github numpy/numpy v1.21.4

latest releases: v1.23.0rc1, v1.24.0.dev0, v1.22.4...
6 months ago

NumPy 1.21.4 Release Notes

The NumPy 1.21.4 is a maintenance release that fixes a few bugs
discovered after 1.21.3. The most important fix here is a fix for the
NumPy header files to make them work for both x86_64 and M1 hardware
when included in the Mac universal2 wheels. Previously, the header files
only worked for M1 and this caused problems for folks building x86_64
extensions. This problem was not seen before Python 3.10 because there
were thin wheels for x86_64 that had precedence. This release also
provides thin x86_64 Mac wheels for Python 3.10.

The Python versions supported in this release are 3.7-3.10. If you want
to compile your own version using gcc-11, you will need to use gcc-11.2+
to avoid problems.

Contributors

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

  • Bas van Beek
  • Charles Harris
  • Isuru Fernando
  • Matthew Brett
  • Sayed Adel
  • Sebastian Berg
  • 傅立业(Chris Fu) +

Pull requests merged

A total of 9 pull requests were merged for this release.

  • #20278: BUG: Fix shadowed reference of dtype in type stub
  • #20293: BUG: Fix headers for universal2 builds
  • #20294: BUG: VOID_nonzero could sometimes mutate alignment flag
  • #20295: BUG: Do not use nonzero fastpath on unaligned arrays
  • #20296: BUG: Distutils patch to allow for 2 as a minor version (!)
  • #20297: BUG, SIMD: Fix 64-bit/8-bit integer division by a scalar
  • #20298: BUG, SIMD: Workaround broadcasting SIMD 64-bit integers on MSVC...
  • #20300: REL: Prepare for the NumPy 1.21.4 release.
  • #20302: TST: Fix a Arrayterator typing test failure

Checksums

MD5

95486a3ed027c926fb3fc279db6d843e  numpy-1.21.4-cp310-cp310-macosx_10_9_universal2.whl
9f57fad74762f7665669af33583a3dc9  numpy-1.21.4-cp310-cp310-macosx_10_9_x86_64.whl
719a9053aef01a067ce44ede2281eef9  numpy-1.21.4-cp310-cp310-macosx_11_0_arm64.whl
72035d101774fd03beff391927f59aa9  numpy-1.21.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
5813e7a378a6e3f5c269c23f61eff4d9  numpy-1.21.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
b88a1bc4f08dfb154d5a07d15e387af6  numpy-1.21.4-cp310-cp310-win_amd64.whl
f0cc946d2f4ab4df7cc7e0cc8cfd429e  numpy-1.21.4-cp37-cp37m-macosx_10_9_x86_64.whl
1234643306ce481f0e5f801ddf3f1099  numpy-1.21.4-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
b9208ce1695ba61ab2932c7ce7285d1d  numpy-1.21.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
9804fe2011618bf2d7b8d92f6860b2e3  numpy-1.21.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2ad3a06f974acd61326fd66c098df5bc  numpy-1.21.4-cp37-cp37m-win32.whl
172301389f1532b2d9130362580e1e22  numpy-1.21.4-cp37-cp37m-win_amd64.whl
a037bf88979ae0d4699a0cdce92bbab3  numpy-1.21.4-cp38-cp38-macosx_10_9_universal2.whl
ba94609688f575cc8dce84f1512db116  numpy-1.21.4-cp38-cp38-macosx_10_9_x86_64.whl
c78edc0ae8c9a5d8d0f9e3eb6dabd0b3  numpy-1.21.4-cp38-cp38-macosx_11_0_arm64.whl
d683b6f6af46806391579d528a040451  numpy-1.21.4-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
df631f776716aeb3fd705f3659599b9e  numpy-1.21.4-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
b1cbca49d24c7ba43d377feb425afdce  numpy-1.21.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
8b5c214bc0f060dbb0287c15dde4673d  numpy-1.21.4-cp38-cp38-win32.whl
2307cf9f3c02f6cdad448a681c272974  numpy-1.21.4-cp38-cp38-win_amd64.whl
fc02b5a068e29b2dd2de19c7ddd69926  numpy-1.21.4-cp39-cp39-macosx_10_9_universal2.whl
f16068540001de8a3d8f096830c97ea2  numpy-1.21.4-cp39-cp39-macosx_10_9_x86_64.whl
80562c39cfbdf1af9bb43b2ea5e45b6d  numpy-1.21.4-cp39-cp39-macosx_11_0_arm64.whl
6c103bec3085e5a6ea92cf7f6e4189ab  numpy-1.21.4-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
9d715ba5f7596a39eb631f2dae85d203  numpy-1.21.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
8b8cf8c7b093419ff75ed1dd2eaa18ae  numpy-1.21.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
404200b858b7addd03f6cdd5a484d30a  numpy-1.21.4-cp39-cp39-win32.whl
cdab6a1bf1b86021526d08a60219a6ad  numpy-1.21.4-cp39-cp39-win_amd64.whl
70ca6b591e844fdcb8c22175f094d3b4  numpy-1.21.4-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
06019c1116b3e2791bd507f898257e7f  numpy-1.21.4.tar.gz
b3c4477a027d5b6fba5e1065064fd076  numpy-1.21.4.zip

