Skip to main content

swiglpk - Simple swig bindings for the GNU Linear Programming Kit

Project description

Plain python bindings for the GNU Linear Programming Kit (GLPK)

PyPI License Build Status

Why?

swiglpk is not a high-level wrapper for GLPK (take a look at optlang if you are interested in a python-based mathematical programming language). It just provides plain vanilla swig bindings to the underlying C library. In constrast to other GLPK wrappers for python (e.g. PyGLPK, Python-GLPK, ctypes-glpk, ecyglpki etc.) it is fairly version agnostic: it will try to guess the location of the glpk.h header file (using which glpsol) and then compile the extension for your particular GLPK installation. Furthermore, swiglpk provides binary wheels for all major platforms, which are always up-to-date with the most recent GLPK version (swiglpk versions follow GLPK versioning in the major and minor version digits to emphasize that).

Please show us some love by staring this repo if you find swiglpk useful!

Installation

pip install swiglpk

That’s it. swiglpk comes with binary wheels for Windows, Mac, and Linux. No installation of third-party dependencies necessary.

Example

Running the following (slightly adapted) example from the GLPK manual

from swiglpk import *

ia = intArray(1+1000); ja = intArray(1+1000);
ar = doubleArray(1+1000);
lp = glp_create_prob();
glp_set_prob_name(lp, "sample");
glp_set_obj_dir(lp, GLP_MAX);
glp_add_rows(lp, 3);
glp_set_row_name(lp, 1, "p");
glp_set_row_bnds(lp, 1, GLP_UP, 0.0, 100.0);
glp_set_row_name(lp, 2, "q");
glp_set_row_bnds(lp, 2, GLP_UP, 0.0, 600.0);
glp_set_row_name(lp, 3, "r");
glp_set_row_bnds(lp, 3, GLP_UP, 0.0, 300.0);
glp_add_cols(lp, 3);
glp_set_col_name(lp, 1, "x1");
glp_set_col_bnds(lp, 1, GLP_LO, 0.0, 0.0);
glp_set_obj_coef(lp, 1, 10.0);
glp_set_col_name(lp, 2, "x2");
glp_set_col_bnds(lp, 2, GLP_LO, 0.0, 0.0);
glp_set_obj_coef(lp, 2, 6.0);
glp_set_col_name(lp, 3, "x3");
glp_set_col_bnds(lp, 3, GLP_LO, 0.0, 0.0);
glp_set_obj_coef(lp, 3, 4.0);
ia[1] = 1; ja[1] = 1; ar[1] = 1.0; # a[1,1] = 1
ia[2] = 1; ja[2] = 2; ar[2] = 1.0; # a[1,2] = 1
ia[3] = 1; ja[3] = 3; ar[3] = 1.0; # a[1,3] = 1
ia[4] = 2; ja[4] = 1; ar[4] = 10.0; # a[2,1] = 10
ia[5] = 3; ja[5] = 1; ar[5] = 2.0; # a[3,1] = 2
ia[6] = 2; ja[6] = 2; ar[6] = 4.0; # a[2,2] = 4
ia[7] = 3; ja[7] = 2; ar[7] = 2.0; # a[3,2] = 2
ia[8] = 2; ja[8] = 3; ar[8] = 5.0; # a[2,3] = 5
ia[9] = 3; ja[9] = 3; ar[9] = 6.0; # a[3,3] = 6
glp_load_matrix(lp, 9, ia, ja, ar);
glp_simplex(lp, None);
Z = glp_get_obj_val(lp);
x1 = glp_get_col_prim(lp, 1);
x2 = glp_get_col_prim(lp, 2);
x3 = glp_get_col_prim(lp, 3);
print("\nZ = %g; x1 = %g; x2 = %g; x3 = %g\n" % (Z, x1, x2, x3))
glp_delete_prob(lp);

… will produce the following output (the example can also be found at examples/example.py):

GLPK Simplex Optimizer, v4.52
3 rows, 3 columns, 9 non-zeros
*     0: obj =   0.000000000e+00  infeas =  0.000e+00 (0)
*     2: obj =   7.333333333e+02  infeas =  0.000e+00 (0)
OPTIMAL LP SOLUTION FOUND

Z = 733.333; x1 = 33.3333; x2 = 66.6667; x3 = 0

Pretty ugly right? Consider using optlang for formulating and solving your optimization problems.

