Change point detection for signals in Python.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ctruong from gravatar.com ctruong Avatar for oboulant from gravatar.com oboulant

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License (BSD-2-Clause)
  • Author: Charles Truong, Laurent Oudre, Nicolas Vayatis
  • Maintainer: Charles Truong, Olivier Boulant
  • Tags change point detection , signal segmentation , computer science , machine learning , kernel methods , time series
  • Requires: Python <3.14, >=3.9
  • Provides-Extra: display , test , dev , docs
Classifiers
Report project as malware

Project description

Welcome to ruptures

Maintenance build python PyPI version Conda Version docs PyPI - License Downloads Code style: black Binder Codecov

ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package.

How to cite. If you use ruptures in a scientific publication, we would appreciate citations to the following paper:

  • C. Truong, L. Oudre, N. Vayatis. Selective review of offline change point detection methods. Signal Processing, 167:107299, 2020. [journal] [pdf]

Latest news

  • Welcome to our new PhD student, Nicolas Cecchi! He will integrate new algorithms in ruptures and create tutorials and illustrative examples.

  • NASA uses ruptures! They monitor crops in California and Iran. We submitted an article, let's hope for the best!!

    • Jalilvand, E., Kumar, S.V., Haacker, E., Truong, C., Mahanama, S., 2024, Characterizing spatiotemporal variability in irrigation extent and timing through thermal remote sensing, submitted to Remote Sensing of Environment.

  • We have been contacted by CHELSEA FC to monitor players using ruptures. Stay tuned...

  • We use ruptures to understand the regulation of acetylcholine, an important neurotransmitter that plays a role in muscle contraction (involved in myasthenia gravis). Check out our work at the Journal of Physiology

  • They use ruptures to detect changes in classroom engagement and student participation in Japan. Check out their work

  • ruptures is part of a larger pipeline to observe Earth, in particular marine biodiversity. The authors use it to find change in the phytoplankton diversity. Check out their work

  • We work with Croatian crystallographers (hi Zoran Štefanić!) to understand protein motions using angular diagrams. We will keep you posted for our next joint publications.

  • Charles Truong presented ruptures at PyConDE & PyData Berlin 2024. Check out the video.

Basic usage

(Please refer to the documentation for more advanced use.)

The following snippet creates a noisy piecewise constant signal, performs a penalized kernel change point detection and displays the results (alternating colors mark true regimes and dashed lines mark estimated change points).

import matplotlib.pyplot as plt
import ruptures as rpt

# generate signal
n_samples, dim, sigma = 1000, 3, 4
n_bkps = 4  # number of breakpoints
signal, bkps = rpt.pw_constant(n_samples, dim, n_bkps, noise_std=sigma)

# detection
algo = rpt.Pelt(model="rbf").fit(signal)
result = algo.predict(pen=10)

# display
rpt.display(signal, bkps, result)
plt.show()

General information

Contact

Concerning this package, its use and bugs, use the issue page of the ruptures repository. For other inquiries, you can contact me here.

Important links

Dependencies and install

Installation instructions can be found here.

Changelog

See the changelog for a history of notable changes to ruptures.

Thanks to all our contributors

License

This project is under BSD license.

BSD 2-Clause License

Copyright (c) 2017-2022, ENS Paris-Saclay, CNRS
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
  this list of conditions and the following disclaimer in the documentation
  and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ctruong from gravatar.com ctruong Avatar for oboulant from gravatar.com oboulant

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License (BSD-2-Clause)
  • Author: Charles Truong, Laurent Oudre, Nicolas Vayatis
  • Maintainer: Charles Truong, Olivier Boulant
  • Tags change point detection , signal segmentation , computer science , machine learning , kernel methods , time series
  • Requires: Python <3.14, >=3.9
  • Provides-Extra: display , test , dev , docs
Classifiers

Release history Release notifications | RSS feed

1.1.11rc1 pre-release

This version

1.1.10

1.1.9

1.1.9rc1 pre-release

1.1.8

1.1.8rc1 pre-release

1.1.7

1.1.7rc1 pre-release

1.1.6

1.1.6rc2 pre-release

1.1.6rc1 pre-release

1.1.5

1.1.5rc2 pre-release

1.1.5rc1 pre-release

1.1.4

1.1.4rc1 pre-release

1.1.3

1.1.3rc4 pre-release

1.1.3rc3 pre-release

1.1.3rc2 pre-release

1.1.3rc1 pre-release

1.1.2

1.1.2rc3 pre-release

1.1.2rc2 pre-release

1.1.2rc1 pre-release

1.1.1

1.1.1rc1 pre-release

1.1.0rc1 pre-release

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

1.0.1

1.0a1 pre-release

Download files

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

Source Distribution

ruptures-1.1.10.tar.gz (320.7 kB view details)

Uploaded Source

Built Distributions

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

ruptures-1.1.10-cp313-cp313-win_amd64.whl (477.2 kB view details)

