v1.21.5

NumPy 1.21.5 Release Notes

NumPy 1.21.5 is a maintenance release that fixes a few bugs discovered
after the 1.21.4 release and does some maintenance to extend the 1.21.x
lifetime. 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
• Matti Picus
• Rohit Goswami
• Ross Barnowski
• Sayed Adel
• Sebastian Berg

Pull requests merged

A total of 11 pull requests were merged for this release.

• #20357: MAINT: Do not forward __(deep)copy__ calls of _GenericAlias...
• #20462: BUG: Fix float16 einsum fastpaths using wrong tempvar
• #20463: BUG, DIST: Print os error message when the executable not exist
• #20464: BLD: Verify the ability to compile C++ sources before initiating...
• #20465: BUG: Force npymath to respect npy_longdouble
• #20466: BUG: Fix failure to create aligned, empty structured dtype
• #20467: ENH: provide a convenience function to replace npy_load_module
• #20495: MAINT: update wheel to version that supports python3.10
• #20497: BUG: Clear errors correctly in F2PY conversions
• #20613: DEV: add a warningfilter to fix pytest workflow.
• #20618: MAINT: Help boost::python libraries at least not crash

Checksums

MD5

e00a3c2e1461dd2920ab4af6b753d3da  numpy-1.21.5-cp310-cp310-macosx_10_9_universal2.whl
50e0526fa29110fb6033fa8285fba4e1  numpy-1.21.5-cp310-cp310-macosx_10_9_x86_64.whl
bdbb19e7656d66250aa67bd1c7924764  numpy-1.21.5-cp310-cp310-macosx_11_0_arm64.whl
c5c982a07797c8963b8fec44aae6db09  numpy-1.21.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
8b27b622f58caeeb7f14472651d655e3  numpy-1.21.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e545f6f85f950f57606efcaeeac2e50a  numpy-1.21.5-cp310-cp310-win_amd64.whl
5c36eefdcb039c0d4db8882fddbeb695  numpy-1.21.5-cp37-cp37m-macosx_10_9_x86_64.whl
b5d080e0fd8b658419b3636f1cf5dc3a  numpy-1.21.5-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
ec1a9a1333a2bf61897f105ecd9f212a  numpy-1.21.5-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
d5ab050300748f20cdc9c6e17ba8ffd4  numpy-1.21.5-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
b7498a1d0ea7273ef1af56d58e02a550  numpy-1.21.5-cp37-cp37m-win32.whl
f55c7ecfd35769fb3f6a408c0c123372  numpy-1.21.5-cp37-cp37m-win_amd64.whl
843e3431ba4b56d3fc36b7c4cb6fc10c  numpy-1.21.5-cp38-cp38-macosx_10_9_universal2.whl
4721e71bdc5697d310cd3a6b6cd60741  numpy-1.21.5-cp38-cp38-macosx_10_9_x86_64.whl
2169fb8ed40046e1e33d187fc85b91bb  numpy-1.21.5-cp38-cp38-macosx_11_0_arm64.whl
52de43977749109509ee708a142a7d97  numpy-1.21.5-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
703c0f54c5ede8cc0c648ef66cafac47  numpy-1.21.5-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
50432f9cf1d5b2278ceb7a96890353ed  numpy-1.21.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
0c4c5336136e045d02c60ba8115eb6a2  numpy-1.21.5-cp38-cp38-win32.whl
c2e0744164f8255be70725ef42bc3f5b  numpy-1.21.5-cp38-cp38-win_amd64.whl
b16dd7103117d051cb6c3b6c4434f7d2  numpy-1.21.5-cp39-cp39-macosx_10_9_universal2.whl
220dd07273aeb0b2ca8f0e4f543e43c3  numpy-1.21.5-cp39-cp39-macosx_10_9_x86_64.whl
1dd09ad75eff93b274f650871e0b9287  numpy-1.21.5-cp39-cp39-macosx_11_0_arm64.whl
6801263f51d3b13420b59ff84c716869  numpy-1.21.5-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
035bde3955ae2f62ada65084d71a7421  numpy-1.21.5-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
09f202576cbd0ed6121cff10cdea831a  numpy-1.21.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
c6a44c90c2d5124fea6cedbbf575e252  numpy-1.21.5-cp39-cp39-win32.whl
bbc11e31406a9fc48c18a41259bc8866  numpy-1.21.5-cp39-cp39-win_amd64.whl
5be2b6f6cf6fb3a3d98231e891260624  numpy-1.21.5-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
8bc9ff24bac9bf4268372cefea8f0b6b  numpy-1.21.5.tar.gz
88b5438ded7992fa2e6a810d43cd32a1  numpy-1.21.5.zip

