cvxopt

Convex optimization package

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Development Status
- 5 - Production/Stable
Intended Audience
- Science/Research
License
- OSI Approved :: GNU General Public License v3 (GPLv3)
Operating System
- OS Independent
Programming Language
- C
- Python
- Python :: 3
Topic
- Scientific/Engineering

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

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Development Status
- 5 - Production/Stable
Intended Audience
- Science/Research
License
- OSI Approved :: GNU General Public License v3 (GPLv3)
Operating System
- OS Independent
Programming Language
- C
- Python
- Python :: 3
Topic
- Scientific/Engineering

Release history Release notifications | RSS feed

1.3.2

Aug 9, 2023

1.3.1

May 10, 2023

This version

1.3.0.1

Mar 30, 2023

1.3.0

Mar 8, 2022

1.2.7

Sep 20, 2021

1.2.6

Feb 19, 2021

1.2.5.post1

Oct 10, 2020

1.2.5

Apr 17, 2020

1.2.4

Jan 22, 2020

1.2.3

Feb 5, 2019

1.2.2

Oct 19, 2018

1.2.1

Aug 31, 2018

1.2.0

Apr 17, 2018

1.1.9

Nov 30, 2016

1.1.8

Sep 22, 2015

1.1.7

Jun 4, 2014

1.1.6

Feb 21, 2014

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

cvxopt-1.3.0.1-cp311-cp311-win_amd64.whl (12.8 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.11 Windows x86-64

cvxopt-1.3.0.1-cp311-cp311-win32.whl (7.4 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.11 Windows x86

cvxopt-1.3.0.1-cp310-cp310-win_amd64.whl (12.8 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.10 Windows x86-64

cvxopt-1.3.0.1-cp310-cp310-win32.whl (7.4 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.10 Windows x86

cvxopt-1.3.0.1-cp39-cp39-win_amd64.whl (12.8 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.9 Windows x86-64

cvxopt-1.3.0.1-cp39-cp39-win32.whl (7.4 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.9 Windows x86

cvxopt-1.3.0.1-cp38-cp38-win_amd64.whl (12.8 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.8 Windows x86-64

cvxopt-1.3.0.1-cp38-cp38-win32.whl (7.4 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.8 Windows x86

cvxopt-1.3.0.1-cp37-cp37m-win_amd64.whl (12.8 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.7m Windows x86-64

cvxopt-1.3.0.1-cp37-cp37m-win32.whl (7.4 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.7m Windows x86

cvxopt-1.3.0.1-cp36-cp36m-win_amd64.whl (12.9 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.6m Windows x86-64

cvxopt-1.3.0.1-cp36-cp36m-win32.whl (7.5 MB view hashes)

Uploaded Mar 30, 2023 CPython 3.6m Windows x86

Hashes for cvxopt-1.3.0.1-cp311-cp311-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp311-cp311-win_amd64.whl
Algorithm	Hash digest
SHA256	`a43aee498e47f2acb4eaffd2405da2a54915019bf09951d412f0deb0906383e9`
MD5	`66c053574e065ea988cb8ff10310711b`
BLAKE2b-256	`a46016d2334e45712ba30ed20f8fdded8521525d9a98c45049f31be39518ec17`

Hashes for cvxopt-1.3.0.1-cp311-cp311-win32.whl

Hashes for cvxopt-1.3.0.1-cp311-cp311-win32.whl
Algorithm	Hash digest
SHA256	`3be9cca4538346abc2d3534a8667b3e03e047067cbc8d7cf2ae3fa81b4da619b`
MD5	`0fc2f439dfcb6194dc5ddd44fa8f5a44`
BLAKE2b-256	`fa014660316b1a1da62f8ba75105e93ef841a478cd3b2819c054040ab081baf4`

Hashes for cvxopt-1.3.0.1-cp310-cp310-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp310-cp310-win_amd64.whl
Algorithm	Hash digest
SHA256	`eddb2c1ee863c7dd7edd3401cdb036c9c8d7779e2b1fe434b34b8d2b04bcebfc`
MD5	`430a7fca1e70f1596a7f643a88bf25e7`
BLAKE2b-256	`35b91aaf723ecb7e78ea9531396d1a2b86bd0035cf1451af9c24044fe7ddd04f`

