numpy@2.4.6

Fundamental package for array computing in Python

2026-05-18 Python >=3.11 wheel sdist

安装 (2.4.6)

pip install numpy==2.4.6

poetry add numpy==2.4.6

pipenv install numpy==2.4.6

conda install numpy=2.4.6

下载文件

文件名	类型	Python 版本	大小
numpy-2.4.6-cp311-cp311-macosx_10_9_x86_64.whl	bdist_wheel	`cp311`	16969194 bytes
numpy-2.4.6-cp311-cp311-macosx_11_0_arm64.whl	bdist_wheel	`cp311`	14964111 bytes
numpy-2.4.6-cp311-cp311-macosx_14_0_arm64.whl	bdist_wheel	`cp311`	5469159 bytes
numpy-2.4.6-cp311-cp311-macosx_14_0_x86_64.whl	bdist_wheel	`cp311`	6798936 bytes
numpy-2.4.6-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp311`	15966692 bytes
numpy-2.4.6-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp311`	16918164 bytes
numpy-2.4.6-cp311-cp311-musllinux_1_2_aarch64.whl	bdist_wheel	`cp311`	17322877 bytes
numpy-2.4.6-cp311-cp311-musllinux_1_2_x86_64.whl	bdist_wheel	`cp311`	18651487 bytes
numpy-2.4.6-cp311-cp311-win32.whl	bdist_wheel	`cp311`	6233945 bytes
numpy-2.4.6-cp311-cp311-win_amd64.whl	bdist_wheel	`cp311`	12608406 bytes
numpy-2.4.6-cp311-cp311-win_arm64.whl	bdist_wheel	`cp311`	10479528 bytes
numpy-2.4.6-cp312-cp312-macosx_10_13_x86_64.whl	bdist_wheel	`cp312`	16689119 bytes
numpy-2.4.6-cp312-cp312-macosx_11_0_arm64.whl	bdist_wheel	`cp312`	14699246 bytes
numpy-2.4.6-cp312-cp312-macosx_14_0_arm64.whl	bdist_wheel	`cp312`	5204410 bytes
numpy-2.4.6-cp312-cp312-macosx_14_0_x86_64.whl	bdist_wheel	`cp312`	6551240 bytes
numpy-2.4.6-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp312`	15671012 bytes
numpy-2.4.6-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp312`	16645538 bytes
numpy-2.4.6-cp312-cp312-musllinux_1_2_aarch64.whl	bdist_wheel	`cp312`	17020706 bytes
numpy-2.4.6-cp312-cp312-musllinux_1_2_x86_64.whl	bdist_wheel	`cp312`	18368541 bytes
numpy-2.4.6-cp312-cp312-win32.whl	bdist_wheel	`cp312`	5962825 bytes
numpy-2.4.6-cp312-cp312-win_amd64.whl	bdist_wheel	`cp312`	12321687 bytes
numpy-2.4.6-cp312-cp312-win_arm64.whl	bdist_wheel	`cp312`	10221482 bytes
numpy-2.4.6-cp313-cp313-macosx_10_13_x86_64.whl	bdist_wheel	`cp313`	16684648 bytes
numpy-2.4.6-cp313-cp313-macosx_11_0_arm64.whl	bdist_wheel	`cp313`	14693902 bytes
numpy-2.4.6-cp313-cp313-macosx_14_0_arm64.whl	bdist_wheel	`cp313`	5198992 bytes
numpy-2.4.6-cp313-cp313-macosx_14_0_x86_64.whl	bdist_wheel	`cp313`	6546944 bytes
numpy-2.4.6-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp313`	15669392 bytes
numpy-2.4.6-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp313`	16633220 bytes
numpy-2.4.6-cp313-cp313-musllinux_1_2_aarch64.whl	bdist_wheel	`cp313`	17020800 bytes
numpy-2.4.6-cp313-cp313-musllinux_1_2_x86_64.whl	bdist_wheel	`cp313`	18357600 bytes
numpy-2.4.6-cp313-cp313t-macosx_11_0_arm64.whl	bdist_wheel	`cp313`	14821197 bytes
numpy-2.4.6-cp313-cp313t-macosx_14_0_arm64.whl	bdist_wheel	`cp313`	5326287 bytes
numpy-2.4.6-cp313-cp313t-macosx_14_0_x86_64.whl	bdist_wheel	`cp313`	6646763 bytes
numpy-2.4.6-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp313`	15728070 bytes
