Update dependency numpy to v2.1.1 #54

Merged
renovate_bot merged 1 commit from renovate/numpy-2.x into main 2024-09-20 07:01:29 -07:00
Collaborator

This PR contains the following updates:

Package Update Change
numpy (source, changelog) patch ==2.1.0 -> ==2.1.1

Release Notes

numpy/numpy (numpy)

v2.1.1: 2.1.1 (Sep 3, 2024)

Compare Source

NumPy 2.1.1 Release Notes

NumPy 2.1.1 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.0 release.

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

Contributors

A total of 7 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Andrew Nelson
  • Charles Harris
  • Mateusz Sokół
  • Maximilian Weigand +
  • Nathan Goldbaum
  • Pieter Eendebak
  • Sebastian Berg

Pull requests merged

A total of 10 pull requests were merged for this release.

  • #​27236: REL: Prepare for the NumPy 2.1.0 release [wheel build]
  • #​27252: MAINT: prepare 2.1.x for further development
  • #​27259: BUG: revert unintended change in the return value of set_printoptions
  • #​27266: BUG: fix reference counting bug in __array_interface__ implementation...
  • #​27267: TST: Add regression test for missing descr in array-interface
  • #​27276: BUG: Fix #​27256 and #​27257
  • #​27278: BUG: Fix array_equal for numeric and non-numeric scalar types
  • #​27287: MAINT: Update maintenance/2.1.x after the 2.0.2 release
  • #​27303: BLD: cp311- macosx_arm64 wheels [wheel build]
  • #​27304: BUG: f2py: better handle filtering of public/private subroutines

