Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat(Dependencies): Update dependency numpy to v2.1.3 - abandoned #78

Open
wants to merge 1 commit into
base: dev
Choose a base branch
from

Conversation

renovate[bot]
Copy link
Contributor

@renovate renovate bot commented Sep 3, 2024

This PR contains the following updates:

Package Change Age Adoption Passing Confidence
numpy (source, changelog) ==2.1.0 -> ==2.1.3 age adoption passing confidence

Release Notes

numpy/numpy (numpy)

v2.1.3

Compare Source

v2.1.2

Compare Source

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 is behind base branch, 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 was generated by Mend Renovate. View the repository job log.

@renovate renovate bot force-pushed the deps/numpy-2.1.x branch from 51cf6c8 to b2f32c1 Compare October 5, 2024 18:52
@renovate renovate bot changed the title feat(Dependencies): Update dependency numpy to v2.1.1 feat(Dependencies): Update dependency numpy to v2.1.2 Oct 5, 2024
@renovate renovate bot changed the title feat(Dependencies): Update dependency numpy to v2.1.2 feat(Dependencies): Update dependency numpy to v2.1.3 Nov 2, 2024
@renovate renovate bot force-pushed the deps/numpy-2.1.x branch from b2f32c1 to ce59ac7 Compare November 2, 2024 18:05
| datasource | package | from  | to    |
| ---------- | ------- | ----- | ----- |
| pypi       | numpy   | 2.1.0 | 2.1.3 |
@renovate renovate bot force-pushed the deps/numpy-2.1.x branch from ce59ac7 to fe19950 Compare December 18, 2024 10:43
@renovate renovate bot changed the title feat(Dependencies): Update dependency numpy to v2.1.3 feat(Dependencies): Update dependency numpy to v2.1.3 - abandoned Dec 18, 2024
Copy link
Contributor Author

renovate bot commented Dec 18, 2024

Autoclosing Skipped

This PR has been flagged for autoclosing. However, it is being skipped due to the branch being already modified. Please close/delete it manually or report a bug if you think this is in error.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants