Convex optimization package

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for msa from gravatar.com msa

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for msa from gravatar.com msa

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

This version

1.3.2

1.3.1

1.3.0.1

1.3.0

1.2.7

1.2.6

1.2.5.post1

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.9

1.1.8

1.1.7

1.1.6

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cvxopt-1.3.2.tar.gz (4.1 MB view details)

Uploaded Source

Built Distributions

cvxopt-1.3.2-cp313-cp313-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.13 Windows x86-64

cvxopt-1.3.2-cp313-cp313-musllinux_1_2_x86_64.whl (16.2 MB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ x86-64

cvxopt-1.3.2-cp313-cp313-musllinux_1_2_i686.whl (13.7 MB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ i686

cvxopt-1.3.2-cp313-cp313-musllinux_1_2_aarch64.whl (9.5 MB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp313-cp313-manylinux_2_28_x86_64.whl (21.3 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.28+ x86-64

cvxopt-1.3.2-cp313-cp313-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.9 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp313-cp313-macosx_15_0_arm64.whl (12.4 MB view details)

Uploaded CPython 3.13 macOS 15.0+ ARM64

cvxopt-1.3.2-cp313-cp313-macosx_14_0_x86_64.whl (16.9 MB view details)

Uploaded CPython 3.13 macOS 14.0+ x86-64

cvxopt-1.3.2-cp312-cp312-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.12 Windows x86-64

cvxopt-1.3.2-cp312-cp312-musllinux_1_2_aarch64.whl (9.5 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp312-cp312-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.9 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp312-cp312-macosx_11_0_arm64.whl (12.8 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

cvxopt-1.3.2-cp312-cp312-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

cvxopt-1.3.2-cp311-cp311-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.11 Windows x86-64

cvxopt-1.3.2-cp311-cp311-musllinux_1_2_aarch64.whl (9.5 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp311-cp311-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp311-cp311-macosx_11_0_arm64.whl (11.1 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

cvxopt-1.3.2-cp311-cp311-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

cvxopt-1.3.2-cp310-cp310-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

cvxopt-1.3.2-cp310-cp310-musllinux_1_2_aarch64.whl (9.5 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp310-cp310-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp310-cp310-macosx_11_0_arm64.whl (11.1 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

cvxopt-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

cvxopt-1.3.2-cp39-cp39-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

cvxopt-1.3.2-cp39-cp39-musllinux_1_2_aarch64.whl (9.5 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp39-cp39-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp39-cp39-macosx_11_0_arm64.whl (11.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

cvxopt-1.3.2-cp39-cp39-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

cvxopt-1.3.2-cp38-cp38-win_amd64.whl (12.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

cvxopt-1.3.2-cp38-cp38-musllinux_1_2_aarch64.whl (9.4 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp38-cp38-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp38-cp38-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

cvxopt-1.3.2-cp37-cp37m-musllinux_1_2_aarch64.whl (9.4 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp37-cp37m-manylinux_2_28_aarch64.whl (13.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

cvxopt-1.3.2-cp37-cp37m-macosx_10_9_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

cvxopt-1.3.2-cp36-cp36m-musllinux_1_2_aarch64.whl (9.4 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.2+ ARM64

cvxopt-1.3.2-cp36-cp36m-manylinux_2_28_aarch64.whl (13.7 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.28+ ARM64

cvxopt-1.3.2-cp36-cp36m-macosx_10_9_x86_64.whl (13.9 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file cvxopt-1.3.2.tar.gz.

File metadata

  • Download URL: cvxopt-1.3.2.tar.gz
  • Upload date:
  • Size: 4.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2.tar.gz
Algorithm Hash digest
SHA256 3461fa42c1b2240ba4da1d985ca73503914157fc4c77417327ed6d7d85acdbe6
MD5 ced06e7d92d8a10c84db94589e7f8162
BLAKE2b-256 f5128467d16008ab7577259d32f1e59c4d84edda22b7729ab4a1a0dfd5f0550b

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 0a0987966009ad383de0918e61255d34ed9ebc783565bcb15470d4155010b6bf
MD5 6c9491bc39a780115ac753164544b308
BLAKE2b-256 b95590b40b489a235a9f35a532eb77cec81782e466779d9a531ffda6b2f99410

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 85c3b52c1353b294c597b169cc901f5274d8bb8776908ccad66fec7a14b69519
MD5 299b3274469f92f4acee4ded2af1c03e
BLAKE2b-256 76f27e3c3f51e8e6b325bf00bfc37036f1f58bd9a5c29bbd88fb2eef2ebc0ac2

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 4c56965415afd8a493cc4af3587960751f8780057ca3de8c6be97217156e4633
MD5 bcf9a658a4f566c34c20e4f97aebf54c
BLAKE2b-256 42ccac0705749f96cc52f8d30c9c06e54dc8d4c04ef9c2d21aeed1ae2ee63dab

