passagemath-glpk

passagemath: Linear and mixed integer linear optimization backend using GLPK

These details have not been verified by PyPI

Project links

Project description

passagemath is open source mathematical software in Python, released under the GNU General Public Licence GPLv2+.

It is a fork of SageMath, which has been developed 2005-2025 under the motto “Creating a Viable Open Source Alternative to Magma, Maple, Mathematica, and MATLAB”.

The passagemath fork uses the motto “Creating a Free Passage Between the Scientific Python Ecosystem and Mathematical Software Communities.” It was created in October 2024 with the following goals:

providing modularized installation with pip,
establishing first-class membership in the scientific Python ecosystem,
giving clear attribution of upstream projects,
providing independently usable Python interfaces to upstream libraries,
offering platform portability and integration testing services to upstream projects,
inviting collaborations with upstream projects,
building a professional, respectful, inclusive community,
empowering Sage users to participate in the scientific Python ecosystem by publishing packages,
developing a port to Pyodide for serverless deployment with Javascript,
developing a native Windows port.

Full documentation is available online.

passagemath attempts to support and provides binary wheels suitable for all major Linux distributions and recent versions of macOS.

Binary wheels for native Windows (x86_64) are are available for a subset of the passagemath distributions. Use of the full functionality of passagemath on Windows currently requires the use of Windows Subsystem for Linux (WSL) or virtualization.

The supported Python versions in the passagemath 10.6.x series are 3.10.x-3.14.x.

About this pip-installable distribution package

This pip-installable distribution passagemath-glpk provides a backend for linear and mixed integer linear optimization backend using GLPK.

It can be installed as an extra of the distribution sagemath-polyhedra:

$ pip install "passagemath-polyhedra[glpk]"