Checksums

MD5
3053a97400db800b7377749e691eb39e  numpy-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl
84b752a2220dce7c96ff89eef4f4aec3  numpy-2.1.1-cp310-cp310-macosx_11_0_arm64.whl
47ed4f704a64261f07ca24ef2e674524  numpy-2.1.1-cp310-cp310-macosx_14_0_arm64.whl
b8a45caa870aee980c298053cf064d28  numpy-2.1.1-cp310-cp310-macosx_14_0_x86_64.whl
e097ad5eee572b791b4a25eedad6df4a  numpy-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
ae502c99315884cda7f0236a07c035c4  numpy-2.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
841a859d975c55090c0b60b72aab93a3  numpy-2.1.1-cp310-cp310-musllinux_1_1_x86_64.whl
d51be2b17f5b87aac64ab80fdfafc85e  numpy-2.1.1-cp310-cp310-musllinux_1_2_aarch64.whl
1f8249bd725397c6233fe6a0e8ad18b1  numpy-2.1.1-cp310-cp310-win32.whl
d38d6f06589c1ec104a6a31ff6035781  numpy-2.1.1-cp310-cp310-win_amd64.whl
6a18fe3029aae00986975250313bf16f  numpy-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl
5b0b3aa01fbd0b5a8b0f354bb878351e  numpy-2.1.1-cp311-cp311-macosx_11_0_arm64.whl
1c492dad399abe7b97274b4c6c12ae53  numpy-2.1.1-cp311-cp311-macosx_14_0_arm64.whl
4d55d91e71b62eb5fa6561c606524f60  numpy-2.1.1-cp311-cp311-macosx_14_0_x86_64.whl
88e99ecd063c178f25bc08d20792a9bf  numpy-2.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
f3c8b0e4fb059b9219e8ec86d9fda861  numpy-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
df632b5fed7eb78d39e7194d2475c19b  numpy-2.1.1-cp311-cp311-musllinux_1_1_x86_64.whl
65499daccdb178d26e322d9f359cf146  numpy-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl
eb97327fd7aa6027e2409d0dcca1129a  numpy-2.1.1-cp311-cp311-win32.whl
9e4b05b38cbff22c2bdfead528b9d2bc  numpy-2.1.1-cp311-cp311-win_amd64.whl
6b8a359bb865b5c624fd9ffc848393e1  numpy-2.1.1-cp312-cp312-macosx_10_9_x86_64.whl
eaf8dce312efa2b0f17ad46612fb1681  numpy-2.1.1-cp312-cp312-macosx_11_0_arm64.whl
c861ff048b336284fe7c0791b1a6b0b4  numpy-2.1.1-cp312-cp312-macosx_14_0_arm64.whl
7e1befccfe729dc5d6c450a5fb6b801c  numpy-2.1.1-cp312-cp312-macosx_14_0_x86_64.whl
ea0a401ef653a167221987a10cbef260  numpy-2.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
97326ac792d26f2e536a519c82f2d6bc  numpy-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
fdd2a82232c03d11bbc7cec0a8e01ab0  numpy-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl
0d6716e9a7b2c0d6e5ace9c01b9bca01  numpy-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl
ba589ed2a79c88187c3b8574ae72a1c7  numpy-2.1.1-cp312-cp312-win32.whl
806ca7c1e2a2013b786edbb619f6da47  numpy-2.1.1-cp312-cp312-win_amd64.whl
647665353e5af5884df4e51610990c22  numpy-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl
bfd3b3c5c4616ef99d917bd94d39114a  numpy-2.1.1-cp313-cp313-macosx_11_0_arm64.whl
cb989095f9c74e3b32250a984390faeb  numpy-2.1.1-cp313-cp313-macosx_14_0_arm64.whl
55ad7548e58f61b9a4f91749e36d237f  numpy-2.1.1-cp313-cp313-macosx_14_0_x86_64.whl
5bc73d67dd1032524bfd36ef877b09e4  numpy-2.1.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
c7dfb09db8284cb75296f708c3f77ea3  numpy-2.1.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
7cf90ce1b844a97aeea1a5b8c71fb49b  numpy-2.1.1-cp313-cp313-musllinux_1_1_x86_64.whl
6ec8baeac5f979a3b98017679d457bbc  numpy-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl
1f198cb5210c76faae81359a83d58230  numpy-2.1.1-cp313-cp313-win32.whl
1766258213ad41f7e36f2209ee6d2a30  numpy-2.1.1-cp313-cp313-win_amd64.whl
f0a7a0456308dbeb739ad886f1632f16  numpy-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl
302c9cf7b4aa695974500ee1935a92c9  numpy-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl
f4aa7d784992abb9bd9fe9db09c01c06  numpy-2.1.1-cp313-cp313t-macosx_14_0_arm64.whl
3bb4ae9906499609769f1774438149a5  numpy-2.1.1-cp313-cp313t-macosx_14_0_x86_64.whl
ff6b9e1993d3d540074736014b1d13af  numpy-2.1.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
749489c091ee9c00abf1ad1ef822c3ca  numpy-2.1.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
32d2daf4064031f365ced5036757ad8b  numpy-2.1.1-cp313-cp313t-musllinux_1_1_x86_64.whl
603dfe4ef56c01e1fc0dcc9d5e3090ed  numpy-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl
70fa2d3b78633bb6061c90e17364f27f  numpy-2.1.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
9a430be5d14b689ed051eccc540dfbdc  numpy-2.1.1-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
7291ff124e471d32c03464da18ff108d  numpy-2.1.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e56ce141724af119c7c647a8705827a5  numpy-2.1.1-pp310-pypy310_pp73-win_amd64.whl
f63b4750618bfa5490f10cae37fde998  numpy-2.1.1.tar.gz
SHA256
c8a0e34993b510fc19b9a2ce7f31cb8e94ecf6e924a40c0c9dd4f62d0aac47d9  numpy-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl
7dd86dfaf7c900c0bbdcb8b16e2f6ddf1eb1fe39c6c8cca6e94844ed3152a8fd  numpy-2.1.1-cp310-cp310-macosx_11_0_arm64.whl
5889dd24f03ca5a5b1e8a90a33b5a0846d8977565e4ae003a63d22ecddf6782f  numpy-2.1.1-cp310-cp310-macosx_14_0_arm64.whl
59ca673ad11d4b84ceb385290ed0ebe60266e356641428c845b39cd9df6713ab  numpy-2.1.1-cp310-cp310-macosx_14_0_x86_64.whl
13ce49a34c44b6de5241f0b38b07e44c1b2dcacd9e36c30f9c2fcb1bb5135db7  numpy-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
913cc1d311060b1d409e609947fa1b9753701dac96e6581b58afc36b7ee35af6  numpy-2.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
caf5d284ddea7462c32b8d4a6b8af030b6c9fd5332afb70e7414d7fdded4bfd0  numpy-2.1.1-cp310-cp310-musllinux_1_1_x86_64.whl
57eb525e7c2a8fdee02d731f647146ff54ea8c973364f3b850069ffb42799647  numpy-2.1.1-cp310-cp310-musllinux_1_2_aarch64.whl
9a8e06c7a980869ea67bbf551283bbed2856915f0a792dc32dd0f9dd2fb56728  numpy-2.1.1-cp310-cp310-win32.whl
d10c39947a2d351d6d466b4ae83dad4c37cd6c3cdd6d5d0fa797da56f710a6ae  numpy-2.1.1-cp310-cp310-win_amd64.whl
0d07841fd284718feffe7dd17a63a2e6c78679b2d386d3e82f44f0108c905550  numpy-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl
b5613cfeb1adfe791e8e681128f5f49f22f3fcaa942255a6124d58ca59d9528f  numpy-2.1.1-cp311-cp311-macosx_11_0_arm64.whl
0b8cc2715a84b7c3b161f9ebbd942740aaed913584cae9cdc7f8ad5ad41943d0  numpy-2.1.1-cp311-cp311-macosx_14_0_arm64.whl
b49742cdb85f1f81e4dc1b39dcf328244f4d8d1ded95dea725b316bd2cf18c95  numpy-2.1.1-cp311-cp311-macosx_14_0_x86_64.whl
e8d5f8a8e3bc87334f025194c6193e408903d21ebaeb10952264943a985066ca  numpy-2.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d51fc141ddbe3f919e91a096ec739f49d686df8af254b2053ba21a910ae518bf  numpy-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
98ce7fb5b8063cfdd86596b9c762bf2b5e35a2cdd7e967494ab78a1fa7f8b86e  numpy-2.1.1-cp311-cp311-musllinux_1_1_x86_64.whl
24c2ad697bd8593887b019817ddd9974a7f429c14a5469d7fad413f28340a6d2  numpy-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl
397bc5ce62d3fb73f304bec332171535c187e0643e176a6e9421a6e3eacef06d  numpy-2.1.1-cp311-cp311-win32.whl
ae8ce252404cdd4de56dcfce8b11eac3c594a9c16c231d081fb705cf23bd4d9e  numpy-2.1.1-cp311-cp311-win_amd64.whl
