ad396c0bd3e0f2798ccbe2 numpy-2.1.2-cp310-cp310-win_amd64.whl b42a1a511c81cc78cbc4539675713bbcf9d9c3913386243ceff0e9429ca892fe numpy-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl faa88bc527d0f097abdc2c663cddf37c05a1c2f113716601555249805cf573f1 numpy-2.1.2-cp311-cp311-macosx_11_0_arm64.whl c82af4b2ddd2ee72d1fc0c6695048d457e00b3582ccde72d8a1c991b808bb20f numpy-2.1.2-cp311-cp311-macosx_14_0_arm64.whl 13602b3174432a35b16c4cfb5de9a12d229727c3dd47a6ce35111f2ebdf66ff4 numpy-2.1.2-cp311-cp311-macosx_14_0_x86_64.whl 1ebec5fd716c5a5b3d8dfcc439be82a8407b7b24b230d0ad28a81b61c2f4659a numpy-2.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl e2b49c3c0804e8ecb05d59af8386ec2f74877f7ca8fd9c1e00be2672e4d399b1 numpy-2.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 2cbba4b30bf31ddbe97f1c7205ef976909a93a66bb1583e983adbd155ba72ac2 numpy-2.1.2-cp311-cp311-musllinux_1_1_x86_64.whl 8e00ea6fc82e8a804433d3e9cedaa1051a1422cb6e443011590c14d2dea59146 numpy-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl 5006b13a06e0b38d561fab5ccc37581f23c9511879be7693bd33c7cd15ca227c numpy-2.1.2-cp311-cp311-win32.whl f1eb068ead09f4994dec71c24b2844f1e4e4e013b9629f812f292f04bd1510d9 numpy-2.1.2-cp311-cp311-win_amd64.whl d7bf0a4f9f15b32b5ba53147369e94296f5fffb783db5aacc1be15b4bf72f43b numpy-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl b1d0fcae4f0949f215d4632be684a539859b295e2d0cb14f78ec231915d644db numpy-2.1.2-cp312-cp312-macosx_11_0_arm64.whl f751ed0a2f250541e19dfca9f1eafa31a392c71c832b6bb9e113b10d050cb0f1 numpy-2.1.2-cp312-cp312-macosx_14_0_arm64.whl bd33f82e95ba7ad632bc57837ee99dba3d7e006536200c4e9124089e1bf42426 numpy-2.1.2-cp312-cp312-macosx_14_0_x86_64.whl 1b8cde4f11f0a975d1fd59373b32e2f5a562ade7cde4f85b7137f3de8fbb29a0 numpy-2.1.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 6d95f286b8244b3649b477ac066c6906fbb2905f8ac19b170e2175d3d799f4df numpy-2.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl ab4754d432e3ac42d33a269c8567413bdb541689b02d93788af4131018cbf366 numpy-2.1.2-cp312-cp312-musllinux_1_1_x86_64.whl e585c8ae871fd38ac50598f4763d73ec5497b0de9a0ab4ef5b69f01c6a046142 numpy-2.1.2-cp312-cp312-musllinux_1_2_aarch64.whl 9c6c754df29ce6a89ed23afb25550d1c2d5fdb9901d9c67a16e0b16eaf7e2550 numpy-2.1.2-cp312-cp312-win32.whl 456e3b11cb79ac9946c822a56346ec80275eaf2950314b249b512896c0d2505e numpy-2.1.2-cp312-cp312-win_amd64.whl a84498e0d0a1174f2b3ed769b67b656aa5460c92c9554039e11f20a05650f00d numpy-2.1.2-cp313-cp313-macosx_10_13_x86_64.whl 4d6ec0d4222e8ffdab1744da2560f07856421b367928026fb540e1945f2eeeaf numpy-2.1.2-cp313-cp313-macosx_11_0_arm64.whl 259ec80d54999cc34cd1eb8ded513cb053c3bf4829152a2e00de2371bd406f5e numpy-2.1.2-cp313-cp313-macosx_14_0_arm64.whl 675c741d4739af2dc20cd6c6a5c4b7355c728167845e3c6b0e824e4e5d36a6c3 numpy-2.1.2-cp313-cp313-macosx_14_0_x86_64.whl 05b2d4e667895cc55e3ff2b56077e4c8a5604361fc21a042845ea3ad67465aa8 numpy-2.1.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 43cca367bf94a14aca50b89e9bc2061683116cfe864e56740e083392f533ce7a numpy-2.1.