Documentation

You can find documentation on GLPK’s C API here

Development

You still want to install it from source? Then you’ll need to install the following dependencies first.

  • GLPK

  • swig

If you’re on OS X, swig and GLPK can easily be installed with homebrew.

brew install swig glpk

If you’re using ubuntu linux, you can install swig and GLPK using apt-get.

apt-get install glpk-utils libglpk-dev swig

If you’re on Windows, you are on your own (checkout the appveyor.yml config file for directions).

Then clone the repo and run the following.

python setup.py install

Project details


Download files

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

Source Distribution

swiglpk-5.0.8.tar.gz (21.5 kB view details)

Uploaded Source

Built Distributions

swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (1.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

swiglpk-5.0.8-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (770.0 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (1.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

swiglpk-5.0.8-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (770.6 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (1.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

swiglpk-5.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (770.0 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

swiglpk-5.0.8-cp311-cp311-win_amd64.whl (571.1 kB view details)

Uploaded CPython 3.11 Windows x86-64

swiglpk-5.0.8-cp311-cp311-win32.whl (461.7 kB view details)

Uploaded CPython 3.11 Windows x86

swiglpk-5.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

swiglpk-5.0.8-cp311-cp311-macosx_11_0_arm64.whl (737.8 kB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

swiglpk-5.0.8-cp311-cp311-macosx_10_9_x86_64.whl (780.0 kB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

swiglpk-5.0.8-cp310-cp310-win_amd64.whl (571.1 kB view details)

Uploaded CPython 3.10 Windows x86-64

swiglpk-5.0.8-cp310-cp310-win32.whl (461.7 kB view details)

Uploaded CPython 3.10 Windows x86

swiglpk-5.0.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

swiglpk-5.0.8-cp310-cp310-macosx_11_0_arm64.whl (737.8 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

swiglpk-5.0.8-cp310-cp310-macosx_10_9_x86_64.whl (780.0 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

swiglpk-5.0.8-cp39-cp39-win_amd64.whl (571.1 kB view details)

Uploaded CPython 3.9 Windows x86-64

swiglpk-5.0.8-cp39-cp39-win32.whl (461.9 kB view details)

Uploaded CPython 3.9 Windows x86

swiglpk-5.0.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

swiglpk-5.0.8-cp39-cp39-macosx_11_0_arm64.whl (737.8 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

swiglpk-5.0.8-cp39-cp39-macosx_10_9_x86_64.whl (780.0 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

swiglpk-5.0.8-cp38-cp38-win_amd64.whl (570.7 kB view details)

Uploaded CPython 3.8 Windows x86-64

swiglpk-5.0.8-cp38-cp38-win32.whl (461.7 kB view details)

Uploaded CPython 3.8 Windows x86

swiglpk-5.0.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

swiglpk-5.0.8-cp38-cp38-macosx_11_0_arm64.whl (738.0 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

swiglpk-5.0.8-cp38-cp38-macosx_10_9_x86_64.whl (780.2 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

swiglpk-5.0.8-cp37-cp37m-win_amd64.whl (569.8 kB view details)

Uploaded CPython 3.7m Windows x86-64

swiglpk-5.0.8-cp37-cp37m-win32.whl (461.7 kB view details)

Uploaded CPython 3.7m Windows x86

swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

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

swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp37-cp37m-macosx_10_9_x86_64.whl (779.9 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

swiglpk-5.0.8-cp36-cp36m-win_amd64.whl (580.1 kB view details)

Uploaded CPython 3.6m Windows x86-64

swiglpk-5.0.8-cp36-cp36m-win32.whl (468.5 kB view details)

Uploaded CPython 3.6m Windows x86

swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686

swiglpk-5.0.8-cp36-cp36m-macosx_10_9_x86_64.whl (779.9 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file swiglpk-5.0.8.tar.gz.