7c803b7934a7f59563db459292e6aa078bb38b7ab1446ca38dd138646a38203e  numpy-2.1.1-cp312-cp312-macosx_10_9_x86_64.whl
6435c48250c12f001920f0751fe50c0348f5f240852cfddc5e2f97e007544cbe  numpy-2.1.1-cp312-cp312-macosx_11_0_arm64.whl
3269c9eb8745e8d975980b3a7411a98976824e1fdef11f0aacf76147f662b15f  numpy-2.1.1-cp312-cp312-macosx_14_0_arm64.whl
fac6e277a41163d27dfab5f4ec1f7a83fac94e170665a4a50191b545721c6521  numpy-2.1.1-cp312-cp312-macosx_14_0_x86_64.whl
fcd8f556cdc8cfe35e70efb92463082b7f43dd7e547eb071ffc36abc0ca4699b  numpy-2.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d2b9cd92c8f8e7b313b80e93cedc12c0112088541dcedd9197b5dee3738c1201  numpy-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
afd9c680df4de71cd58582b51e88a61feed4abcc7530bcd3d48483f20fc76f2a  numpy-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl
8661c94e3aad18e1ea17a11f60f843a4933ccaf1a25a7c6a9182af70610b2313  numpy-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl
950802d17a33c07cba7fd7c3dcfa7d64705509206be1606f196d179e539111ed  numpy-2.1.1-cp312-cp312-win32.whl
3fc5eabfc720db95d68e6646e88f8b399bfedd235994016351b1d9e062c4b270  numpy-2.1.1-cp312-cp312-win_amd64.whl
046356b19d7ad1890c751b99acad5e82dc4a02232013bd9a9a712fddf8eb60f5  numpy-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl
6e5a9cb2be39350ae6c8f79410744e80154df658d5bea06e06e0ac5bb75480d5  numpy-2.1.1-cp313-cp313-macosx_11_0_arm64.whl
d4c57b68c8ef5e1ebf47238e99bf27657511ec3f071c465f6b1bccbef12d4136  numpy-2.1.1-cp313-cp313-macosx_14_0_arm64.whl
8ae0fd135e0b157365ac7cc31fff27f07a5572bdfc38f9c2d43b2aff416cc8b0  numpy-2.1.1-cp313-cp313-macosx_14_0_x86_64.whl
981707f6b31b59c0c24bcda52e5605f9701cb46da4b86c2e8023656ad3e833cb  numpy-2.1.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2ca4b53e1e0b279142113b8c5eb7d7a877e967c306edc34f3b58e9be12fda8df  numpy-2.1.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e097507396c0be4e547ff15b13dc3866f45f3680f789c1a1301b07dadd3fbc78  numpy-2.1.1-cp313-cp313-musllinux_1_1_x86_64.whl
f7506387e191fe8cdb267f912469a3cccc538ab108471291636a96a54e599556  numpy-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl
251105b7c42abe40e3a689881e1793370cc9724ad50d64b30b358bbb3a97553b  numpy-2.1.1-cp313-cp313-win32.whl
f212d4f46b67ff604d11fff7cc62d36b3e8714edf68e44e9760e19be38c03eb0  numpy-2.1.1-cp313-cp313-win_amd64.whl
920b0911bb2e4414c50e55bd658baeb78281a47feeb064ab40c2b66ecba85553  numpy-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl
bab7c09454460a487e631ffc0c42057e3d8f2a9ddccd1e60c7bb8ed774992480  numpy-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl
cea427d1350f3fd0d2818ce7350095c1a2ee33e30961d2f0fef48576ddbbe90f  numpy-2.1.1-cp313-cp313t-macosx_14_0_arm64.whl
e30356d530528a42eeba51420ae8bf6c6c09559051887196599d96ee5f536468  numpy-2.1.1-cp313-cp313t-macosx_14_0_x86_64.whl
e8dfa9e94fc127c40979c3eacbae1e61fda4fe71d84869cc129e2721973231ef  numpy-2.1.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
910b47a6d0635ec1bd53b88f86120a52bf56dcc27b51f18c7b4a2e2224c29f0f  numpy-2.1.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
13cc11c00000848702322af4de0147ced365c81d66053a67c2e962a485b3717c  numpy-2.1.1-cp313-cp313t-musllinux_1_1_x86_64.whl
53e27293b3a2b661c03f79aa51c3987492bd4641ef933e366e0f9f6c9bf257ec  numpy-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl
7be6a07520b88214ea85d8ac8b7d6d8a1839b0b5cb87412ac9f49fa934eb15d5  numpy-2.1.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