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 e863238d64a4b4443b8be53a08f6b94eda6ec1727038c330da02014f7c19e1be
MD5 c7cb0f84fe2b0df11e404417dbff1d1a
BLAKE2b-256 6a19b1e1c16895a36cc504bf7a940e88431b82b18ca10cbce81072860b9e3d60

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a47a95d7848e6fe768b55910bac8bb114c5f1f355f5a6590196d5e9bdf775d2f
MD5 9c70f7b51b3c29487bd75a1953caf472
BLAKE2b-256 e42bd8721b046a3c8bff494490a01ef1eeacf1f970f0d1274448856ccbe0475c

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 8fe178ac780a8bccf425a08004d853eae43b3ddcf7617521fb35c63550077b17
MD5 2e126a1740e727273fae3888fae82e2f
BLAKE2b-256 6260583a1ef8e2e259bdd1bf32fccd4ea15aef4aad5854746ec59cbb2462eb92

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0af63db45ba559e3e15180fbec140d8a4ff612d8f21d989181a4e8479fa3b8b6
MD5 0445003dd692a6f219d141c7253a5cad
BLAKE2b-256 32082c621ad782e9ff7f921c2244c6b4bcbc72ca756cb33021295c288123c465

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 d7921768712db156e6ec92ac21f7ce52069feb1fb994868d0ca795498111fbac
MD5 e2202bfae0fbe5c96f7add77ae2ac0de
BLAKE2b-256 6196e42b9ec38e1bbe9bf85a5fc9cc7feb173de5a874889735072b49a7d4d8d0

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp313-cp313-macosx_14_0_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp313-cp313-macosx_14_0_x86_64.whl
Algorithm Hash digest
SHA256 2f9135eea23c9b781574e0cadc5738cf5651a8fd8de822b6de1260411523bfd1
MD5 810eee7870af4b4903282853fa1b201c
BLAKE2b-256 3ec53e70e50c4c478acd3fefe3ea51b7e42ad661ce5a265a72b3dba175ce10fc

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.10

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 a92ebfc5df77fea57544f8ad2102bfc45af0e77ac4dfe98ed1b9628e8bba77c3
MD5 af1f1162227f8b8705e211f46efc0edd
BLAKE2b-256 9fadedce467c24529c536fc9de787546a1c8eca293009383a872b6f638d22eae

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 be7800ac4556d8920aaf8e4e2d89348aafd5d585642aabf9eeecb09a2659fbca
MD5 cb1f692aa4d9a3fa029909c86d908eb0
BLAKE2b-256 418ec3869928250e12ad9264da388bc70150a9de039e233b815a6a3bd2b8b8ae

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 a581e6c87a06371210184f64353055ff7c917d49363901ae0c527da139095082
MD5 fadb5da0034d50b2ceb12f6f09ea17f4
BLAKE2b-256 c6f9467c3f4682f3dbfbd7ff67f2307ed746a86b6dcc6b0b62cf1eeaebbd9d74

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e8bcf71a5016aeb24e597dc099564e8de809e0bc5d6af21e26422586aea26718
MD5 06b0a711812260e33b03462035fc2838
BLAKE2b-256 c717ee82c745c5bda340a4dd812652c42fb71efd45f663554a10c3ec45f230df

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 c10e27cb7a27b55f17e0df30c6b85e98c9672a7bdb7000a7509560eee7679137
MD5 203c8431d7cb7be28ceb4c84a5c05f7d
BLAKE2b-256 cdc8a04048143d0329ccd36403951746c1a6b5f1fc56c479e5a0a77efb2064b2

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 25adbeb0efd50d7ea4f07e5f5bd390a3c807df907f03efb86b018807c2c8cfbe
MD5 fa1a99a70e7bea8a2359956729f77ca4
BLAKE2b-256 10dc1c21715e1267ca29f562e4450426d1ff8a7ffcc3e670100cec332a105b95

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 0c45f663e40b3ed2e2320e7ae8d50fcf09b5ac72c5af4c66aa523e0045453311
MD5 70b2341056327717c9d0196969cb5c16
BLAKE2b-256 a3522237d72cf007e6c36367ab8a776388a9f13511e4cfa8a71b79101ad6e0fa

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 a8c92308165b632bc43dc39acee052180037a1209d4a57b5c3d10136a2f563a4
MD5 7f88101b066f3ae627e57b0ddce333e8
BLAKE2b-256 1ecdcd01bd7f4052d2ca336d67da4ecae4ffef34289ff408e8f654e14ee44b96