numpy-2.4.6-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp313`	16681752 bytes
numpy-2.4.6-cp313-cp313t-musllinux_1_2_aarch64.whl	bdist_wheel	`cp313`	17086024 bytes
numpy-2.4.6-cp313-cp313t-musllinux_1_2_x86_64.whl	bdist_wheel	`cp313`	18403398 bytes
numpy-2.4.6-cp313-cp313t-win32.whl	bdist_wheel	`cp313`	6084971 bytes
numpy-2.4.6-cp313-cp313t-win_amd64.whl	bdist_wheel	`cp313`	12458532 bytes
numpy-2.4.6-cp313-cp313t-win_arm64.whl	bdist_wheel	`cp313`	10291881 bytes
numpy-2.4.6-cp313-cp313-win32.whl	bdist_wheel	`cp313`	5961134 bytes
numpy-2.4.6-cp313-cp313-win_amd64.whl	bdist_wheel	`cp313`	12318598 bytes
numpy-2.4.6-cp313-cp313-win_arm64.whl	bdist_wheel	`cp313`	10222272 bytes
numpy-2.4.6-cp314-cp314-macosx_10_15_x86_64.whl	bdist_wheel	`cp314`	16683458 bytes
numpy-2.4.6-cp314-cp314-macosx_11_0_arm64.whl	bdist_wheel	`cp314`	14704559 bytes
numpy-2.4.6-cp314-cp314-macosx_14_0_arm64.whl	bdist_wheel	`cp314`	5209716 bytes
numpy-2.4.6-cp314-cp314-macosx_14_0_x86_64.whl	bdist_wheel	`cp314`	6543947 bytes
numpy-2.4.6-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp314`	15685197 bytes
numpy-2.4.6-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp314`	16638245 bytes
numpy-2.4.6-cp314-cp314-musllinux_1_2_aarch64.whl	bdist_wheel	`cp314`	17036587 bytes
numpy-2.4.6-cp314-cp314-musllinux_1_2_x86_64.whl	bdist_wheel	`cp314`	18363226 bytes
numpy-2.4.6-cp314-cp314t-macosx_11_0_arm64.whl	bdist_wheel	`cp314`	14823672 bytes
numpy-2.4.6-cp314-cp314t-macosx_14_0_arm64.whl	bdist_wheel	`cp314`	5328731 bytes
numpy-2.4.6-cp314-cp314t-macosx_14_0_x86_64.whl	bdist_wheel	`cp314`	6649805 bytes
numpy-2.4.6-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`cp314`	15730496 bytes
numpy-2.4.6-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`cp314`	16679616 bytes
numpy-2.4.6-cp314-cp314t-musllinux_1_2_aarch64.whl	bdist_wheel	`cp314`	17085145 bytes
numpy-2.4.6-cp314-cp314t-musllinux_1_2_x86_64.whl	bdist_wheel	`cp314`	18403813 bytes
numpy-2.4.6-cp314-cp314t-win32.whl	bdist_wheel	`cp314`	6156982 bytes
numpy-2.4.6-cp314-cp314t-win_amd64.whl	bdist_wheel	`cp314`	12638908 bytes
numpy-2.4.6-cp314-cp314t-win_arm64.whl	bdist_wheel	`cp314`	10565867 bytes
numpy-2.4.6-cp314-cp314-win32.whl	bdist_wheel	`cp314`	6010196 bytes
numpy-2.4.6-cp314-cp314-win_amd64.whl	bdist_wheel	`cp314`	12450334 bytes
numpy-2.4.6-cp314-cp314-win_arm64.whl	bdist_wheel	`cp314`	10495678 bytes
numpy-2.4.6-pp311-pypy311_pp73-macosx_10_15_x86_64.whl	bdist_wheel	`pp311`	16847511 bytes
numpy-2.4.6-pp311-pypy311_pp73-macosx_11_0_arm64.whl	bdist_wheel	`pp311`	14889064 bytes
numpy-2.4.6-pp311-pypy311_pp73-macosx_14_0_arm64.whl	bdist_wheel	`pp311`	5394157 bytes
numpy-2.4.6-pp311-pypy311_pp73-macosx_14_0_x86_64.whl	bdist_wheel	`pp311`	6708728 bytes
numpy-2.4.6-pp311-pypy311_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl	bdist_wheel	`pp311`	15798374 bytes
numpy-2.4.6-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl	bdist_wheel	`pp311`	16747286 bytes
numpy-2.4.6-pp311-pypy311_pp73-win_amd64.whl	bdist_wheel	`pp311`	12504263 bytes
numpy-2.4.6.tar.gz	sdist	`source`	20735807 bytes

