No project description provided

These details have not been verified by PyPI

Project links

Project description

JijModeling Transpiler

JijModeling Transpiler provides the feature to transpile mathematical models created by JijModeling to other formats such as PyQUBO or LP files.
The library is located on the public PyPI server and is available free of charge to users, but it is obfuscated. You cannot do reverse engineering.

Users can install this library and use it as a subpackage of jijmodeling like from jijmodeling import transpiler.

Project details

These details have not been verified by PyPI

Project links

Release history Release notifications | RSS feed

0.7.3

Mar 17, 2025

0.7.2

Mar 5, 2025

0.7.1

Dec 23, 2024

0.7.0

Dec 19, 2024

0.6.15

Apr 17, 2024

0.6.14

Apr 5, 2024

0.6.13

Feb 9, 2024

0.6.8

Dec 13, 2023

0.6.7

Dec 12, 2023

0.6.6

Nov 13, 2023

0.6.5

Sep 14, 2023

This version

0.6.4

Sep 14, 2023

0.6.3

Sep 12, 2023

0.6.2

Sep 12, 2023

0.6.1

Sep 11, 2023

0.6.0

Aug 29, 2023

0.6.0rc3 pre-release

Jul 28, 2023

0.6.0rc2 pre-release

Jul 11, 2023

0.6.0rc1 pre-release

Jul 11, 2023

0.5.1

Jul 5, 2023

0.5.0

Jun 23, 2023

0.4.1

Jun 6, 2023

0.4.0

May 10, 2023

0.3.9

Apr 4, 2023

0.3.8

Mar 16, 2023

0.3.7

Mar 9, 2023

0.3.6

Mar 9, 2023

0.3.5

Feb 28, 2023

0.3.4

Feb 27, 2023

0.3.3

Feb 25, 2023

0.3.2

Feb 19, 2023

0.3.1

Feb 9, 2023

0.2.6

Jan 23, 2023

0.2.5

Dec 21, 2022

0.2.4

Nov 9, 2022

0.2.3

Nov 9, 2022

0.2.2

Oct 18, 2022

0.2.1

Oct 4, 2022

0.1.23

Oct 4, 2022

0.1.22

Sep 27, 2022

0.1.21

Sep 22, 2022

0.1.20

Sep 16, 2022

0.1.19

Sep 15, 2022

0.1.18

Sep 15, 2022

0.1.17

Aug 31, 2022

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

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

jijmodeling_transpiler-0.6.4-cp311-cp311-win_amd64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.11Windows x86-64

jijmodeling_transpiler-0.6.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl (8.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.11manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

jijmodeling_transpiler-0.6.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl (8.1 MB view details)

Uploaded Sep 14, 2023 CPython 3.11manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

jijmodeling_transpiler-0.6.4-cp311-cp311-macosx_12_0_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.11macOS 12.0+ x86-64

jijmodeling_transpiler-0.6.4-cp311-cp311-macosx_12_0_arm64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.11macOS 12.0+ ARM64

jijmodeling_transpiler-0.6.4-cp310-cp310-win_amd64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.10Windows x86-64

jijmodeling_transpiler-0.6.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded Sep 14, 2023 CPython 3.10manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

jijmodeling_transpiler-0.6.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl (7.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.10manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

jijmodeling_transpiler-0.6.4-cp310-cp310-macosx_12_0_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.10macOS 12.0+ x86-64

jijmodeling_transpiler-0.6.4-cp310-cp310-macosx_12_0_arm64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.10macOS 12.0+ ARM64

jijmodeling_transpiler-0.6.4-cp310-cp310-macosx_11_0_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.10macOS 11.0+ x86-64

jijmodeling_transpiler-0.6.4-cp310-cp310-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.10macOS 11.0+ ARM64

jijmodeling_transpiler-0.6.4-cp310-cp310-macosx_10_16_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.10macOS 10.16+ x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-win_amd64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.9Windows x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.9manylinux: glibc 2.17+ x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded Sep 14, 2023 CPython 3.9manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (7.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.9manylinux: glibc 2.17+ ARM64

jijmodeling_transpiler-0.6.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl (7.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.9manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

jijmodeling_transpiler-0.6.4-cp39-cp39-macosx_12_0_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.9macOS 12.0+ x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-macosx_12_0_arm64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.9macOS 12.0+ ARM64

jijmodeling_transpiler-0.6.4-cp39-cp39-macosx_11_0_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.9macOS 11.0+ x86-64

jijmodeling_transpiler-0.6.4-cp39-cp39-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded Sep 14, 2023 CPython 3.9macOS 11.0+ ARM64

jijmodeling_transpiler-0.6.4-cp39-cp39-macosx_10_16_x86_64.whl (1.4 MB view details)

Uploaded Sep 14, 2023 CPython 3.9macOS 10.16+ x86-64

File details

Details for the file jijmodeling_transpiler-0.6.4-cp311-cp311-win_amd64.whl.