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 ede23c1aaacdbfd3b8fd192121b3024b41d00a97f2e9fc8f106be922ea05523d
MD5 cd715dc18de43c98d0a2a31f3c92d416
BLAKE2b-256 e84516b1719c489f734c76a6d9187f6dcdc41a1b923cd91c081aa0f4bedb923d

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 994dab68c193bea405a3a89a88b8703dd2c79bb790a330c8d459f0454cca71ef
MD5 19a7a100541b4c0e02afe5edf2711659
BLAKE2b-256 8b595e617916304022f5ad421459aa3f6e631537317d7a804c8128b32c6c29e6

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp311-cp311-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 11.1 MB
  • Tags: CPython 3.11, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8ae730ebc130461f743922f11d00c2d59a79492e57a1f5d245d4a6c731b7e334
MD5 44722761b74a0eccf7c0dea4d7dff8f3
BLAKE2b-256 084d2b2cc805f7db0636896b185dc8204556d363ccadbdca67e1a60e7aab4be6

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp311-cp311-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.8 MB
  • Tags: CPython 3.11, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a459b6ee9f99fc34861cbcf679a196af2d930ec70d95018a94f2e6dbe46c8c24
MD5 5d8d894c94b6fe960efb5c7c189c243a
BLAKE2b-256 c143f626c353802fb5ed37a087a0e41ad92246a1e1189869d47865853a980927

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 22d12b88190e047c0cedde165711222aa0dcdc325a229b876c36f746dd4a6f12
MD5 ffc99225c880d47233617b1922db4bd3
BLAKE2b-256 5b10429440cf9b841a5f8645f0aacc6a8da0a87cce4846d45e836f6b5f83be34

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 9eb704be0918f04691af1267107539222cc2277bca888fdc385733bcab30f734
MD5 d3580c41328fb456e31c9adb5b45b5ab
BLAKE2b-256 8991a68d87b421c4bfe936c756778d58c7220abd9292e8e2dac951a3e3f64505

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 32d9f88940464bffddfc0601fe3156ab16bf5a92393483e32342df0272fa64ce
MD5 4798a179a07b6baf7ff1d1a50f58abb2
BLAKE2b-256 ef673c577c9b4a09c3006e994a581fb540f48cf0378d8f3785cc1fe00fd48b87

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6874e1b9aa002f9d796da9d02bdca76b15aa3d4b2f83ca5064ac4c7894b92ece
MD5 a662b1c00676e39f65138c4afc77607d
BLAKE2b-256 416d98814860dbb9cdc27dcb6651b35124d7adca3bfe281f3351abb02a8a3f72

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp310-cp310-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 11.1 MB
  • Tags: CPython 3.10, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e3cd2db913b1cf64d84cdb7bc467a8a15adbd1f0f83a7a45a7167ad590f79408
MD5 b9810b46770dd9f7814e0be27bb3b9af
BLAKE2b-256 44b1b27dcf10dc6b61ffeb84bcf684d83ca90557b717d80b78a4758576c17010

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.8 MB
  • Tags: CPython 3.10, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cd4a1bba537a34808b92f1e793e3499029d339a7a2ab6d989f82e395b7b740ff
MD5 0a7e6e4ee05b30851e9d0988cd28487d
BLAKE2b-256 c2ab78b8dcaf31f034184c4d9051562631856212614f34b9246f694dfb3e105b

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f4ae2bc20a7d44657cc3ab1e2b80fa07ff3ebe0c1e0fa1f0b27b2ba693eb5072
MD5 8bb8515eea67afa8f5b6a6c5f26a4974
BLAKE2b-256 73d53f6bbdf913e6707b0ee93241060d50289cb1587b4d3036fb357e1882dad9

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 b68238b40b4ea88018f4cd82920903201ba0dbf4aae35264aaf7aef7e1752a41
MD5 c04319ba496c9ba45a4d1f7d575619c8
BLAKE2b-256 c81778f4940f60af5fc64b9bdfa918d8e647a090effe8401b6c3dbf93573fe5f

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 d4f2d79689d59a028a87c4cecc9a1f11d88da09025c3ab92d00c5457d4d7d916
MD5 41abd335c1c69ac10f746a73c7326181
BLAKE2b-256 7901f76f9f48822b4bd2cb65e480f46c8dd1ebf71ee2f8dcff29d495ba25b75c

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 098abd1d648d9e44f7ad55542b3b7f978b82280f4332ad80a937db6fbe274600
MD5 0aa4511c5a42021c29c998ba399b7e11
BLAKE2b-256 0039c8186f7d674d60ea1ff0e6e32bd867fc65c60d03fca73cd8a48af1415754

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 11.1 MB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8157ef551c80b4745b786d0d8ae5cc222824482fb8596ce271bf49b707d38577
MD5 65a338e932a785ceca9757fa0cdedfd1
BLAKE2b-256 3e690cae7accc45e61fd5479c9cf140c31d63c2521ec83c4204582031660bb66