52ac2e48f5ad847cd43c4755520a2317f3380213493b9d8a4c5e37f3b87df504  numpy-2.1.1-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
50a95ca3560a6058d6ea91d4629a83a897ee27c00630aed9d933dff191f170cd  numpy-2.1.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
99f4a9ee60eed1385a86e82288971a51e71df052ed0b2900ed30bc840c0f2e39  numpy-2.1.1-pp310-pypy310_pp73-win_amd64.whl
d0cf7d55b1051387807405b3898efafa862997b4cba8aa5dbe657be794afeafd  numpy-2.1.1.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 | `==2.1.0` -> `==2.1.1` | --- ### Release Notes <details> <summary>numpy/numpy (numpy)</summary> ### [`v2.1.1`](https://github.com/numpy/numpy/releases/tag/v2.1.1): 2.1.1 (Sep 3, 2024) [Compare Source](https://github.com/numpy/numpy/compare/v2.1.0...v2.1.1) ### NumPy 2.1.1 Release Notes NumPy 2.1.1 is a maintenance release that fixes bugs and regressions discovered after the 2.1.0 release. The Python versions supported by this release are 3.10-3.13. #### Contributors A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Andrew Nelson - Charles Harris - Mateusz Sokół - Maximilian Weigand + - Nathan Goldbaum - Pieter Eendebak - Sebastian Berg #### Pull requests merged A total of 10 pull requests were merged for this release. - [#&#8203;27236](https://github.com/numpy/numpy/pull/27236): REL: Prepare for the NumPy 2.1.0 release \[wheel build] - [#&#8203;27252](https://github.com/numpy/numpy/pull/27252): MAINT: prepare 2.1.x for further development - [#&#8203;27259](https://github.com/numpy/numpy/pull/27259): BUG: revert unintended change in the return value of set_printoptions - [#&#8203;27266](https://github.com/numpy/numpy/pull/27266): BUG: fix reference counting bug in \__array_interface\_\_ implementation... - [#&#8203;27267](https://github.com/numpy/numpy/pull/27267): TST: Add regression test for missing descr in array-interface - [#&#8203;27276](https://github.com/numpy/numpy/pull/27276): BUG: Fix [#&#8203;27256](https://github.com/numpy/numpy/issues/27256) and [#&#8203;27257](https://github.com/numpy/numpy/issues/27257) - [#&#8203;27278](https://github.com/numpy/numpy/pull/27278): BUG: Fix array_equal for numeric and non-numeric scalar types - [#&#8203;27287](https://github.com/numpy/numpy/pull/27287): MAINT: Update maintenance/2.1.x after the 2.0.2 release - [#&#8203;27303](https://github.com/numpy/numpy/pull/27303): BLD: cp311- macosx_arm64 wheels \[wheel build] - [#&#8203;27304](https://github.com/numpy/numpy/pull/27304): BUG: f2py: better handle filtering of public/private subroutines #### Checksums ##### MD5 3053a97400db800b7377749e691eb39e numpy-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl 84b752a2220dce7c96ff89eef4f4aec3 numpy-2.1.1-cp310-cp310-macosx_11_0_arm64.whl 47ed4f704a64261f07ca24ef2e674524 numpy-2.1.1-cp310-cp310-macosx_14_0_arm64.whl b8a45caa870aee980c298053cf064d28 numpy-2.1.1-cp310-cp310-macosx_14_0_x86_64.whl e097ad5eee572b791b4a25eedad6df4a numpy-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl ae502c99315884cda7f0236a07c035c4 numpy-2.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 841a859d975c55090c0b60b72aab93a3 numpy-2.1.1-cp310-cp310-musllinux_1_1_x86_64.whl d51be2b17f5b87aac64ab80fdfafc85e numpy-2.1.1-cp310-cp310-musllinux_1_2_aarch64.whl 1f8249bd725397c6233fe6a0e8ad18b1 numpy-2.1.1-cp310-cp310-win32.whl d38d6f06589c1ec104a6a31ff6035781 numpy-2.1.1-cp310-cp310-win_amd64.whl 6a18fe3029aae00986975250313bf16f numpy-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl 5b0b3aa01fbd0b5a8b0f354bb878351e numpy-2.1.1-cp311-cp311-macosx_11_0_arm64.whl 1c492dad399abe7b97274b4c6c12ae53 numpy-2.1.1-cp311-cp311-macosx_14_0_arm64.whl 4d55d91e71b62eb5fa6561c606524f60 numpy-2.1.1-cp311-cp311-macosx_14_0_x86_64.whl 88e99ecd063c178f25bc08d20792a9bf numpy-2.