File metadata

  • Download URL: swiglpk-5.0.8.tar.gz
  • Upload date:
  • Size: 21.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8.tar.gz
Algorithm Hash digest
SHA256 9b933d7ba17c619f5d838b6b3216647bcf8a2e22cd67ea89b0f2e2f50f7be0ae
MD5 bd3792d104af594c668905562caec800
BLAKE2b-256 1ec519eb970b1ccbc048e76960cb608726b52dd4826eabebb335333a458154c9

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ca59c82113364c68e37a3a4540446393345ba711d15c9c1b6df52d7a0196b2ec
MD5 3cd52172197aaf61ed2bb0de670abe08
BLAKE2b-256 686f2caacd17c05426dfdcb9dd5934ef33c9754a856b13e17467280a2068de1d

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9786898afcc639ea1324f4cb3d62f246618272ce09dfea021ee73381bbb788c1
MD5 519f96de6e0b07111fdbc401a67d38bc
BLAKE2b-256 b5acb5a399400b8d3ac4a96c85c9c4a8bb9eaa55a399902523eb8f65a13c5e4f

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f98d49bb844bf302358d47d38a53e63f70370548b63fc826c84be78ecd622b73
MD5 25e1b2d73f01a8064ec7a0ae7682b171
BLAKE2b-256 9a30a0eb4d3f472c18efc02bc1778db91a3e910d0e735cacc7671bd74d7a10cc

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 93fdf619f802de590f3be5a454fd89b23bb22562e4d775553b4bd8689c3301c6
MD5 652b125f66f9acbfbc2995e2a20a406c
BLAKE2b-256 8f473fd5b1ad05fc8544c9c4832857ac04554638fd9f2e9f5330e769eb44c895

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 fbeb878a5333adbf85f0469d9a87c4468d4c7de561a5994e8d85acf260c3cf9b
MD5 4c34476dc4741322a2f7ebcf638a7c32
BLAKE2b-256 66f7a393cd20b3738096c7e877e5e146f5c5edc3f42cc926c93add78bee9374b

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0a10a28e26d3ef23f6f08ef34309079162260aeb5572ac8f8ee8f1509cc8ec2b
MD5 c1eae23c99c8254e98d374d4158bc62f
BLAKE2b-256 dc1d6242263b2020a0ce4974a4a377c754726c9cace21b7fd54237bc7d39ced0

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6d4bf6a41834301b4f8f69937fd216cb7fd962b4a9b952f38310b2ca02bb7271
MD5 a955fabfad420d3161af4b72cefd0865
BLAKE2b-256 8c5a362f4776cc09179f29adcc82727a17a768055b4eac7f1e82484bd40fb497

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 33a68f12d97ead6718bc5fcd5c76dd670ef02ab4fdd1ad5c822822311055dc4c
MD5 40251cc1f380b7cdbcdf44d5f08e093d
BLAKE2b-256 2c25636ba44deaad224cb453ebbf3c1eaf6bc4ff7c55be475cab2afb4e858f19

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5d36763eda34cea6e22667302dcd7161ba5b17fc2520fba28a2ddf7c7fe6eb39
MD5 3855f6b37a0fa30fa96c418175e97f61
BLAKE2b-256 75483e7ae475061d6abdfc1a08a3e5081019d485ee407edb0f4a81ebd9e3b3b8

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 571.1 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 ab1c02c3c8e60a0f382ff35bfb4482f9222d74c596fef91c817bf3cede446554
MD5 ffe2fefbc2c0895c1bd52fe63160f232
BLAKE2b-256 b5c73c40f496b84fb14f4b73601ec0bc5c2e4502ff5314dd3f7954892091115a

