doki-Mowstyl

Python interface for Doki (QSimov core)

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Project description

Python module containing Doki, the core of QSimov quantum computer simulation platform. Written in C with OpenMP parallelism.

Project details

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Release history Release notifications | RSS feed

1.6.0

Sep 19, 2024

1.5.2

Apr 4, 2024

1.5.0

Aug 4, 2023

1.4.0

May 10, 2023

1.3.2

Feb 15, 2022

1.3.1

Feb 15, 2022

1.3.0

Nov 8, 2021

1.2.0

Oct 19, 2021

This version

1.0.1

Sep 21, 2021

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Source Distribution

doki-Mowstyl-1.0.1.tar.gz (19.8 kB view hashes)

Uploaded Sep 21, 2021 Source

Built Distributions

doki_Mowstyl-1.0.1-cp38-cp38-win_amd64.whl (31.9 kB view hashes)

Uploaded Sep 21, 2021 CPython 3.8 Windows x86-64

doki_Mowstyl-1.0.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (114.5 kB view hashes)

Uploaded Sep 21, 2021 CPython 3.8 manylinux: glibc 2.12+ x86-64

doki_Mowstyl-1.0.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (114.9 kB view hashes)

Uploaded Sep 21, 2021 CPython 3.7m manylinux: glibc 2.12+ x86-64

doki_Mowstyl-1.0.1-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (113.9 kB view hashes)

Uploaded Sep 21, 2021 CPython 3.6m manylinux: glibc 2.12+ x86-64

Hashes for doki-Mowstyl-1.0.1.tar.gz

Hashes for doki-Mowstyl-1.0.1.tar.gz
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Hashes for doki_Mowstyl-1.0.1-cp38-cp38-win_amd64.whl

Hashes for doki_Mowstyl-1.0.1-cp38-cp38-win_amd64.whl
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Hashes for doki_Mowstyl-1.0.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for doki_Mowstyl-1.0.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
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Hashes for doki_Mowstyl-1.0.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for doki_Mowstyl-1.0.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
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MD5	`a9da00f0450e6629d362f50651082a9a`
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Hashes for doki_Mowstyl-1.0.1-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for doki_Mowstyl-1.0.1-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`23193daa99e1baa70a80b123a0b4fb5e99659bc2d97bd80f7a4b13a692fd146b`
MD5	`ae7a853cd2d31a34f6da66253ebdde07`
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