版本列表

2.5.0rc1 2026-06-02

2.4.6 2026-05-18

2.4.5 2026-05-15

2.4.4 2026-03-29

2.4.3 2026-03-09

2.4.2 2026-01-31

2.4.1 2026-01-10

2.4.0 2025-12-20

2.4.0rc1 2025-12-03

2.3.5 2025-11-16

2.3.4 2025-10-15

2.3.3 2025-09-09

2.3.2 2025-07-24

2.3.1 2025-06-21

2.3.0 2025-06-07

2.2.6 2025-05-17

2.2.5 2025-04-19

2.2.4 2025-03-16

2.2.3 2025-02-13

2.2.2 2025-01-18

2.2.1 2024-12-21

2.2.0 2024-12-08

2.1.3 2024-11-02

2.1.2 2024-10-05

2.1.1 2024-09-03

2.1.0 2024-08-18

2.0.2 2024-08-26

2.0.1 2024-07-21

2.0.0 2024-06-16

1.26.4 2024-02-05

1.26.3 2024-01-02

1.26.2 2023-11-12

1.26.1 2023-10-14

1.26.0 2023-09-16

1.25.2 2023-07-31

1.25.1 2023-07-08

1.25.0 2023-06-17

1.24.4 2023-06-26

1.24.3 2023-04-22

1.24.2 2023-02-05

1.24.1 2022-12-26

1.24.0 2022-12-18

1.23.5 2022-11-20

1.23.4 2022-10-12

1.23.3 2022-09-09

1.23.2 2022-08-14

1.23.1 2022-07-09

1.23.0 2022-06-22

1.22.4 2022-05-20

1.22.3 2022-03-07

1.22.2 2022-02-04

1.22.1 2022-01-14

1.22.0 2021-12-31

1.21.6 2022-04-12

1.21.5 2021-12-19

1.21.4 2021-11-05

1.21.3 2021-10-20

1.21.2 2021-08-15

1.21.1 2021-07-18

1.21.0 2021-06-22

1.20.3 2021-05-10

1.20.2 2021-03-27

1.20.1 2021-02-07

1.20.0 2021-01-30

1.19.5 2021-01-05

1.19.4 2020-11-02

1.19.3 2020-10-29

1.19.2 2020-09-10

1.19.1 2020-07-21

1.19.0 2020-06-20

1.18.5 2020-06-04

1.18.4 2020-05-03

1.18.3 2020-04-19

1.18.2 2020-03-17

1.18.1 2020-01-06

1.18.0 2019-12-22

1.17.5 2020-01-01

1.17.4 2019-11-11

1.17.3 2019-10-17

1.17.2 2019-09-07

1.17.1 2019-08-27

1.17.0 2019-07-26

1.16.6 2019-12-29

1.16.5 2019-08-28

1.16.4 2019-05-28

1.16.3 2019-04-22

1.16.2 2019-02-26

1.16.1 2019-01-31

1.16.0 2019-01-14

1.15.4 2018-11-04

1.15.3 2018-10-22

1.15.2 2018-09-23

1.15.1 2018-08-21

1.15.0 2018-07-23

1.14.6 2018-09-23

1.14.5 2018-06-12

1.14.4 2018-06-06

1.14.3 2018-04-28

1.14.2 2018-03-12

1.14.1 2018-02-21

1.14.0 2018-01-06

1.13.3 2017-09-30

1.13.1 2017-07-07

1.13.0 2017-06-07

1.12.1 2017-03-18

1.12.0 2017-01-15

1.11.3 2016-12-19

1.11.2 2016-10-04

1.11.1 2016-06-26

1.11.0 2016-03-27

1.10.4 2016-04-20

1.10.3 2016-04-20

1.10.2 2016-04-20

1.10.1 2016-04-20

1.10.0 2016-04-20

1.9.3 2016-04-20

1.9.2 2016-04-20

1.9.1 2016-04-20

1.9.0 2016-04-20

1.8.2 2016-04-20

1.8.1 2016-04-20

1.8.0 2016-04-20

1.7.2 2016-04-20

1.7.1 2016-04-20

1.7.0 2016-04-20

1.6.2 2016-04-20

1.6.1 2016-04-20

1.6.0 2016-04-20

1.5.1 2014-07-30

1.5.0 2010-09-15

1.4.1 2010-04-24

1.4.0

1.3.0 2009-04-06

1.2.1

1.2.0

1.1.1

1.0.4

1.0.3

1.0 2006-12-02

1.0rc3

1.0rc2

1.0rc1

1.0b5

1.0b4

1.0b1

0.9.8

0.9.6

numpy@2.4.6

安装 (2.4.6)

下载文件

版本列表

相关教程