Hashes for cvxopt-1.3.0.1-cp310-cp310-win32.whl

Hashes for cvxopt-1.3.0.1-cp310-cp310-win32.whl
Algorithm	Hash digest
SHA256	`429895c9cdd33b97ba1354b1d7a9d73c7179934d8649920a64d1d114062695dc`
MD5	`8238671d7dad27cce3b6693cba370ba9`
BLAKE2b-256	`d6b10a13c42ac6411c5bcd453b080a93e66d23e0bbef6c3da2dccc611c70ce12`

Hashes for cvxopt-1.3.0.1-cp39-cp39-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`f5acf720235014d69e4ee68a7682f2fef7ef30c705933d9b758c2edffd2a5bcf`
MD5	`4cef420d5db564aea4202ec7b3538ef0`
BLAKE2b-256	`0f6ac10dac3e2b06f02fc909274fea210c972ca8367d9ffe005e533f36408519`

Hashes for cvxopt-1.3.0.1-cp39-cp39-win32.whl

Hashes for cvxopt-1.3.0.1-cp39-cp39-win32.whl
Algorithm	Hash digest
SHA256	`d1bbc011d5d83c913972e1bd30358f4fa56defa0be13fea956612ff2168f2b91`
MD5	`7b6a5846adae6a3f9d83fb1625226743`
BLAKE2b-256	`26b18a0ed9fadcc28f9daa84f567e3df79f1384a0ed491e1a7866be2cae2b515`

Hashes for cvxopt-1.3.0.1-cp38-cp38-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`517554aa443a4818d9fe01e73f8bd420b6acad0086019d0b03469d2a8810f21e`
MD5	`2af66f4a8b10fda5c186009d6e9c2be3`
BLAKE2b-256	`ed2a20ea8c6df971eb09ae5ac88eb26d3697dd173d99ce37009051678cf2b101`

Hashes for cvxopt-1.3.0.1-cp38-cp38-win32.whl

Hashes for cvxopt-1.3.0.1-cp38-cp38-win32.whl
Algorithm	Hash digest
SHA256	`615e947e2c9ff74dc4b0dbede6414e1f6106590bc3caa52c690cdc2bcd6e4569`
MD5	`92f9d2c0a523b9022a3e02e924d08b94`
BLAKE2b-256	`5457ab59a32fae32ce0740fae1dbc6d640c98645a2110d4ab3d82eff4fa397b2`

Hashes for cvxopt-1.3.0.1-cp37-cp37m-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`9e9219e8fb0af22013c150dfbd6e38167b38f61bc2e0d269d19b6137772055a9`
MD5	`f9fc1db8ac8043a5dea22d5f047fdab9`
BLAKE2b-256	`7e822f1705c22bd4c34d98591ddc53413b534c7be62b11e0bb028721667284cc`

Hashes for cvxopt-1.3.0.1-cp37-cp37m-win32.whl

Hashes for cvxopt-1.3.0.1-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`77ac45a262c767cb1d614e51672821edf260af6798370b05a07e0181c80a52e2`
MD5	`a7a0f516e6dc2c03ad2d68b85d5de3c9`
BLAKE2b-256	`dc133e57fa7eb328e73ce75cd980a666dbab7c1f8243f0403be3308ee3b95cd9`

Hashes for cvxopt-1.3.0.1-cp36-cp36m-win_amd64.whl

Hashes for cvxopt-1.3.0.1-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`122e805decffbdd104d9096b8b21f0ce35ba7b5e8b961f3f23eb9b7fe1cdbec5`
MD5	`776b1438fa643bb151b8d306626c3331`
BLAKE2b-256	`f180f8aedcab25b31b121b669fa729dc94e32bb026b558451a8491b7c6ad0d02`

Hashes for cvxopt-1.3.0.1-cp36-cp36m-win32.whl

Hashes for cvxopt-1.3.0.1-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`34c5d6fe2af6a5b1aa2bbaebb3880152923717eca699b8689052d1439c15dd71`
MD5	`851f8876ffd177fa93d0b3539d039fc9`
BLAKE2b-256	`027186fcf0ef8d92f65adb019dff1345a86b4ee46051ff6f9116699be865b394`