File metadata

Download URL: jijmodeling_transpiler-0.6.4-cp311-cp311-win_amd64.whl
Upload date: Sep 14, 2023
Size: 1.3 MB
Tags: CPython 3.11, Windows x86-64
Uploaded using Trusted Publishing? No
Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for jijmodeling_transpiler-0.6.4-cp311-cp311-win_amd64.whl
Algorithm	Hash digest
SHA256	`6e2dbfda1f08cd63ad6f10832173c711c9b8bb96e9e351820ed617db4440e6ad`
MD5	`95bf01a3eaae00947102769abf2783df`
BLAKE2b-256	`82f29839670416ec9e1ddeb48afbbdbb0239980639815ef7eccf560aa8436175`

Algorithm	Hash digest
SHA256	`7141a370501f81d6c2c4b93447390680a9eda05fc2744487615c8e0d23d2774c`
MD5	`aa557566ea6e22bc046c9ac9c9410fd6`
BLAKE2b-256	`64ca3d0826e3b8899580fbda9126d6f894834a055c4dcfb892b894c2a4a5f9e0`

Algorithm	Hash digest
SHA256	`654d2e3d9b167366f431d77bf83fc63fa4a16e06d777a98423bc53240d71b976`
MD5	`14553c0f312ead1980fcf6c6fd881f83`
BLAKE2b-256	`1a5d0867a9bf96779bb69160c830beb9b1c553b151c30fda58af2bcc62ca244e`

Algorithm	Hash digest
SHA256	`6a0af9187fba3fa853b6dc6396cbba8d37a59772774b2b2cbfd86f146e2e1515`
MD5	`02fe2286441588c636bc642963674649`
BLAKE2b-256	`b57be3d3689d0b5b5def8970e76204163b3afc5b1e73e5cae2fab9d2287069f1`

Algorithm	Hash digest
SHA256	`5ba7f35593a76a9a42232b310f8c2bb8337b5b56e73f45cf49ae3e693f70f7db`
MD5	`2fe27b5e21035729be73b08a0e1054e2`
BLAKE2b-256	`612eed269c68e87c8ccc285ebffb27995c2d762e2b26278c4e18905a96345c21`

Algorithm	Hash digest
SHA256	`3bf6e7147e82dda2d836f7aaf9b14a09b0285a4ff6b796134d57507292a013a1`
MD5	`6ba882852c0ac7bbaaeb1b155052a0e3`
BLAKE2b-256	`945dbf3cbea2cf593107a514d45a880a4179e4a6c909101128d0bc1188f49c60`

Algorithm	Hash digest
SHA256	`220e2d928f8e6d4d8dfa5bbbc42752cda079dce36915cdfe0a1ae0591e4a8b9c`
MD5	`18f5b4d1bd74c4ed58ae5e5615081095`
BLAKE2b-256	`6342885fae690488739b54962106ce1bf03fb0de9a8839190e850dbf1189c7d8`

Algorithm	Hash digest
SHA256	`b24a8d4ff151040219ad19d647a755411cff71a5cc8d8a037f17b62ea1c1b49f`
MD5	`98ea6df39988e426d25293dd5edd8b4c`
BLAKE2b-256	`ab2f8c2bd6d62cdb2f0837a5c7a2f2eb2567069f0c2c4409f33036644124e21a`

Algorithm	Hash digest
SHA256	`51b2131e0fdc2b39a6ef2a575cbc9c7ebf238eca78b9abafbe290c33035e15d9`
MD5	`7172c1fd8c233f44233aa6a29dbd7987`
BLAKE2b-256	`b7dadec71d7457283fee74801eb6be3022305bf0334f00f656f5ea1127bf0be1`

Algorithm	Hash digest
SHA256	`6cb77fb5459a8ff573e9e18654bcd41e7bf4bbd4fcfd6a4522c58a70b55a0adf`
MD5	`37bd19eff16b94c95c999e105ce9b7d1`
BLAKE2b-256	`b33079e966212f0de46073d51927bf9febba42dab1c03dd29fd9d1dde40fc4d6`

Algorithm	Hash digest
SHA256	`6adeee50637cfc9569adc66b15fb4e3eb67a7446b495896596acf14057767d5e`
MD5	`00f8fbc88fa6ceb41548bb365378d2d5`
BLAKE2b-256	`39265273af20c7a4693016d7b3d2ab74540f55b0f8d400af0674aa829ef5c3a2`