SHA256

8890b3360f345e8360133bc078d2dacc2843b6ee6059b568781b15b97acbe39f  numpy-1.21.4-cp310-cp310-macosx_10_9_universal2.whl
69077388c5a4b997442b843dbdc3a85b420fb693ec8e33020bb24d647c164fa5  numpy-1.21.4-cp310-cp310-macosx_10_9_x86_64.whl
e89717274b41ebd568cd7943fc9418eeb49b1785b66031bc8a7f6300463c5898  numpy-1.21.4-cp310-cp310-macosx_11_0_arm64.whl
0b78ecfa070460104934e2caf51694ccd00f37d5e5dbe76f021b1b0b0d221823  numpy-1.21.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
615d4e328af7204c13ae3d4df7615a13ff60a49cb0d9106fde07f541207883ca  numpy-1.21.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
1403b4e2181fc72664737d848b60e65150f272fe5a1c1cbc16145ed43884065a  numpy-1.21.4-cp310-cp310-win_amd64.whl
74b85a17528ca60cf98381a5e779fc0264b4a88b46025e6bcbe9621f46bb3e63  numpy-1.21.4-cp37-cp37m-macosx_10_9_x86_64.whl
92aafa03da8658609f59f18722b88f0a73a249101169e28415b4fa148caf7e41  numpy-1.21.4-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
5d95668e727c75b3f5088ec7700e260f90ec83f488e4c0aaccb941148b2cd377  numpy-1.21.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
f5162ec777ba7138906c9c274353ece5603646c6965570d82905546579573f73  numpy-1.21.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
81225e58ef5fce7f1d80399575576fc5febec79a8a2742e8ef86d7b03beef49f  numpy-1.21.4-cp37-cp37m-win32.whl
32fe5b12061f6446adcbb32cf4060a14741f9c21e15aaee59a207b6ce6423469  numpy-1.21.4-cp37-cp37m-win_amd64.whl
c449eb870616a7b62e097982c622d2577b3dbc800aaf8689254ec6e0197cbf1e  numpy-1.21.4-cp38-cp38-macosx_10_9_universal2.whl
2e4ed57f45f0aa38beca2a03b6532e70e548faf2debbeb3291cfc9b315d9be8f  numpy-1.21.4-cp38-cp38-macosx_10_9_x86_64.whl
1247ef28387b7bb7f21caf2dbe4767f4f4175df44d30604d42ad9bd701ebb31f  numpy-1.21.4-cp38-cp38-macosx_11_0_arm64.whl
34f3456f530ae8b44231c63082c8899fe9c983fd9b108c997c4b1c8c2d435333  numpy-1.21.4-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
4c9c23158b87ed0e70d9a50c67e5c0b3f75bcf2581a8e34668d4e9d7474d76c6  numpy-1.21.4-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
e4799be6a2d7d3c33699a6f77201836ac975b2e1b98c2a07f66a38f499cb50ce  numpy-1.21.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
bc988afcea53e6156546e5b2885b7efab089570783d9d82caf1cfd323b0bb3dd  numpy-1.21.4-cp38-cp38-win32.whl
170b2a0805c6891ca78c1d96ee72e4c3ed1ae0a992c75444b6ab20ff038ba2cd  numpy-1.21.4-cp38-cp38-win_amd64.whl
fde96af889262e85aa033f8ee1d3241e32bf36228318a61f1ace579df4e8170d  numpy-1.21.4-cp39-cp39-macosx_10_9_universal2.whl
c885bfc07f77e8fee3dc879152ba993732601f1f11de248d4f357f0ffea6a6d4  numpy-1.21.4-cp39-cp39-macosx_10_9_x86_64.whl
9e6f5f50d1eff2f2f752b3089a118aee1ea0da63d56c44f3865681009b0af162  numpy-1.21.4-cp39-cp39-macosx_11_0_arm64.whl
ad010846cdffe7ec27e3f933397f8a8d6c801a48634f419e3d075db27acf5880  numpy-1.21.4-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
c74c699b122918a6c4611285cc2cad4a3aafdb135c22a16ec483340ef97d573c  numpy-1.21.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
9864424631775b0c052f3bd98bc2712d131b3e2cd95d1c0c68b91709170890b0  numpy-1.21.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
b1e2312f5b8843a3e4e8224b2b48fe16119617b8fc0a54df8f50098721b5bed2  numpy-1.21.4-cp39-cp39-win32.whl
e3c3e990274444031482a31280bf48674441e0a5b55ddb168f3a6db3e0c38ec8  numpy-1.21.4-cp39-cp39-win_amd64.whl
a3deb31bc84f2b42584b8c4001c85d1934dbfb4030827110bc36bfd11509b7bf  numpy-1.21.4-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
5d412381aa489b8be82ac5c6a9e99c3eb3f754245ad3f90ab5c339d92f25fb47  numpy-1.21.4.tar.gz
e6c76a87633aa3fa16614b61ccedfae45b91df2767cf097aa9c933932a7ed1e0  numpy-1.21.4.zip

Don't miss a new numpy release

NewReleases is sending notifications on new releases.