Skip to content

v1.24.2

Compare
Choose a tag to compare
@charris charris released this 05 Feb 20:16
· 4844 commits to main since this release
v1.24.2
85f38ab

NumPy 1.24.2 Release Notes

NumPy 1.24.2 is a maintenance release that fixes bugs and regressions
discovered after the 1.24.1 release. The Python versions supported by
this release are 3.8-3.11.

Contributors

A total of 14 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Bas van Beek
  • Charles Harris
  • Khem Raj +
  • Mark Harfouche
  • Matti Picus
  • Panagiotis Zestanakis +
  • Peter Hawkins
  • Pradipta Ghosh
  • Ross Barnowski
  • Sayed Adel
  • Sebastian Berg
  • Syam Gadde +
  • dmbelov +
  • pkubaj +

Pull requests merged

A total of 17 pull requests were merged for this release.

  • #22965: MAINT: Update python 3.11-dev to 3.11.
  • #22966: DOC: Remove dangling deprecation warning
  • #22967: ENH: Detect CPU features on FreeBSD/powerpc64*
  • #22968: BUG: np.loadtxt cannot load text file with quoted fields separated...
  • #22969: TST: Add fixture to avoid issue with randomizing test order.
  • #22970: BUG: Fix fill violating read-only flag. (#22959)
  • #22971: MAINT: Add additional information to missing scalar AttributeError
  • #22972: MAINT: Move export for scipy arm64 helper into main module
  • #22976: BUG, SIMD: Fix spurious invalid exception for sin/cos on arm64/clang
  • #22989: BUG: Ensure correct loop order in sin, cos, and arctan2
  • #23030: DOC: Add version added information for the strict parameter in...
  • #23031: BUG: use _Alignof rather than offsetof() on most compilers
  • #23147: BUG: Fix for npyv__trunc_s32_f32 (VXE)
  • #23148: BUG: Fix integer / float scalar promotion
  • #23149: BUG: Add missing <type_traits> header.
  • #23150: TYP, MAINT: Add a missing explicit Any parameter to the npt.ArrayLike...
  • #23161: BLD: remove redundant definition of npy_nextafter [wheel build]

Checksums

MD5

73fe0b507f56c0baf43171a76ad2003f  numpy-1.24.2-cp310-cp310-macosx_10_9_x86_64.whl
2dbbe6f8a14e14978d24de9fcc8b49fe  numpy-1.24.2-cp310-cp310-macosx_11_0_arm64.whl
9ddadbf9cac2742318d8b292cb9ca579  numpy-1.24.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
969f4f33baaff53dbbbaf1a146c43534  numpy-1.24.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
6df575dff02feac835d22debb15d190e  numpy-1.24.2-cp310-cp310-win32.whl
2f939228a8c33265f2a8a1fce349d6f1  numpy-1.24.2-cp310-cp310-win_amd64.whl
c093e61421be01ffff435387839949f1  numpy-1.24.2-cp311-cp311-macosx_10_9_x86_64.whl
03d71e3d9a086b56837c461fd7c9188b  numpy-1.24.2-cp311-cp311-macosx_11_0_arm64.whl
c0dc33697d156e2b9a029095efeb1b10  numpy-1.24.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
13b57957a1f40e13f8826d14b031a6fe  numpy-1.24.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
5afd966db0b59655618c1859d98d87f6  numpy-1.24.2-cp311-cp311-win32.whl
e0b850f9c20871cd65ecb35235688f4d  numpy-1.24.2-cp311-cp311-win_amd64.whl
9a30452135ab0387b8ea9007e94e9f81  numpy-1.24.2-cp38-cp38-macosx_10_9_x86_64.whl
bdd6eede4524a230574b37e1f631f2c0  numpy-1.24.2-cp38-cp38-macosx_11_0_arm64.whl
4f930a9030d77d45a1cb6f374c91fb53  numpy-1.24.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
e77155c010f9dd63ea2815579a28c503  numpy-1.24.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
1a45f4373945eaeabeaa4020ce04e8fd  numpy-1.24.2-cp38-cp38-win32.whl
66e93d70fad16b4ccb4531e31aad36e3  numpy-1.24.2-cp38-cp38-win_amd64.whl
93a4984da83c6811367d3daf709ed25c  numpy-1.24.2-cp39-cp39-macosx_10_9_x86_64.whl
e0281b96c490ba00f1382eb3984b4e51  numpy-1.24.2-cp39-cp39-macosx_11_0_arm64.whl
ce97d81e4ae6e10241d471492391b1be  numpy-1.24.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
0c0ea440190705f98abeaa856e7da690  numpy-1.24.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c25f7fbb185f1b8f7761bc22082d9939  numpy-1.24.2-cp39-cp39-win32.whl
7705c6b0bcf22b5e64cf248144b2f554  numpy-1.24.2-cp39-cp39-win_amd64.whl
07b6361e36e0093b580dc05799b1f03d  numpy-1.24.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
4c1466ae486b39d1a35aacb46256ec1e  numpy-1.24.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
4fea9d95e0489d06c3a24a87697d2fc0  numpy-1.24.2-pp38-pypy38_pp73-win_amd64.whl
c4212a8da1ecf17ece37e2afd0319806  numpy-1.24.2.tar.gz

