Skip to main content

Python module for interfacing with the CQC tket library of quantum software

Reason this release was yanked:

MacOS wheels incompatible with MacOS 11

Project description

Pytket is a python module for interfacing with TKET, an optimising compiler for quantum circuits developed by Cambridge Quantum. In addition to pytket there are several extension modules for accessing a range of quantum hardware and classical simulators. The extension modules also provide integration with several widely used quantum software tools.

The source code for the TKET compiler can be found in this github repository.

Installation

Installation is supported for Linux, MacOS and Windows. Installation requires python 3.8, 3.9 or 3.10.

To install run the pip command:

pip install pytket

See Installation troubleshooting for help with installation.

To install the pytket extension modules add a hyphen and the extension name to the command:

pip install pytket-quantinuum

For a list of pytket extensions see this page: https://cqcl.github.io/pytket-extensions/api/index.html.

Documentation and Examples

API reference: https://cqcl.github.io/tket/pytket/api/

To get started using pytket see the user manual.

For worked examples using TKET see our examples repository.

Support and Discussion

For bugs and feature requests we recommend creating an issue on the github repository.

User support: tket-support@cambridgequantum.com

For discussion, join the public slack channel here.

Mailing list: join here.

Citation

If you wish to cite TKET in any academic publications, we generally recommend citing our software overview paper for most cases.

If your work is on the topic of specific compilation tasks, it may be more appropriate to cite one of our other papers:

  • "On the qubit routing problem" for qubit placement (a.k.a. allocation) and routing (a.k.a. swap network insertion, connectivity solving). https://arxiv.org/abs/1902.08091 .
  • "Phase Gadget Synthesis for Shallow Circuits" for representing exponentiated Pauli operators in the ZX calculus and their circuit decompositions. https://arxiv.org/abs/1906.01734 .
  • "A Generic Compilation Strategy for the Unitary Coupled Cluster Ansatz" for sequencing of terms in Trotterisation and Pauli diagonalisation. https://arxiv.org/abs/2007.10515 .

Project details


Release history Release notifications | RSS feed

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.

pytket-1.7.2-cp310-cp310-win_amd64.whl (10.5 MB view details)

Uploaded CPython 3.10Windows x86-64

pytket-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.2 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

pytket-1.7.2-cp310-cp310-macosx_11_0_arm64.whl (9.0 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pytket-1.7.2-cp310-cp310-macosx_10_14_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.10macOS 10.14+ x86-64

pytket-1.7.2-cp39-cp39-win_amd64.whl (10.5 MB view details)

Uploaded CPython 3.9Windows x86-64

pytket-1.7.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.2 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

pytket-1.7.2-cp39-cp39-macosx_11_0_arm64.whl (9.0 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pytket-1.7.2-cp39-cp39-macosx_10_14_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.9macOS 10.14+ x86-64

pytket-1.7.2-cp38-cp38-win_amd64.whl (10.5 MB view details)

Uploaded CPython 3.8Windows x86-64

pytket-1.7.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.2 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

pytket-1.7.2-cp38-cp38-macosx_11_0_arm64.whl (9.0 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

pytket-1.7.2-cp38-cp38-macosx_10_14_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.8macOS 10.14+ x86-64

File details

Details for the file pytket-1.7.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pytket-1.7.2-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 10.5 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for pytket-1.7.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 054a56ed6a592da665723cf4cc2f482c29dd4fa261d0e56b800d7bf5248926dc
MD5 674649c7a6308155fb7f71a5e55289b9
BLAKE2b-256 292a728faa7b76f96583bf6b9e2184c7ecfa86872b853480fc78b38f91c94b6f

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 59b7cca0a8c16b1fe6e17b603a725b148a6afe39bd18580646c114d16e9d446f
MD5 5bd9683eab0ea3f5f9bbe864cda1ea45
BLAKE2b-256 685896c2129b3244ca2d05209f85da5371b1b20d1aad5d128dd59436a7556e40

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b426305ab8a990cfd9282abf6625c5b68d8263669ea72bef0c3d4fc39cb05999
MD5 129fb7fe2dee634241672696cd759630
BLAKE2b-256 5d659697c22ceea129f3952666299193420a7ef1f4239af6fc6c8f5b0973b102

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 8c6b2e44f2fbd04855886b2b3dc842c8e873ba7178b8ba1c55773884ba88b600
MD5 289e39322a51eaa19ef606865c01a94a
BLAKE2b-256 1ab5d3cb77122431eeb19a4f185e7d74a6118de320f7cb43ff9fdf8dd5130223

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pytket-1.7.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 10.5 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for pytket-1.7.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 ccc00a75794340e6e817f9cf72312f9522a5622b839d3d725bc2fe8e5dbfea47
MD5 8d2de770599758469c3e92b60c324916
BLAKE2b-256 7c6c69d67b82f1785684ade321d8c3520d4cbec3c24cdcebc7e124aa59e11633

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 56e837a4e655a29b57e6f398998fd97e5ccfe8f0aee4cce45717b364c6e08835
MD5 8e591d7700a9f2e3191faa0b21bdcadb
BLAKE2b-256 0c6d67aeb5efb19603de0b6e992637ecb57221f0fa3a4ce6d6435aba92340eac

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 95e65b9265c6e60d1608625cbc9e2edccaed7297c75eadfbb9797b0776da9025
MD5 9adf18357bc7158ef2f0363d7f581fef
BLAKE2b-256 ff5db18334e29b4dbc65fc2b674b0629b5d29ee8d7c99e1c8cc05e83166a3e79

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 a6b0de7c24fe9293589db00de8c1e80e0e292719007299fbdcef2acbda351f3f
MD5 0f6dec21b6278f013a98d9b9077d292f
BLAKE2b-256 cc14642e6714ead1cce95989dff57095cfb26dc874c6caffbfb4abdcf120b847

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pytket-1.7.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 10.5 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for pytket-1.7.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 71ad556b96df494d4418513cd7b82714ac302018a24895bddad53b3474a137ab
MD5 54d6b19c2cc119393c342daac55df69d
BLAKE2b-256 d2f250063bd4b3a06b1843212c98380198438b1cc9837941e4030c0ccc53fc63

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4083da6907c6e8d962216032c5cb0335c8246d0f05f20a62db416bc02d354fbf
MD5 2bff5321706fcd4558cb16548f12187c
BLAKE2b-256 524d8e903d20fd8311c5ec3a3048ef27e86a147942987d439c07fe94adb6a624

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 49bb06c09d55bd763030a368ac59b16501ceaffb4e27f8a845b431803917f3cd
MD5 1b1d55f3b7c3f9eba39e892b30f184de
BLAKE2b-256 0fa446ca98337bc8cce62960eb7c8da64362c2fd422f23fa5d43d95e81383eae

See more details on using hashes here.

File details

Details for the file pytket-1.7.2-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.7.2-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 deed9d8fcae9ad501f9af49b3a24b02e28eafcb9e56ceea73ffd2cf843eacfbe
MD5 1bf263e818b630efcf21fe47bf9dd6b2
BLAKE2b-256 dbfd542619eb658a180dfdfc2c3355a8a5f5d0d990f303959d74cba2528828a2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page