SHA256

301e408a052fdcda5cdcf03021ebafc3c6ea093021bf9d1aa47c54d48bdad166  numpy-1.21.5-cp310-cp310-macosx_10_9_universal2.whl
a7e8f6216f180f3fd4efb73de5d1eaefb5f5a1ee5b645c67333033e39440e63a  numpy-1.21.5-cp310-cp310-macosx_10_9_x86_64.whl
fc7a7d7b0ed72589fd8b8486b9b42a564f10b8762be8bd4d9df94b807af4a089  numpy-1.21.5-cp310-cp310-macosx_11_0_arm64.whl
58ca1d7c8aef6e996112d0ce873ac9dfa1eaf4a1196b4ff7ff73880a09923ba7  numpy-1.21.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
dc4b2fb01f1b4ddbe2453468ea0719f4dbb1f5caa712c8b21bb3dd1480cd30d9  numpy-1.21.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
cc1b30205d138d1005adb52087ff45708febbef0e420386f58664f984ef56954  numpy-1.21.5-cp310-cp310-win_amd64.whl
08de8472d9f7571f9d51b27b75e827f5296295fa78817032e84464be8bb905bc  numpy-1.21.5-cp37-cp37m-macosx_10_9_x86_64.whl
4fe6a006557b87b352c04596a6e3f12a57d6e5f401d804947bd3188e6b0e0e76  numpy-1.21.5-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
3d893b0871322eaa2f8c7072cdb552d8e2b27645b7875a70833c31e9274d4611  numpy-1.21.5-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
341dddcfe3b7b6427a28a27baa59af5ad51baa59bfec3264f1ab287aa3b30b13  numpy-1.21.5-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
ca9c23848292c6fe0a19d212790e62f398fd9609aaa838859be8459bfbe558aa  numpy-1.21.5-cp37-cp37m-win32.whl
025b497014bc33fc23897859350f284323f32a2fff7654697f5a5fc2a19e9939  numpy-1.21.5-cp37-cp37m-win_amd64.whl
3a5098df115340fb17fc93867317a947e1dcd978c3888c5ddb118366095851f8  numpy-1.21.5-cp38-cp38-macosx_10_9_universal2.whl
311283acf880cfcc20369201bd75da907909afc4666966c7895cbed6f9d2c640  numpy-1.21.5-cp38-cp38-macosx_10_9_x86_64.whl
b545ebadaa2b878c8630e5bcdb97fc4096e779f335fc0f943547c1c91540c815  numpy-1.21.5-cp38-cp38-macosx_11_0_arm64.whl
c5562bcc1a9b61960fc8950ade44d00e3de28f891af0acc96307c73613d18f6e  numpy-1.21.5-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
eed2afaa97ec33b4411995be12f8bdb95c87984eaa28d76cf628970c8a2d689a  numpy-1.21.5-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
61bada43d494515d5b122f4532af226fdb5ee08fe5b5918b111279843dc6836a  numpy-1.21.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
7b9d6b14fc9a4864b08d1ba57d732b248f0e482c7b2ff55c313137e3ed4d8449  numpy-1.21.5-cp38-cp38-win32.whl
dbce7adeb66b895c6aaa1fad796aaefc299ced597f6fbd9ceddb0dd735245354  numpy-1.21.5-cp38-cp38-win_amd64.whl
507c05c7a37b3683eb08a3ff993bd1ee1e6c752f77c2f275260533b265ecdb6c  numpy-1.21.5-cp39-cp39-macosx_10_9_universal2.whl
00c9fa73a6989895b8815d98300a20ac993c49ac36c8277e8ffeaa3631c0dbbb  numpy-1.21.5-cp39-cp39-macosx_10_9_x86_64.whl
69a5a8d71c308d7ef33ef72371c2388a90e3495dbb7993430e674006f94797d5  numpy-1.21.5-cp39-cp39-macosx_11_0_arm64.whl
2d8adfca843bc46ac199a4645233f13abf2011a0b2f4affc5c37cd552626f27b  numpy-1.21.5-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
c293d3c0321996cd8ffe84215ffe5d269fd9d1d12c6f4ffe2b597a7c30d3e593  numpy-1.21.5-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
3c978544be9e04ed12016dd295a74283773149b48f507d69b36f91aa90a643e5  numpy-1.21.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
2a9add27d7fc0fdb572abc3b2486eb3b1395da71e0254c5552b2aad2a18b5441  numpy-1.21.5-cp39-cp39-win32.whl
1964db2d4a00348b7a60ee9d013c8cb0c566644a589eaa80995126eac3b99ced  numpy-1.21.5-cp39-cp39-win_amd64.whl
a7c4b701ca418cd39e28ec3b496e6388fe06de83f5f0cb74794fa31cfa384c02  numpy-1.21.5-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
1a7ee0ffb35dc7489aebe5185a483f4c43b0d2cf784c3c9940f975a7dde56506  numpy-1.21.5.tar.gz
6a5928bc6241264dce5ed509e66f33676fc97f464e7a919edc672fb5532221ee  numpy-1.21.5.zip