SHA256

eef70b4fc1e872ebddc38cddacc87c19a3709c0e3e5d20bf3954c147b1dd941d  numpy-1.24.2-cp310-cp310-macosx_10_9_x86_64.whl
e8d2859428712785e8a8b7d2b3ef0a1d1565892367b32f915c4a4df44d0e64f5  numpy-1.24.2-cp310-cp310-macosx_11_0_arm64.whl
6524630f71631be2dabe0c541e7675db82651eb998496bbe16bc4f77f0772253  numpy-1.24.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
a51725a815a6188c662fb66fb32077709a9ca38053f0274640293a14fdd22978  numpy-1.24.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
2620e8592136e073bd12ee4536149380695fbe9ebeae845b81237f986479ffc9  numpy-1.24.2-cp310-cp310-win32.whl
97cf27e51fa078078c649a51d7ade3c92d9e709ba2bfb97493007103c741f1d0  numpy-1.24.2-cp310-cp310-win_amd64.whl
7de8fdde0003f4294655aa5d5f0a89c26b9f22c0a58790c38fae1ed392d44a5a  numpy-1.24.2-cp311-cp311-macosx_10_9_x86_64.whl
4173bde9fa2a005c2c6e2ea8ac1618e2ed2c1c6ec8a7657237854d42094123a0  numpy-1.24.2-cp311-cp311-macosx_11_0_arm64.whl
4cecaed30dc14123020f77b03601559fff3e6cd0c048f8b5289f4eeabb0eb281  numpy-1.24.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
9a23f8440561a633204a67fb44617ce2a299beecf3295f0d13c495518908e910  numpy-1.24.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e428c4fbfa085f947b536706a2fc349245d7baa8334f0c5723c56a10595f9b95  numpy-1.24.2-cp311-cp311-win32.whl
557d42778a6869c2162deb40ad82612645e21d79e11c1dc62c6e82a2220ffb04  numpy-1.24.2-cp311-cp311-win_amd64.whl
d0a2db9d20117bf523dde15858398e7c0858aadca7c0f088ac0d6edd360e9ad2  numpy-1.24.2-cp38-cp38-macosx_10_9_x86_64.whl
c72a6b2f4af1adfe193f7beb91ddf708ff867a3f977ef2ec53c0ffb8283ab9f5  numpy-1.24.2-cp38-cp38-macosx_11_0_arm64.whl
c29e6bd0ec49a44d7690ecb623a8eac5ab8a923bce0bea6293953992edf3a76a  numpy-1.24.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2eabd64ddb96a1239791da78fa5f4e1693ae2dadc82a76bc76a14cbb2b966e96  numpy-1.24.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e3ab5d32784e843fc0dd3ab6dcafc67ef806e6b6828dc6af2f689be0eb4d781d  numpy-1.24.2-cp38-cp38-win32.whl
76807b4063f0002c8532cfeac47a3068a69561e9c8715efdad3c642eb27c0756  numpy-1.24.2-cp38-cp38-win_amd64.whl
4199e7cfc307a778f72d293372736223e39ec9ac096ff0a2e64853b866a8e18a  numpy-1.24.2-cp39-cp39-macosx_10_9_x86_64.whl
adbdce121896fd3a17a77ab0b0b5eedf05a9834a18699db6829a64e1dfccca7f  numpy-1.24.2-cp39-cp39-macosx_11_0_arm64.whl
889b2cc88b837d86eda1b17008ebeb679d82875022200c6e8e4ce6cf549b7acb  numpy-1.24.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
f64bb98ac59b3ea3bf74b02f13836eb2e24e48e0ab0145bbda646295769bd780  numpy-1.24.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
63e45511ee4d9d976637d11e6c9864eae50e12dc9598f531c035265991910468  numpy-1.24.2-cp39-cp39-win32.whl
a77d3e1163a7770164404607b7ba3967fb49b24782a6ef85d9b5f54126cc39e5  numpy-1.24.2-cp39-cp39-win_amd64.whl
92011118955724465fb6853def593cf397b4a1367495e0b59a7e69d40c4eb71d  numpy-1.24.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
f9006288bcf4895917d02583cf3411f98631275bc67cce355a7f39f8c14338fa  numpy-1.24.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
150947adbdfeceec4e5926d956a06865c1c690f2fd902efede4ca6fe2e657c3f  numpy-1.24.2-pp38-pypy38_pp73-win_amd64.whl
003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22  numpy-1.24.2.tar.gz