What is included

GLPK backends for LP, MILP, and graphs

Project details

These details have not been verified by PyPI

Project links

Release history Release notifications | RSS feed

10.8.3

Mar 30, 2026

10.8.3rc3 pre-release

Mar 28, 2026

10.8.3rc2 pre-release

Mar 26, 2026

10.8.3rc1 pre-release

Mar 25, 2026

10.8.3rc0 pre-release

Mar 23, 2026

10.8.2

Mar 10, 2026

10.8.2rc4 pre-release

Mar 8, 2026

10.8.2rc3 pre-release

Mar 6, 2026

10.8.2rc2 pre-release

Mar 3, 2026

10.8.2rc1 pre-release

Mar 2, 2026

10.8.2rc0 pre-release

Mar 1, 2026

10.8.1

Feb 8, 2026

10.8.1rc3 pre-release

Feb 6, 2026

10.8.1rc2 pre-release

Feb 4, 2026

10.8.1rc1 pre-release

Feb 3, 2026

10.8.1rc0 pre-release

Feb 1, 2026

10.8.1a4 pre-release

Jan 31, 2026

10.8.1a3 pre-release

Jan 28, 2026

10.8.1a2 pre-release

Jan 25, 2026

10.8.1a1 pre-release

Jan 24, 2026

10.6.48

Feb 2, 2026

10.6.47

Jan 15, 2026

10.6.46

Jan 12, 2026

10.6.45

Jan 8, 2026

10.6.44

Jan 5, 2026

This version

10.6.43

Jan 1, 2026

10.6.42

Dec 13, 2025

10.6.41

Dec 11, 2025

10.6.40

Dec 6, 2025

10.6.39

Nov 29, 2025

10.6.38

Nov 24, 2025

10.6.37

Nov 19, 2025

10.6.36

Nov 15, 2025

10.6.35

Nov 13, 2025

10.6.34

Nov 10, 2025

10.6.33

Nov 7, 2025

10.6.32

Nov 4, 2025

10.6.31

Oct 31, 2025

10.6.31rc3 pre-release

Oct 23, 2025

10.6.31rc2 pre-release

Oct 21, 2025

10.6.31rc1 pre-release

Oct 15, 2025

10.6.30

Oct 5, 2025

10.6.29

Sep 29, 2025

10.6.28

Sep 23, 2025

10.6.27

Sep 22, 2025

10.6.26

Sep 21, 2025

10.6.25

Sep 19, 2025

10.6.24

Sep 16, 2025

10.6.23

Sep 15, 2025

10.6.22

Sep 14, 2025

10.6.21

Sep 13, 2025

10.6.20

Sep 11, 2025

10.6.19

Sep 10, 2025

10.6.18

Sep 9, 2025

10.6.17

Sep 7, 2025

10.6.16

Sep 6, 2025

10.6.15

Sep 4, 2025

10.6.14

Sep 2, 2025

10.6.13

Aug 31, 2025

10.6.12

Aug 29, 2025

10.6.11

Aug 28, 2025

10.6.10

Aug 27, 2025

10.6.9

Aug 26, 2025

10.6.8

Aug 24, 2025

10.6.7

Aug 21, 2025

10.6.6

Aug 20, 2025

10.6.5

Aug 17, 2025

10.6.4

Aug 12, 2025

10.6.3

Aug 10, 2025

10.6.2

Aug 8, 2025

10.6.1

Jul 31, 2025

10.6.1rc15 pre-release

Jul 29, 2025

10.6.1rc14 pre-release

Jul 28, 2025

10.6.1rc13 pre-release

Jul 27, 2025

10.6.1rc12 pre-release

Jul 26, 2025

10.6.1rc11 pre-release

Jul 25, 2025

10.6.1rc10 pre-release

Jul 23, 2025

10.6.1rc9 pre-release

Jul 21, 2025

10.6.1rc8 pre-release

Jul 19, 2025

10.6.1rc7 pre-release

Jul 16, 2025

10.6.1rc6 pre-release

Jul 12, 2025

10.6.1rc5 pre-release

Jul 8, 2025

10.6.1rc4 pre-release

Jun 30, 2025

10.6.1rc3 pre-release

Jun 28, 2025

10.6.1rc2 pre-release

Jun 25, 2025

10.6.1rc1 pre-release

Jun 20, 2025

10.5.49

Nov 1, 2025

10.5.48

Jul 24, 2025

10.5.47

Jul 20, 2025

10.5.46

Jul 15, 2025

10.5.45

Jul 5, 2025

10.5.44

Jun 28, 2025

10.5.43

Jun 19, 2025

10.5.42

Jun 16, 2025

10.5.41

Jun 5, 2025

10.5.40

May 27, 2025

10.5.39

May 25, 2025

10.5.38

May 22, 2025

10.5.37

May 21, 2025

10.5.36

May 20, 2025

10.5.35

May 19, 2025

10.5.34

May 17, 2025

10.5.33

May 13, 2025

10.5.32

May 10, 2025

10.5.31

May 7, 2025

10.5.30

May 5, 2025

10.5.29

May 2, 2025

10.5.28

Apr 30, 2025

10.5.27

Apr 27, 2025

10.5.26

Apr 26, 2025

10.5.25

Apr 23, 2025

10.5.24

Apr 22, 2025

10.5.23

Apr 2, 2025

10.5.22

Jan 21, 2025

10.5.21

Jan 20, 2025

10.5.20

Jan 12, 2025

10.5.19

Jan 9, 2025

10.5.18

Jan 5, 2025

10.5.17

Jan 1, 2025

10.5.16

Dec 31, 2024

10.5.15

Dec 30, 2024

10.5.14

Dec 29, 2024

10.5.13

Dec 26, 2024

10.5.12

Dec 23, 2024

10.5.10

Dec 18, 2024

10.5.9

Dec 17, 2024

10.5.8

Dec 16, 2024

10.5.7

Dec 14, 2024

10.5.6

Dec 12, 2024

10.5.5

Dec 12, 2024

10.5.2

Dec 7, 2024

10.5.1

Dec 5, 2024

10.4.68

Dec 2, 2024

10.4.67

Nov 29, 2024

10.4.66

Nov 26, 2024

10.4.65

Nov 23, 2024

10.4.36

Oct 30, 2024

10.4.31

Oct 27, 2024

10.4.30

Oct 26, 2024

10.4.29

Oct 25, 2024

10.4.22

Oct 22, 2024

10.4.21

Oct 21, 2024

10.4.17

Oct 20, 2024

10.4.16

Oct 19, 2024

10.4.15

Oct 19, 2024

10.4.14

Oct 19, 2024

10.4.8

Oct 18, 2024

10.4.7

Oct 17, 2024

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Algorithm	Hash digest
SHA256	`8611062138bf897e8273979193c65a011424e8fb814b7a8babfbfa684acd798c`
MD5	`66ccb340c20b480e3b1fa72e26cadfb7`
BLAKE2b-256	`fe4eb956a047a848515d3cbf314ac46dc686149b1fcd22a9cca459124cd59018`

Algorithm	Hash digest
SHA256	`59cacdfebee9e4bdd76aaaf592e7d52ebdee042246d28d65e167e07fb68c0c0c`
MD5	`2a7445629d4dc34077d50e776c7e2849`
BLAKE2b-256	`5e748ce304bd53e84b29b190bc032c11aa58210d0168cd6c7894d68b4b20c442`

Algorithm	Hash digest
SHA256	`8068c47fdbea29cf47d99ae260906eaf72d0a19c02acca6165193cfe55bba923`
MD5	`10a82c54b204da96efc635b2dd0e0fc5`
BLAKE2b-256	`db66a28dcf5eda438b402698f2dd97b2c45842bc139c1775d4ece13d3f59da2b`

Algorithm	Hash digest
SHA256	`9374327354d7d2c746547d4585a9df3da30889e27a359599bfa2e34626b023f9`
MD5	`ef8aa679ebfb51be4f71fa03a870bbba`
BLAKE2b-256	`71aeaf5dbb8f07a47e80c6588db840a6d9e1994e83d4b3bcd90e6e8fe268c489`