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp311-cp311-win32.whl
  • Upload date:
  • Size: 461.7 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 96b01db87d82827f1eda4cb251f62382d4f50c45d7f4fa9d56e0a24639fd3d36
MD5 ed938aecf69c5851b048537dc3a83c54
BLAKE2b-256 9a93566d695733a06cb8efbcf4de8140238764280f2a08161f075b21338f46d3

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5e6e4214f07d4879005860b76ed0cc7e6236acc0685342c3e120c8eae113ff57
MD5 cb6f90bae74c591f7c775fe3cf9c2c85
BLAKE2b-256 18835ad02901657b22733b6186befbe4ca841a1ce8347273b3ea1d52b031c318

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 2ac1d07657fe77b86ec91de7fac4e30d4d082c505249fbc9f13a94c63c38b423
MD5 7cedeca586992c5088a956ab4cf1dfa4
BLAKE2b-256 8d516126d2f51de578fa8eafc7262d1ccd29ca5f7030c592be74a8635a43b23c

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2da701ecc85dfc344dd500afe3c6886dc6b3faf7ec3fbaf5345a529e8edfc587
MD5 471739c6b1546834fd147586bec4ac61
BLAKE2b-256 273c215863927f791681094390de554244e4a14dc3de0f0786e80412cc173d68

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 76edf30377e87d8e73fd483e71d3abd9b79b5d005632690798cbcbfe78f4bb3c
MD5 4ae661ae1db3dabde7077a9476c0ff2f
BLAKE2b-256 307671ef2c52e0b800f003acf2c9459ba4ab085a3f9e1960029160ae27f934b4

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f01dd54e22a4c710d4d8c2a689342df0ccf857838d48a6248e708a0cf8ffd1c1
MD5 8f6f0b599555d8cc1ef4c847a07eac4b
BLAKE2b-256 b0fc6fb6e4c47911ccb42b97e6f177a09b23bf6bf37fd71adf61fb20badb1c85

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 571.1 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 6acfa4d3c4e51fc7064451748dadb26bae579a780ebf997212c408c1f4078a9c
MD5 ce49c2e0234c9346fbb8708e66ca90dd
BLAKE2b-256 b30708ff989bafab87f66ee50de0789c7b014fd1b8ed1291a633dbe815f2fef2

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp310-cp310-win32.whl
  • Upload date:
  • Size: 461.7 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 9371f68d494ce07088b72a883d15c4c53decfc3fa6294b95154b19232b94324f
MD5 02d48361466658451fdb6c6c3365420a
BLAKE2b-256 4655d8908776483cc42d638fd7bc3ea6dcc2ad3c7179b492696d301fac542de4

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d57de07605e4f8010f18d833a0c6c558acb6c4b4d17e0e87ff22a71fee6e09ca
MD5 e871d0bf669b47ebeaba7f743fffdcb1
BLAKE2b-256 33307be7d0f18f4f56f7b186f6f91612dff7937284414d276a055d58d4aae22d

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 73eb122066b85fdaaf661b814d23f03c14a131a8ca2c594819de4a8a479d8350
MD5 41debe37944643f38553a386627872ea
BLAKE2b-256 38fcdec5d321c7e726bd3f212cb7effa67fb69c94587f2829597d1e628fe6f62

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 93762c6c3ee3fee1607c3e70d43fb79963475ca7f6908200726fc9d35f76ab91
MD5 bb95550e5b813912b41450166f15a2e7
BLAKE2b-256 bd2eb444ff866d9e7a0b45b617f06d6447e296af29bc932e9c0def770eeabb8f

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7f8858789b5a57b9837cd1645342f3e54a7011f2323bd7082ae51e6c429a9b1b
MD5 b7bff5fc9c5dad382453e84671ab1f1c
BLAKE2b-256 0e7c1d7f7369b58bd094f4ff30898487791c89f78e911cb8a00c392ffdc1da9e

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cc148b509f24e4cdd58b3d685d05c521ada3cf893696f26363a07280aa39f549
MD5 bdbdcbd0d59fbe2e58fc341e8d07ed52
BLAKE2b-256 8d39de7902a3ea444100a5d9dc9503fbb5f7a76c9fe17ef7059b00f4df3e31dd