Algorithm	Hash digest
SHA256	`df3128fce1927a8737e828cef4cd87006264e20b4cfd557f05aee2435379da9d`
MD5	`f84ae906430f16833b9453a9b7709ef5`
BLAKE2b-256	`252d8ab8143b7ad325770e85182b1f6d659e4d61180aa09f2afbea37ba3ed2dc`

Algorithm	Hash digest
SHA256	`bcf80359f04218f3a6860f6f93ff8ef730f8bbfff5faeb1881de7989857f43af`
MD5	`db9ade85b970597e9f4bbafe1339c1bd`
BLAKE2b-256	`73b644201763c7c4c408aca910c818dd2c249c364cda35b7cbdbb6456050c3f4`

Algorithm	Hash digest
SHA256	`5f26529e773750ea4c191282a6cbb1a81a2dfb5b3105068d724a43d274cd6989`
MD5	`cce366d380713b9f82b17d2082e7f09a`
BLAKE2b-256	`f05eec04f1621939038c6f7e76b8bacfcf25644168626697a97724b8f8101f10`

Algorithm	Hash digest
SHA256	`33bf6e0b9baa867e7e2f23003eb070cf959040427dcef3ce489d6ef420af630e`
MD5	`2559dc32d88b14a7dadff8034e8d3c4f`
BLAKE2b-256	`f1e59caa4ff7dbdd11649d2eb161c7dcc00187ffdc95e926f17cd27ec4cb1d0c`

Algorithm	Hash digest
SHA256	`034bbed9aaa03a3957730a2b0d02f62883ae4de6cd8416c184bcd58afefa9de7`
MD5	`ebd5ee12b8044590cd30080872ccbcde`
BLAKE2b-256	`7029c18f3765a3afe5a181b22571e440e5e12885dfd6956953178ed2bab91f7b`

Algorithm	Hash digest
SHA256	`057e835b030b8f6061c1abfb776db8ec3ae6b1bda3bc2f6845e5edf20add7604`
MD5	`024cf96ced3c11bc4fd8603d2ae56f7f`
BLAKE2b-256	`fdb089025ddd2a05226f570a586b78179c7c12edae416a60f6ec59aa596ef54d`

Algorithm	Hash digest
SHA256	`fde62e11bb2269a269d7e7a5586f2db0dbfc20b84f486be5d5c98616e2f907a7`
MD5	`9bcd3b8542d3e65f645c9c2a1da1ceb4`
BLAKE2b-256	`4f5c9c8f307c85a3f3d8cdfc3645d2c143988ebffaf6d596683a52981bd92431`

Algorithm	Hash digest
SHA256	`c80934fb41f0b0d534d136688ba4f5bab863650f7535f22a2540cf2dc64f8fb8`
MD5	`ea46c976ce778968e8131a51c3f96d42`
BLAKE2b-256	`084330d18814bd9f60efe7b823ffb8463347c52777803a832519170cf1966ab6`

Algorithm	Hash digest
SHA256	`15b056815445e7759fd5da1563b833b0fff22cd941a394467a0da28082a486a9`
MD5	`1a70aaaf096bf54d114b084f45ea9b2c`
BLAKE2b-256	`f32711ee13d501fa4180b1955663f0bd6f9bfbf8f11515fe40e2e8c7e65e3c42`

Algorithm	Hash digest
SHA256	`92881203811bc6b41b9e08e492a2e997f5b6b8dcbee4ce1941e3c11990a02128`
MD5	`05197f8f86d15748112ee30b7e5117f1`
BLAKE2b-256	`dae22c9cbe2d41ce9122658e543f281f9ff0d9eaced9797a36bf977b35aeb92a`

jijmodeling-transpiler 0.6.4

Navigation

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Project description

JijModeling Transpiler

Project details

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Release history Release notifications | RSS feed

Download files

Source Distributions

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

Algorithm	Hash digest
SHA256	`7cdbcb66d2f70b236151441096e90d288368ee905e3ce3c4a552e0229f8689c5`
MD5	`b4c0f0e9b60e6a12da0d6c37df720e4a`
BLAKE2b-256	`817ae95f555e349663e63185e2e6681300a00081550dba73df18f62b50742b5f`

Algorithm	Hash digest
SHA256	`6a75ac42d39121cd0efb820302eb07c96d4713e3d8e2c67a0c23d56ef4a9c41d`
MD5	`ff6c5091683be71cc56dd07efab05f75`
BLAKE2b-256	`443714a23d975bdd2d5a8dfed30cbabda3cc55c63a7c520efceaeec9fdf2e252`