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl f3c8b0e4fb059b9219e8ec86d9fda861 numpy-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl df632b5fed7eb78d39e7194d2475c19b numpy-2.1.1-cp311-cp311-musllinux_1_1_x86_64.whl 65499daccdb178d26e322d9f359cf146 numpy-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl eb97327fd7aa6027e2409d0dcca1129a numpy-2.1.1-cp311-cp311-win32.whl 9e4b05b38cbff22c2bdfead528b9d2bc numpy-2.1.1-cp311-cp311-win_amd64.whl 6b8a359bb865b5c624fd9ffc848393e1 numpy-2.1.1-cp312-cp312-macosx_10_9_x86_64.whl eaf8dce312efa2b0f17ad46612fb1681 numpy-2.1.1-cp312-cp312-macosx_11_0_arm64.whl c861ff048b336284fe7c0791b1a6b0b4 numpy-2.1.1-cp312-cp312-macosx_14_0_arm64.whl 7e1befccfe729dc5d6c450a5fb6b801c numpy-2.1.1-cp312-cp312-macosx_14_0_x86_64.whl ea0a401ef653a167221987a10cbef260 numpy-2.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 97326ac792d26f2e536a519c82f2d6bc numpy-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl fdd2a82232c03d11bbc7cec0a8e01ab0 numpy-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl 0d6716e9a7b2c0d6e5ace9c01b9bca01 numpy-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl ba589ed2a79c88187c3b8574ae72a1c7 numpy-2.1.1-cp312-cp312-win32.whl 806ca7c1e2a2013b786edbb619f6da47 numpy-2.1.1-cp312-cp312-win_amd64.whl 647665353e5af5884df4e51610990c22 numpy-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl bfd3b3c5c4616ef99d917bd94d39114a numpy-2.1.1-cp313-cp313-macosx_11_0_arm64.whl cb989095f9c74e3b32250a984390faeb numpy-2.1.1-cp313-cp313-macosx_14_0_arm64.whl 55ad7548e58f61b9a4f91749e36d237f numpy-2.1.1-cp313-cp313-macosx_14_0_x86_64.whl 5bc73d67dd1032524bfd36ef877b09e4 numpy-2.1.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl c7dfb09db8284cb75296f708c3f77ea3 numpy-2.1.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 7cf90ce1b844a97aeea1a5b8c71fb49b numpy-2.1.1-cp313-cp313-musllinux_1_1_x86_64.whl 6ec8baeac5f979a3b98017679d457bbc numpy-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl 1f198cb5210c76faae81359a83d58230 numpy-2.1.1-cp313-cp313-win32.whl 1766258213ad41f7e36f2209ee6d2a30 numpy-2.1.1-cp313-cp313-win_amd64.whl f0a7a0456308dbeb739ad886f1632f16 numpy-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl 302c9cf7b4aa695974500ee1935a92c9 numpy-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl f4aa7d784992abb9bd9fe9db09c01c06 numpy-2.1.1-cp313-cp313t-macosx_14_0_arm64.whl 3bb4ae9906499609769f1774438149a5 numpy-2.1.1-cp313-cp313t-macosx_14_0_x86_64.whl ff6b9e1993d3d540074736014b1d13af numpy-2.1.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 749489c091ee9c00abf1ad1ef822c3ca numpy-2.1.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 32d2daf4064031f365ced5036757ad8b numpy-2.1.1-cp313-cp313t-musllinux_1_1_x86_64.whl 603dfe4ef56c01e1fc0dcc9d5e3090ed numpy-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl 70fa2d3b78633bb6061c90e17364f27f numpy-2.1.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl 9a430be5d14b689ed051eccc540dfbdc numpy-2.1.1-pp310-pypy310_pp73-macosx_14_0_x86_64.whl 7291ff124e471d32c03464da18ff108d numpy-2.1.