Uploaded CPython 3.13Windows x86-64

ruptures-1.1.10-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

ruptures-1.1.10-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

ruptures-1.1.10-cp313-cp313-macosx_11_0_arm64.whl (494.5 kB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

ruptures-1.1.10-cp313-cp313-macosx_10_13_x86_64.whl (497.2 kB view details)

Uploaded CPython 3.13macOS 10.13+ x86-64

ruptures-1.1.10-cp312-cp312-win_amd64.whl (477.6 kB view details)

Uploaded CPython 3.12Windows x86-64

ruptures-1.1.10-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

ruptures-1.1.10-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

ruptures-1.1.10-cp312-cp312-macosx_11_0_arm64.whl (496.4 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

ruptures-1.1.10-cp312-cp312-macosx_10_13_x86_64.whl (499.2 kB view details)

Uploaded CPython 3.12macOS 10.13+ x86-64

ruptures-1.1.10-cp311-cp311-win_amd64.whl (475.9 kB view details)

Uploaded CPython 3.11Windows x86-64

ruptures-1.1.10-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

ruptures-1.1.10-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

ruptures-1.1.10-cp311-cp311-macosx_11_0_arm64.whl (494.7 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

ruptures-1.1.10-cp311-cp311-macosx_10_9_x86_64.whl (497.0 kB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

ruptures-1.1.10-cp310-cp310-win_amd64.whl (476.1 kB view details)

Uploaded CPython 3.10Windows x86-64

ruptures-1.1.10-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

ruptures-1.1.10-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

ruptures-1.1.10-cp310-cp310-macosx_11_0_arm64.whl (495.4 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

ruptures-1.1.10-cp310-cp310-macosx_10_9_x86_64.whl (497.4 kB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

ruptures-1.1.10-cp39-cp39-win_amd64.whl (476.5 kB view details)

Uploaded CPython 3.9Windows x86-64

ruptures-1.1.10-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

ruptures-1.1.10-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

ruptures-1.1.10-cp39-cp39-macosx_11_0_arm64.whl (496.1 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

ruptures-1.1.10-cp39-cp39-macosx_10_9_x86_64.whl (498.0 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

File details

Details for the file ruptures-1.1.10.tar.gz.

File metadata

  • Download URL: ruptures-1.1.10.tar.gz
  • Upload date:
  • Size: 320.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10.tar.gz
Algorithm Hash digest
SHA256 76b998f10709045e91a5f44173dc574bf98a106fd3bf22ec3c63b298a02df031
MD5 78a6fd99a9e1f62690f815d925493cc7
BLAKE2b-256 64323bcf5a62479b4d83187f872fc68b918b59285f560bee4f37c5d49b1d957a

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: ruptures-1.1.10-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 477.2 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 39f3ece91327440fbebca84155b39435970ccc0f52bd3e33878aaff157d04e01
MD5 8c7acf5506d424e90ef0409a12742898
BLAKE2b-256 bd291fe6a1b1811f64bdd35b61300e9d57f68d630d271c92423553a30072d5c5

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 fada68f6617e26138151a1ce6f73932e84ae01119e48be005773a40363454e51
MD5 e0642fb3602388b5d661d101c78e33c5
BLAKE2b-256 f3dcf0a268190b233c4d4b9fa50cd7078bbc536bf319d724218087b2cb4a1138

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 fea4d0049051530e73babc2f44e75e6ba520bb90fe5bfa60d59c4d054180893e
MD5 284fe37bf6ddbdfeced49658a6c7dab5
BLAKE2b-256 0f2629499f16b62220ce3b0bb75a8f8de921814e55c223e3263df7f2733eb5a7

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bfaf4dbf51ae74a4f8893ba36be98912cd4bd7f2a94a79a5ff0d2edca65c21f5
MD5 808cee263f33c94359cb6c097b79c7bf
BLAKE2b-256 c684f5fe5ded842d1c57ecd53db71f1e9c099ce14d7d2c2cc997f0351ef6f0cb

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 29038a863f52c026d950066a62d23719304273e2cef41159259422a055f04fc0
MD5 f2c90340911530b9801805b00d455a2e
BLAKE2b-256 2940087c4deede27066eb9f075c3768749366030bb24fd2c490fb1affe0b8a3f

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: ruptures-1.1.10-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 477.6 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 4be700aa3fee9057667062343a2fa728e25765f457ea54dac116fd2f4b7f49c9
MD5 fa76ac17bda351b8821f583f11b94c82
BLAKE2b-256 a10adf3f6843d4715e571b1bf4c075802c1cd002d1e462a1fc54faeda79a3b21

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 0930cecc7ec1c9af0b1a7da6fb769d298691e077c6cba8daad6ebaef49ed8e80
MD5 8213bc9dcaaea2c93081afbf7a43e3f3
BLAKE2b-256 78575d00e8500b4d906809b86a23390c035e40460f2ff90acd134a6198320428