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.8 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e2ec16afa3e953159e148b7470159e415108aadb8bb1815baaea2e37ad7e1d8c
MD5 9b99c6491e2671ef6ab9de0f85ed9758
BLAKE2b-256 740f297db0387cc75ea2370d360d62853826d1ddf92e1729fd48ca11d7bb1e53

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 12.8 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 f88dd546d91eb9e0974eee477b76077d001eeeb7b819d8801eb6065376d7d527
MD5 d707f0569e1fd5d1a8066deb1c88ef19
BLAKE2b-256 c1f0f45dc18887e4ed0258f89303b4e317b85d66a4cf31eed53194d27ad85e50

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp38-cp38-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp38-cp38-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 de81f1ff5a8b0083f8c2b577eba212244bbffa5e69c7b97cc305b1d1f9d7af79
MD5 819e239c560554708ba6085409f666c3
BLAKE2b-256 78756352429e026b0edec409b28ec03a7e529e1346e79721e6dd1b9b590939e1

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp38-cp38-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp38-cp38-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 d16c65048e88f73d576ddb6681b5d32d90e134d2459aadde0d3fe6c7d92f6823
MD5 23e5159f829e4cd35d00a651cbccf01f
BLAKE2b-256 4e5ba6fb0ece14906c237b4bdf988162c44e2eefefb6f56d6e50564fd9685035

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 45e702d4649d2d4e73fcd8f244aa5734a04d2b1a3fa3e7c0bff1ab578bf5061e
MD5 9379146f2097757cdc7c893b88cec7f1
BLAKE2b-256 fe602002714a08b548f5828d8ae4ca15ccde4d3b82c172d346de174526cfc1ba

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.8 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c237b57845b1e4ac00c012581cde099cd71a91434c117fec763bb4bf5b22601b
MD5 229f395dec835559e13647e34c735df7
BLAKE2b-256 9e9aa1075147563fa69b6e19446a884a38ae278bb2b9abc5285c748ff0c43e62

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp37-cp37m-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp37-cp37m-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 34dca767c9073dd05c2d8144f40b1edcaa28f222f8b804f5c8ba0863d8c75516
MD5 39c6debcd3fd73348c0de6613cc48fc5
BLAKE2b-256 1a05e9015e61e3497aae4b8035edeae4ad0404c43bf103076c58dc2f2d6f31ae

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp37-cp37m-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp37-cp37m-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 d417981fc9b66e63001a2ebc2861138042fa3d865af9b974f27508107a207cf1
MD5 afd8120e8e096bb7b269a9c355f15ab2
BLAKE2b-256 b480b899f2479a279ac7a272f482d36bb5494cdbd5e00c0c27b689f1ca217a79

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a075e333916da7fc941b36a4f189b88acd291f1d861d97ba876626c277b3e575
MD5 9ecc6e10396fdb8d4a2510ef6a5293ad
BLAKE2b-256 11aeafdcb644b5e9b50fb3a24aa59d3ba12b228600065488a4fe4f5adeac8420

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.8 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6e14c47766b39e97142b163ba218b955cd5c47d19d9bd01b01e0909102b43384
MD5 341c39b6c9094aa1ac96220028fc544a
BLAKE2b-256 eca960c61ed857477c6640efa86b8a4a647aeebcd1ef157aa8e7a6db684c5dd9

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp36-cp36m-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp36-cp36m-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 46d9ed199b0bcb35f88627378e0592b0cc39729c58cb3bb8a7a24a0c27bd1742
MD5 9bfdb26529d8807fa4bbb63b1330098a
BLAKE2b-256 6e127333c3c9e1e3f2aef06af7dac094b4234b7b1be42faeefb16726dd95ffa0

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp36-cp36m-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for cvxopt-1.3.2-cp36-cp36m-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 4a778ffd95a68220d0dcb976c9086d3585d10d51f6fb82a635b6a5cfffa79369
MD5 8459329527f24727031528fc0b32c2a8
BLAKE2b-256 6f939adaa0b6ef706a66ee80307f866efc9c5a347a57e1f6364861eb32e18564

See more details on using hashes here.

File details

Details for the file cvxopt-1.3.2-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: cvxopt-1.3.2-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 13.9 MB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.9.6 requests/2.29.0 setuptools/59.8.0 requests-toolbelt/1.0.0 tqdm/4.65.0 CPython/3.7.12

File hashes

Hashes for cvxopt-1.3.2-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dcc0c091977b9211ad5086d0dfcc8748a4be3a37b0456c93d11a5d8fe15219e8
MD5 2091edb484047a5155e8b5fa137b0f13
BLAKE2b-256 7ad07fe38e7d774bf5bf7ccb874092373cd4d42571ed48ad67b7988d563108fc

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page