Algorithm	Hash digest
SHA256	`e448d31f73db1d0d4942c3e515533c296e6cfc5a403843f00c5652fe879f9f05`
MD5	`72b3b50071593d4484a27b8421e2e48d`
BLAKE2b-256	`ee9a2f614a2d191f892cfd2e45425a153c4788bb7cea65f0d331f76fecb44306`

Algorithm	Hash digest
SHA256	`85daa04eeba5865e41f3c9b08e5b29dac93a616b9416702993f3eda3e70af31e`
MD5	`4051b98bc808053cdffc3ed4cbc85c4a`
BLAKE2b-256	`4bbbef174d5a13aa2d25a59aa35f1970305e856c6e984f131b70864fe2038a38`

Algorithm	Hash digest
SHA256	`76028e7dea3eb0c99f3037d32aa9b9d656b292b5bcbe879fa9edb4e8bd9de414`
MD5	`873afd755da7d19255eb6e40456b311e`
BLAKE2b-256	`647fd6243b77e25d372ef10fc21cc032f0e6c37cd423c6fee73f8856b6acdbc4`

Algorithm	Hash digest
SHA256	`87346125752c60d8bb3f485e20a07041531f8df60a1be2e7b91e4abaf0baf1d0`
MD5	`a625d6074862bf414f4b5b8de2f9f5d5`
BLAKE2b-256	`eed8f4b9f36aea395167b0dc1ffb914af1947a0b4e6f67f035e84a18e072ee83`

passagemath-glpk 10.6.43

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Algorithm	Hash digest
SHA256	`4b63cb0c065caaf13019252bfb0bc78773db52adae9a43bad3a5b8ebfe6f7be6`
MD5	`aee945eec9d53791537e5a9030ea5e02`
BLAKE2b-256	`5c6032695c58071a0428223ad6b2853b1edf234200c18ea4aa7c90b8d73f338e`

Algorithm	Hash digest
SHA256	`e729c9986fea2f8b964e3c74a0c67a7c68d7a3a6f16486f53e4b66a650094715`
MD5	`4c5aef6a47a59bff6a1d9e7beb2a0e1a`
BLAKE2b-256	`edb51117efb918492c05bad2943ccc64b7a82b5c2736661e4af39c3310e69c32`

Algorithm	Hash digest
SHA256	`fa37cbc497a474410f6b991659bf74d8c514822e81eecb3b8e9aa922a0272779`
MD5	`7968d94734de8fafa4ca4146f88197c9`
BLAKE2b-256	`3cebeb242bdb1f482898deca0803892dc781a840417c436f94c9963d5c210a6e`

Algorithm	Hash digest
SHA256	`33bd0c0302a3b31374235296549e7b7d5f233f72e7759f3e3111c4d7c7f4998a`
MD5	`59d496a78ec8fe03c17335855f770d4e`
BLAKE2b-256	`9fd1e23bab54e66d14ec6f67bd0561bf196d05f9657e448df30302e28816d96c`

Algorithm	Hash digest
SHA256	`5bf01dbb55375da5b8c489c60bee1262ea2dacc7f63841c5146894fcfdebb7cc`
MD5	`aa4495cc52cc762500d79add0406ef68`
BLAKE2b-256	`8e2d8781795cc7ba7e5a0d2b0d4fab4f93ed8f81a477b1aa385dabebfe9de66e`

Algorithm	Hash digest
SHA256	`94fc5f5e651323eca4acb2ebb77f80b51672f96914387b005f1d23291c434660`
MD5	`bba374e0204da6018cfa4c65c30cc787`
BLAKE2b-256	`03b7577ca0b7ba3b322b30df73dfaf92a510cd7e5aca25fa8238445c831517bb`

Algorithm	Hash digest
SHA256	`3359641d0c647c8329646f27b59f081a342fd49d2cc86ff20b30f61cde64d31f`
MD5	`fef326472f6a1d3787d2e63062994317`
BLAKE2b-256	`b3471cf4ff848584360e3e1dc414bc35429c42c777ff605ddf4d04ce5c0bb6e6`

Algorithm	Hash digest
SHA256	`65dbc05ad77d93b1acfd842302c2e3900afa24c58af766ceed6bbc8245119587`
MD5	`4e495db79c4831b6c02e4267312d2014`
BLAKE2b-256	`690d1f0ef0c633b5ddd887b88d430f018d43c690f34ba9d3b00ff5a85b8cf9c0`

Algorithm	Hash digest
SHA256	`404a6ee35e0e004e5709754880c34ccda893134efc9e75facffcbb9980f3eeee`
MD5	`9ad10f6b9832ae5cba3099bb45d54efc`
BLAKE2b-256	`dc3de4380171adb5ce5a58364ebd72ff2859b93cf72c797a6aa0cfc1112f184c`

Algorithm	Hash digest
SHA256	`cee682f23c74b4b87d51f0a770c043190f1e3348e83717f780dae138bca7b64e`
MD5	`51668141a8bdcccf54e6a2a8fa575e85`
BLAKE2b-256	`8733fcf3d7c91ca4bfd3994e10493faca716920541aed5953cf10a6f3a6a316a`