Turbo87 / utm

Bidirectional UTM-WGS84 converter for python
http://pypi.python.org/pypi/utm
MIT License
486 stars 101 forks source link

Update dependency numpy to v1.26.4 #117

Open renovate[bot] opened 7 months ago

renovate[bot] commented 7 months ago

This PR contains the following updates:

Package Change Age Adoption Passing Confidence
numpy (source, changelog) ==1.26.3 -> ==1.26.4 age adoption passing confidence
numpy (source, changelog) ==1.24.4 -> ==1.26.4 age adoption passing confidence

Release Notes

numpy/numpy (numpy) ### [`v1.26.4`](https://togithub.com/numpy/numpy/releases/tag/v1.26.4) [Compare Source](https://togithub.com/numpy/numpy/compare/v1.26.3...v1.26.4) ### NumPy 1.26.4 Release Notes NumPy 1.26.4 is a maintenance release that fixes bugs and regressions discovered after the 1.26.3 release. The Python versions supported by this release are 3.9-3.12. This is the last planned release in the 1.26.x series. #### Contributors A total of 13 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Charles Harris - Elliott Sales de Andrade - Lucas Colley + - Mark Ryan + - Matti Picus - Nathan Goldbaum - Ola x Nilsson + - Pieter Eendebak - Ralf Gommers - Sayed Adel - Sebastian Berg - Stefan van der Walt - Stefano Rivera #### Pull requests merged A total of 19 pull requests were merged for this release. - [#​25323](https://togithub.com/numpy/numpy/pull/25323): BUG: Restore missing asstr import - [#​25523](https://togithub.com/numpy/numpy/pull/25523): MAINT: prepare 1.26.x for further development - [#​25539](https://togithub.com/numpy/numpy/pull/25539): BUG: `numpy.array_api`: fix `linalg.cholesky` upper decomp... - [#​25584](https://togithub.com/numpy/numpy/pull/25584): CI: Bump azure pipeline timeout to 120 minutes - [#​25585](https://togithub.com/numpy/numpy/pull/25585): MAINT, BLD: Fix unused inline functions warnings on clang - [#​25599](https://togithub.com/numpy/numpy/pull/25599): BLD: include fix for MinGW platform detection - [#​25618](https://togithub.com/numpy/numpy/pull/25618): TST: Fix test_numeric on riscv64 - [#​25619](https://togithub.com/numpy/numpy/pull/25619): BLD: fix building for windows ARM64 - [#​25620](https://togithub.com/numpy/numpy/pull/25620): MAINT: add `newaxis` to `__all__` in `numpy.array_api` - [#​25630](https://togithub.com/numpy/numpy/pull/25630): BUG: Use large file fallocate on 32 bit linux platforms - [#​25643](https://togithub.com/numpy/numpy/pull/25643): TST: Fix test_warning_calls on Python 3.12 - [#​25645](https://togithub.com/numpy/numpy/pull/25645): TST: Bump pytz to 2023.3.post1 - [#​25658](https://togithub.com/numpy/numpy/pull/25658): BUG: Fix AVX512 build flags on Intel Classic Compiler - [#​25670](https://togithub.com/numpy/numpy/pull/25670): BLD: fix potential issue with escape sequences in `__config__.py` - [#​25718](https://togithub.com/numpy/numpy/pull/25718): CI: pin cygwin python to 3.9.16-1 and fix typing tests \[skip... - [#​25720](https://togithub.com/numpy/numpy/pull/25720): MAINT: Bump cibuildwheel to v2.16.4 - [#​25748](https://togithub.com/numpy/numpy/pull/25748): BLD: unvendor meson-python on 1.26.x and upgrade to meson-python... - [#​25755](https://togithub.com/numpy/numpy/pull/25755): MAINT: Include header defining backtrace - [#​25756](https://togithub.com/numpy/numpy/pull/25756): BUG: Fix np.quantile(\[Fraction(2,1)], 0.5) ([#​24711](https://togithub.com/numpy/numpy/issues/24711)) #### Checksums ##### MD5 90f33cdd8934cd07192d6ede114d8d4d numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl 63ac60767f6724490e587f6010bd6839 numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl ad4e82b225aaaf5898ea9798b50978d8 numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl d428e3da2df4fa359313348302cf003a numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 89937c3bb596193f8ca9eae2ff84181e numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl de4f9da0a4e6dfd4cec39c7ad5139803 numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl 2c1f73fd9b3acf4b9b0c23e985cdd38f numpy-1.26.4-cp310-cp310-win32.whl 920ad1f50e478b1a877fe7b7a46cc520 numpy-1.26.4-cp310-cp310-win_amd64.whl 719d1ff12db38903dcfd6749078fb11d numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl eb601e80194d2e1c00d8daedd8dc68c4 numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl 71a7ab11996fa370dc28e28731bd5c32 numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl eb0cdd03e1ee2eb45c57c7340c98cf48 numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 9d4ae1b0b27a625400f81ed1846a5667 numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl 1b6771350d2f496157430437a895ba4b numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl 1e4a18612ee4d0e54e0833574ebc6d25 numpy-1.26.4-cp311-cp311-win32.whl 5fd325dd8704023c1110835d7a1b095a numpy-1.26.4-cp311-cp311-win_amd64.whl d95ce582923d24dbddbc108aa5fd2128 numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl 6f16f3d70e0d95ce2b032167c546cc95 numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl 5369536d4c45fbe384147ff23185b48a numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 1ceb224096686831ad731e472b65e96a numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl cd8d3c00bbc89f9bc07e2df762f9e2ae numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl 5bd81ce840bb2e42befe01efb0402b79 numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl 2cc3b0757228078395da3efa3dc99f23 numpy-1.26.4-cp312-cp312-win32.whl 305155bd5ae879344c58968879584ed1 numpy-1.26.4-cp312-cp312-win_amd64.whl ec2310f67215743e9c5d16b6c9fb87b6 numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl 406aea6081c1affbebdb6ad56b5deaf4 numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl fee12f0a3cbac7bbf1a1c2d82d3b02a9 numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl baf4b7143c7b9ce170e62b33380fb573 numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 376ff29f90b7840ae19ecd59ad1ddf53 numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl 86785b3a7cd156c08c2ebc26f7816fb3 numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl ab8a9ab69f16b7005f238cda76bc0bac numpy-1.26.4-cp39-cp39-win32.whl fafa4453e820c7ff40907e5dc79d8199 numpy-1.26.4-cp39-cp39-win_amd64.whl 7f13e2f07bd3e4a439ade0e4d27905c6 numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl 928954b41c1cd0e856f1a31d41722661 numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 57bbd5c0b3848d804c416cbcab4a0ae8 numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl 19550cbe7bedd96a928da9d4ad69509d numpy-1.26.4.tar.gz ##### SHA256 9ff0f4f29c51e2803569d7a51c2304de5554655a60c5d776e35b4a41413830d0 numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl 2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl d209d8969599b27ad20994c8e41936ee0964e6da07478d6c35016bc386b66ad4 numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 62b8e4b1e28009ef2846b4c7852046736bab361f7aeadeb6a5b89ebec3c7055a numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2 numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl bfe25acf8b437eb2a8b2d49d443800a5f18508cd811fea3181723922a8a82b07 numpy-1.26.4-cp310-cp310-win32.whl b97fe8060236edf3662adfc2c633f56a08ae30560c56310562cb4f95500022d5 numpy-1.26.4-cp310-cp310-win_amd64.whl 4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71 numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl 7ab55401287bfec946ced39700c053796e7cc0e3acbef09993a9ad2adba6ca6e numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 666dbfb6ec68962c033a450943ded891bed2d54e6755e35e5835d63f4f6931d5 numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 96ff0b2ad353d8f990b63294c8986f1ec3cb19d749234014f4e7eb0112ceba5a numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl 60dedbb91afcbfdc9bc0b1f3f402804070deed7392c23eb7a7f07fa857868e8a numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl 1af303d6b2210eb850fcf03064d364652b7120803a0b872f5211f5234b399f20 numpy-1.26.4-cp311-cp311-win32.whl cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2 numpy-1.26.4-cp311-cp311-win_amd64.whl b3ce300f3644fb06443ee2222c2201dd3a89ea6040541412b8fa189341847218 numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl 03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl 9fad7dcb1aac3c7f0584a5a8133e3a43eeb2fe127f47e3632d43d677c66c102b numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 675d61ffbfa78604709862923189bad94014bef562cc35cf61d3a07bba02a7ed numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl ab47dbe5cc8210f55aa58e4805fe224dac469cde56b9f731a4c098b91917159a numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl 1dda2e7b4ec9dd512f84935c5f126c8bd8b9f2fc001e9f54af255e8c5f16b0e0 numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl 50193e430acfc1346175fcbdaa28ffec49947a06918b7b92130744e81e640110 numpy-1.26.4-cp312-cp312-win32.whl 08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818 numpy-1.26.4-cp312-cp312-win_amd64.whl 7349ab0fa0c429c82442a27a9673fc802ffdb7c7775fad780226cb234965e53c numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl 52b8b60467cd7dd1e9ed082188b4e6bb35aa5cdd01777621a1658910745b90be numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl d5241e0a80d808d70546c697135da2c613f30e28251ff8307eb72ba696945764 numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3 numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 679b0076f67ecc0138fd2ede3a8fd196dddc2ad3254069bcb9faf9a79b1cebcd numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl 47711010ad8555514b434df65f7d7b076bb8261df1ca9bb78f53d3b2db02e95c numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl a354325ee03388678242a4d7ebcd08b5c727033fcff3b2f536aea978e15ee9e6 numpy-1.26.4-cp39-cp39-win32.whl 3373d5d70a5fe74a2c1bb6d2cfd9609ecf686d47a2d7b1d37a8f3b6bf6003aea numpy-1.26.4-cp39-cp39-win_amd64.whl afedb719a9dcfc7eaf2287b839d8198e06dcd4cb5d276a3df279231138e83d30 numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl 95a7476c59002f2f6c590b9b7b998306fba6a5aa646b1e22ddfeaf8f78c3a29c numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0 numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl 2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010 numpy-1.26.4.tar.gz

Configuration

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

🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.

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

πŸ”• Ignore: Close this PR and you won't be reminded about these updates again.



This PR was generated by Mend Renovate. View the repository job log.