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 571.1 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 3379cfa3ad0c8443709867cc507ce2936b187285e3b7e97e252b1741144267f7
MD5 a50b0cb5c1d5a792ecc37d296cc76602
BLAKE2b-256 047468f0966218deeb7507636f9248c095e37ebbccdbb200bc950d9177265957

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp39-cp39-win32.whl
  • Upload date:
  • Size: 461.9 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 69e5e261186080501c9e09152833af14075d5de061f6399f5c34a4f638d7d599
MD5 d6f0088d44fc2890a5571cb4fde7210d
BLAKE2b-256 aa767bff224faf8ccc5e9bde0507f5eb1123bda7e1f82b3eecc189e6c5776874

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4176f03f51a27bad0af94217c6999b1bfe9297b126bdd815ee1a6a18afe5ff8b
MD5 d99bec30121946fd8493f90f97aa8a7d
BLAKE2b-256 bd8525223478767001eebf1db6d2a7cb1b8ca8ceb6d5e4da480ae42eb1e97df6

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 40c0b729b0231b5f953643ebb835d20e3956168c507436a449af00cb399df1b0
MD5 72769e04addca9553e254f85867f41e0
BLAKE2b-256 bc02582e7b0200cd3ad96743ee951b502bfbbd54eeea60c3902e6550528ad4d6

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4cf68f473241488d5504bec9ab1b71df3283a17164070324219ed4c17c184705
MD5 00ba8dff3d162032cb1c884cf16e1a0b
BLAKE2b-256 8d6a66d1ae4cf1f4c4b51d5e8aa59d6c5d7410a5fe8e015f05e3921023692697

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3229bb835cd1c6b71add7edee8782f373b51d1b8389e99190471e0606feaf5ae
MD5 13c8c418af149091b8c8fc3046c42621
BLAKE2b-256 fcc38a3c1424957205dafd4390a64893c2a2db3424f8dc3eac196a4c5b87dfc9

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9a52b0b51bd1397c22a935d135a17ae3c0c2fcc869820a2c89634281a4293879
MD5 9163534ca81f4234b17cde9e30c0a216
BLAKE2b-256 1f4e0c2d5e88ad18f68175c23d3b9e2013607320b580688f45f73dcc79ad210a

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 570.7 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 04f6cb83058343c4ad78fd405b36eccb07f0e8e4c233bb8dfa6f85e8b397be91
MD5 bf8a7638beefe585a832037106b61478
BLAKE2b-256 4b5fe3e31ee16ec4ee4a866fbae5ce6fcf8b34df02373da29a0b82e7d46e4b09

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp38-cp38-win32.whl
  • Upload date:
  • Size: 461.7 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 8bf135eab26fa8c8c21013a7bf32061c623f77efd3b2ff0e600edb87b529d2b5
MD5 f902c3fe136b8136464e40a7db583e4a
BLAKE2b-256 537b6d6963a5f99f7b379c31826e910aaa454355d1b332c2a3cb76c79d21ecd8

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 110edce4f1a4302382953bffe9add0dff987714aaea3279ab85258efe3cf6a2a
MD5 0a46a0bc5b41ee2e5b334a9d15f4cb1a
BLAKE2b-256 57dbd883d368425d6b184591942fe784c1def79d89f5421fb08e75be143cea65

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8335d159855d492fdb6b417e801962757d0186043e249da8fe459968d1a91276
MD5 4e198f470d89832bb246ea60033e69d0
BLAKE2b-256 4abea6dfbd963d651d1e22e0e2dfbaf74f52170e3cc6e304e4b28722548a34f0

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 74aa6abc33ae2235bf2be7512b4eea97a6d7f353a8587bf52f858607beffb66a
MD5 9e3afb446e0bde011e9ae9a9f48b43f4
BLAKE2b-256 8e292056a443ec54674fc3471e7ad39d55d86624698a8b7edb43c8bdbc11edc8

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8f751f4dd9d47da5d206356a9e970ebd66e6f7a80240985909b356fe39c990bb
MD5 9cfbbd6c45bd46b6d7b3f5a3a7ef0156
BLAKE2b-256 61e566ad26d2b2a9ee3e4a3dedc32d43f904887e5fbc9fa5ef29cc3bebe3c97f

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6a4b807b802e45b0f86ac2860a38d3544f58bfb9df6c3cdebf332f881b44eed2
MD5 52f77f24e371bced69532bafa80e46c8
BLAKE2b-256 c0d5531bed799a25ea770c4fc62f317e67678a74408e6b86bf5f1594ed27be71

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 569.8 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3332ff991821372bff82d0c5241a0e65270243d29b0076c47b847d90d4443cb9
MD5 ece1061fb0662a166ae3c1227b45e336
BLAKE2b-256 106c4515abf9aae39a902cd375dd0debed1a63059985fc1b52d68e4e2cdd7514

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp37-cp37m-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 461.7 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 59756d08d3c6e83e1ba0a225c168fd1c0b1f55117dd9d8dcd429ea5ecd0c6513
MD5 e721d0009b5f1392fee38ad39e367c03
BLAKE2b-256 553fa94a6e1ff8561e47834710be0619a7a35c13212ec5ef6682510081bbeae9

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e2bce4148a67677e4385598046277b3b108483e18d744598b39097c233b853aa
MD5 89e2bc60e09c491e990daf37ebf974b0
BLAKE2b-256 eebe3110b5de24389d5951375ca236fa37cafdb9c8fcefcfddf42e9f07c7cc44

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 dcef5b476c95a96398188da794c99df76227fb96612f36c55a462ba41d80a9b8
MD5 bdbd547e03d1c7d1bbb59e1cf08a9dee
BLAKE2b-256 97a514bcd796668c37cc9703f3ef5b042752ec8dc298b21368c4ece7f9203195

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d8fa2528e8d2a35c4fb8dd7ee1a80679c608ece568e9e30c366a5bbfeb852b70
MD5 6e23c0db66975c82b413df1983d680db
BLAKE2b-256 a5b13c5ca39c366ec4a3ba31a736ccef57a01c90f89fcc48fc1565ff2e7ab0a3

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 580.1 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 e9d4a7ffd4a8ec86b5294518843ad0dacd4d34c36f3432ad0500daacdb004301
MD5 f3b7256b7ce5ed39ff9c7f48591c4ad4
BLAKE2b-256 048c7ad01a7880a308e08896e845276b0456a3768d2f0d0c1f78c212f4f7724f

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp36-cp36m-win32.whl.

File metadata

  • Download URL: swiglpk-5.0.8-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 468.5 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for swiglpk-5.0.8-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 e11ac614ffa90332261556708109ceffdc76d7014f54e731d2c17cb622a33892
MD5 c597e29de1079c32009fae37ee78a06f
BLAKE2b-256 ba62501833b2def54f7cbbd1e8d0875fe1546dd2b343b285aa16a81a76c6c560

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 95b2e6888704fe5d9c49584cb0373fd02d966dc5dba2ee14589ff4ad4dddcdd0
MD5 c32da4d83f064ed27b455fad46e96960
BLAKE2b-256 0e1cbd9e08859b38cf7d3a7d9233349da306407c2bbd04d2a4ee7cbe70e5b196

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 1485295eb227000385b49bd5b81760b5730562479ad0fe648b946dbfa1ff9cfe
MD5 82ae698f117c56ec25bdf7e20a698722
BLAKE2b-256 bc3ec385ffc1c73c57c2438474df4bb026a03c393a6090e8fa6408a2c8460dcd

See more details on using hashes here.

File details

Details for the file swiglpk-5.0.8-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swiglpk-5.0.8-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3b6f94ff554b4a0977707d5b25ef3ad8eb9b9d4659ceb0844b20084f0f809905
MD5 6b93a7509168d5eb57b1fa5b2119f751
BLAKE2b-256 af86d21157ea70475301459bda4caa96cfef21efe494953cc96a93920e33bd33

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