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 76322dcdb16fccf2ac56f99048af32259dcc488d9b7e25b51e5eca5147a3fb98 numpy-2.1.2-cp313-cp313-musllinux_1_1_x86_64.whl 32e16a03138cabe0cb28e1007ee82264296ac0983714094380b408097a418cfe numpy-2.1.2-cp313-cp313-musllinux_1_2_aarch64.whl 242b39d00e4944431a3cd2db2f5377e15b5785920421993770cddb89992c3f3a numpy-2.1.2-cp313-cp313-win32.whl f2ded8d9b6f68cc26f8425eda5d3877b47343e68ca23d0d0846f4d312ecaa445 numpy-2.1.2-cp313-cp313-win_amd64.whl 2ffef621c14ebb0188a8633348504a35c13680d6da93ab5cb86f4e54b7e922b5 numpy-2.1.2-cp313-cp313t-macosx_10_13_x86_64.whl ad369ed238b1959dfbade9018a740fb9392c5ac4f9b5173f420bd4f37ba1f7a0 numpy-2.1.2-cp313-cp313t-macosx_11_0_arm64.whl d82075752f40c0ddf57e6e02673a17f6cb0f8eb3f587f63ca1eaab5594da5b17 numpy-2.1.2-cp313-cp313t-macosx_14_0_arm64.whl 1600068c262af1ca9580a527d43dc9d959b0b1d8e56f8a05d830eea39b7c8af6 numpy-2.1.2-cp313-cp313t-macosx_14_0_x86_64.whl a26ae94658d3ba3781d5e103ac07a876b3e9b29db53f68ed7df432fd033358a8 numpy-2.1.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 13311c2db4c5f7609b462bc0f43d3c465424d25c626d95040f073e30f7570e35 numpy-2.1.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 2abbf905a0b568706391ec6fa15161fad0fb5d8b68d73c461b3c1bab6064dd62 numpy-2.1.2-cp313-cp313t-musllinux_1_1_x86_64.whl ef444c57d664d35cac4e18c298c47d7b504c66b17c2ea91312e979fcfbdfb08a numpy-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl bdd407c40483463898b84490770199d5714dcc9dd9b792f6c6caccc523c00952 numpy-2.1.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl da65fb46d4cbb75cb417cddf6ba5e7582eb7bb0b47db4b99c9fe5787ce5d91f5 numpy-2.1.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl 1c193d0b0238638e6fc5f10f1b074a6993cb13b0b431f64079a509d63d3aa8b7 numpy-2.1.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl a7d80b2e904faa63068ead63107189164ca443b42dd1930299e0d1cb041cec2e numpy-2.1.2-pp310-pypy310_pp73-win_amd64.whl 13532a088217fa624c99b843eeb54640de23b3414b14aa66d023805eb731066c numpy-2.1.2.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:eyJjcmVhdGVkSW5WZXIiOiIzOC42NC4yIiwidXBkYXRlZEluVmVyIjoiMzguNjQuMiIsInRhcmdldEJyYW5jaCI6Im1haW4iLCJsYWJlbHMiOltdfQ==-->
renovate_bot added 1 commit 2024-10-05 12:00:17 -07:00
Update dependency numpy to v2.1.2
Some checks failed
ci/woodpecker/pr/lint Pipeline was successful
ci/woodpecker/pr/vulnerability-scan Pipeline was successful
ci/woodpecker/pull_request_closed/lint Pipeline was successful
ci/woodpecker/pull_request_closed/vulnerability-scan Pipeline failed
ci/woodpecker/push/lint Pipeline was successful
ci/woodpecker/push/vulnerability-scan Pipeline was successful
8649c2476f
renovate_bot scheduled this pull request to auto merge when all checks succeed 2024-10-05 12:00:17 -07:00
renovate_bot merged commit 8649c2476f into main 2024-10-05 12:00:43 -07:00
Sign in to join this conversation.
No reviewers
No labels
No milestone
No project
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#59
No description provided.