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl e56ce141724af119c7c647a8705827a5 numpy-2.1.1-pp310-pypy310_pp73-win_amd64.whl f63b4750618bfa5490f10cae37fde998 numpy-2.1.1.tar.gz ##### SHA256 c8a0e34993b510fc19b9a2ce7f31cb8e94ecf6e924a40c0c9dd4f62d0aac47d9 numpy-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl 7dd86dfaf7c900c0bbdcb8b16e2f6ddf1eb1fe39c6c8cca6e94844ed3152a8fd numpy-2.1.1-cp310-cp310-macosx_11_0_arm64.whl 5889dd24f03ca5a5b1e8a90a33b5a0846d8977565e4ae003a63d22ecddf6782f numpy-2.1.1-cp310-cp310-macosx_14_0_arm64.whl 59ca673ad11d4b84ceb385290ed0ebe60266e356641428c845b39cd9df6713ab numpy-2.1.1-cp310-cp310-macosx_14_0_x86_64.whl 13ce49a34c44b6de5241f0b38b07e44c1b2dcacd9e36c30f9c2fcb1bb5135db7 numpy-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 913cc1d311060b1d409e609947fa1b9753701dac96e6581b58afc36b7ee35af6 numpy-2.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl caf5d284ddea7462c32b8d4a6b8af030b6c9fd5332afb70e7414d7fdded4bfd0 numpy-2.1.1-cp310-cp310-musllinux_1_1_x86_64.whl 57eb525e7c2a8fdee02d731f647146ff54ea8c973364f3b850069ffb42799647 numpy-2.1.1-cp310-cp310-musllinux_1_2_aarch64.whl 9a8e06c7a980869ea67bbf551283bbed2856915f0a792dc32dd0f9dd2fb56728 numpy-2.1.1-cp310-cp310-win32.whl d10c39947a2d351d6d466b4ae83dad4c37cd6c3cdd6d5d0fa797da56f710a6ae numpy-2.1.1-cp310-cp310-win_amd64.whl 0d07841fd284718feffe7dd17a63a2e6c78679b2d386d3e82f44f0108c905550 numpy-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl b5613cfeb1adfe791e8e681128f5f49f22f3fcaa942255a6124d58ca59d9528f numpy-2.1.1-cp311-cp311-macosx_11_0_arm64.whl 0b8cc2715a84b7c3b161f9ebbd942740aaed913584cae9cdc7f8ad5ad41943d0 numpy-2.1.1-cp311-cp311-macosx_14_0_arm64.whl b49742cdb85f1f81e4dc1b39dcf328244f4d8d1ded95dea725b316bd2cf18c95 numpy-2.1.1-cp311-cp311-macosx_14_0_x86_64.whl e8d5f8a8e3bc87334f025194c6193e408903d21ebaeb10952264943a985066ca numpy-2.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl d51fc141ddbe3f919e91a096ec739f49d686df8af254b2053ba21a910ae518bf numpy-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 98ce7fb5b8063cfdd86596b9c762bf2b5e35a2cdd7e967494ab78a1fa7f8b86e numpy-2.1.1-cp311-cp311-musllinux_1_1_x86_64.whl 24c2ad697bd8593887b019817ddd9974a7f429c14a5469d7fad413f28340a6d2 numpy-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl 397bc5ce62d3fb73f304bec332171535c187e0643e176a6e9421a6e3eacef06d numpy-2.1.1-cp311-cp311-win32.whl ae8ce252404cdd4de56dcfce8b11eac3c594a9c16c231d081fb705cf23bd4d9e numpy-2.1.1-cp311-cp311-win_amd64.whl 7c803b7934a7f59563db459292e6aa078bb38b7ab1446ca38dd138646a38203e numpy-2.1.1-cp312-cp312-macosx_10_9_x86_64.whl 6435c48250c12f001920f0751fe50c0348f5f240852cfddc5e2f97e007544cbe numpy-2.1.1-cp312-cp312-macosx_11_0_arm64.whl 3269c9eb8745e8d975980b3a7411a98976824e1fdef11f0aacf76147f662b15f numpy-2.1.1-cp312-cp312-macosx_14_0_arm64.whl fac6e277a41163d27dfab5f4ec1f7a83fac94e170665a4a50191b545721c6521 numpy-2.1.1-cp312-cp312-macosx_14_0_x86_64.whl fcd8f556cdc8cfe35e70efb92463082b7f43dd7e547eb071ffc36abc0ca4699b numpy-2.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl d2b9cd92c8f8e7b313b80e93cedc12c0112088541dcedd9197b5dee3738c1201 numpy-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl afd9c680df4de71cd58582b51e88a61feed4abcc7530bcd3d48483f20fc76f2a numpy-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl 8661c94e3aad18e1ea17a11f60f843a4933ccaf1a25a7c6a9182af70610b2313 numpy-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl 950802d17a33c07cba7fd7c3dcfa7d64705509206be1606f196d179e539111ed numpy-2.1.1-cp312-cp312-win32.whl 3fc5eabfc720db95d68e6646e88f8b399bfedd235994016351b1d9e062c4b270 numpy-2.1.1-cp312-cp312-win_amd64.whl 046356b19d7ad1890c751b99acad5e82dc4a02232013bd9a9a712fddf8eb60f5 numpy-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl 6e5a9cb2be39350ae6c8f79410744e80154df658d5bea06e06e0ac5bb75480d5 numpy-2.1.1-cp313-cp313-macosx_11_0_arm64.whl d4c57b68c8ef5e1ebf47238e99bf27657511ec3f071c465f6b1bccbef12d4136 numpy-2.1.1-cp313-cp313-macosx_14_0_arm64.whl 8ae0fd135e0b157365ac7cc31fff27f07a5572bdfc38f9c2d43b2aff416cc8b0 numpy-2.1.1-cp313-cp313-macosx_14_0_x86_64.whl 981707f6b31b59c0c24bcda52e5605f9701cb46da4b86c2e8023656ad3e833cb numpy-2.1.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 2ca4b53e1e0b279142113b8c5eb7d7a877e967c306edc34f3b58e9be12fda8df numpy-2.1.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl e097507396c0be4e547ff15b13dc3866f45f3680f789c1a1301b07dadd3fbc78 numpy-2.1.1-cp313-cp313-musllinux_1_1_x86_64.whl f7506387e191fe8cdb267f912469a3cccc538ab108471291636a96a54e599556 numpy-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl 251105b7c42abe40e3a689881e1793370cc9724ad50d64b30b358bbb3a97553b numpy-2.1.1-cp313-cp313-win32.whl f212d4f46b67ff604d11fff7cc62d36b3e8714edf68e44e9760e19be38c03eb0 numpy-2.1.1-cp313-cp313-win_amd64.whl 920b0911bb2e4414c50e55bd658baeb78281a47feeb064ab40c2b66ecba85553 numpy-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl bab7c09454460a487e631ffc0c42057e3d8f2a9ddccd1e60c7bb8ed774992480 numpy-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl cea427d1350f3fd0d2818ce7350095c1a2ee33e30961d2f0fef48576ddbbe90f numpy-2.1.1-cp313-cp313t-macosx_14_0_arm64.whl e30356d530528a42eeba51420ae8bf6c6c09559051887196599d96ee5f536468 numpy-2.1.1-cp313-cp313t-macosx_14_0_x86_64.whl e8dfa9e94fc127c40979c3eacbae1e61fda4fe71d84869cc129e2721973231ef numpy-2.1.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 910b47a6d0635ec1bd53b88f86120a52bf56dcc27b51f18c7b4a2e2224c29f0f numpy-2.1.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 13cc11c00000848702322af4de0147ced365c81d66053a67c2e962a485b3717c numpy-2.1.1-cp313-cp313t-musllinux_1_1_x86_64.whl 53e27293b3a2b661c03f79aa51c3987492bd4641ef933e366e0f9f6c9bf257ec numpy-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl 7be6a07520b88214ea85d8ac8b7d6d8a1839b0b5cb87412ac9f49fa934eb15d5 numpy-2.1.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl 52ac2e48f5ad847cd43c4755520a2317f3380213493b9d8a4c5e37f3b87df504 numpy-2.1.1-pp310-pypy310_pp73-macosx_14_0_x86_64.whl 50a95ca3560a6058d6ea91d4629a83a897ee27c00630aed9d933dff191f170cd numpy-2.1.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 99f4a9ee60eed1385a86e82288971a51e71df052ed0b2900ed30bc840c0f2e39 numpy-2.1.1-pp310-pypy310_pp73-win_amd64.whl d0cf7d55b1051387807405b3898efafa862997b4cba8aa5dbe657be794afeafd numpy-2.1.1.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 2024-09-20 07:00:28 -07:00
Update dependency numpy to v2.1.1
All checks were successful
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 was successful
ci/woodpecker/push/lint Pipeline was successful
ci/woodpecker/push/vulnerability-scan Pipeline was successful
f72d9260f0
renovate_bot scheduled this pull request to auto merge when all checks succeed 2024-09-20 07:00:28 -07:00
renovate_bot merged commit f72d9260f0 into main 2024-09-20 07:01:29 -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#54
No description provided.