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 01fb8847a58cbb158103c1810022ea29e3fa3291d6531631bc6134f636ea2fc1
MD5 1ac44dfc82fcab1b9d79dc127fd77df9
BLAKE2b-256 0068e54eba1861ab1be8d63fe019ce57632422ae8d0e8979b897d3f2fb4ca33d

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 14e3aa451220a05c6a7782a3b31fdd4fc578d39b77404dc94649bcae5eebd1db
MD5 0292d2ed1d66c3b6e11ed97361aa0cbc
BLAKE2b-256 6728a25c5eecf1b9df53d27482c953c573515ab0056e64b0e9173312344fc169

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 7a7f614c63f2cecd76d7b5f9f79ff34712234d274a41867428ace4a3a45757c8
MD5 b50fb249eeb234be723de01ffa941768
BLAKE2b-256 c6182b93d310a3a96393d48ee06363db860c576dcff3f925c8873a0ca7be219f

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: ruptures-1.1.10-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 475.9 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 733adb020910dbcfc6fdbca7295db28295177a927a70002c7080f2a4bfbf1840
MD5 45ff4b580ff0dfcf3951f544a579151f
BLAKE2b-256 d8a914aa9d2413ad7c29ab9c983cf5f6ce65202c1a63af56a56d1ab075bcf91d

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 14860e1b1bbb439837320147dcd71ad31fc76a35988de94b5aa90bb0d22b1022
MD5 1bdd628d603f3b1ddef67c9a43e31048
BLAKE2b-256 98c00d211972132f2161c594a67552fd0eb30697750c13e7351ab9dc0bb1f2a5

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 728ec63779ebb94341caaca70c57d01eb6a22cb98d7e3079935a73a43febcb30
MD5 f810cbb56e20932ed40ec0b23afa5c70
BLAKE2b-256 858106be598b7dedbcd63683296ebae683dbdab62bb0134fc8a6fd05a4b74e03

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ef2f26424b267a3da46b05b6d78322249ab1325754c61cafd9580d4eef0011ea
MD5 3cf31196e937c2f09b04515055e958a4
BLAKE2b-256 c67a0026c5a85c11d6eb0202e828b5fa8dc829615f6bb61155463827ba1d2e5d

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4038c09d8148bde4c3689adc3570dd3728163326a0b7baa82474641b8276f53e
MD5 bee4cd732b8635f0543031d0a0ae630b
BLAKE2b-256 aeeab561e98a69e412c29a808cdb25acff73005b26d0313632b7ec29a5846f8c

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: ruptures-1.1.10-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 476.1 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 171fe4f61044a0520e1cd4e429f69242570939700aa4990b3401bf9a8d61aebe
MD5 04ea41829f69e2c83881c8c3078ec6d4
BLAKE2b-256 7ed3eb3fb911c23019ac6fdce873a959c63c344780a391ca55355c6fdb088912

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e1a62f024d3714facca48e8859ba2602367af0c7ca1680cffded1cbff7cf264f
MD5 3eefe4a3385be06592994286dd3547eb
BLAKE2b-256 488f36bf50751f11a2b2e81b24b502fbc386c7ae2033a3faf3f7b4502dbdd7fd

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 8810f3c9f71262fa5d4866ea0a8f2d0ea4e15a9d28d868c97043d260c8c87bc8
MD5 bb0b637502919c7e2b9d2fbf8ab28333
BLAKE2b-256 f061e0015e0a95a310edfcf1dc3413ccb4afad1905e33511b78768b32647e14f

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 20ea4ce1e7503bef60aa879196343acea660905f85692c9612d1a1f787e21da6
MD5 19ec89cc37aa1024b5681caa049db9d7
BLAKE2b-256 e16e3fbe3d105bc9100535682dcae147a6f93bde7ebc29af7795236204b7952e

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d2dae4173db1ffab6cf1eead44825b360e354b3c37f7316b7a827dea6a34b577
MD5 69a5fcd6cd17eb36c083c6604e326932
BLAKE2b-256 f36bfbd0f47c95c2e55bfe21447fb5f3878692f1a3686e2f65e70bc7dbbea15b

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: ruptures-1.1.10-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 476.5 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ruptures-1.1.10-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 dff3801467f0ab7c257305fea1f676b55f16fc8c8e8bd8aafac366da52afa578
MD5 474d4d30e54045823ebdfc9c37729b63
BLAKE2b-256 3aae3f6f42038bb992d42b23a8b54790593aa04ef297195901d6534e671fd255

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a1452f5e88c456d63c099d992cca81b07738796ef0eb7ac212fcb440dedc84c8
MD5 dd763ccf1194de69ee0c898d5d7432ed
BLAKE2b-256 f93154e208dc3678d5d09f612201bc99b88842e4ae10266ffe0b08650845a191

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 9db0a66c9ae2a1dbb6ad494337f923712315114c9441ef6974e21933b76e26eb
MD5 20527a3c8145ca5e02c7c507319cd1f0
BLAKE2b-256 3d02444e80a095c2521b66afab818c324b57fc9567904f6027df474ad760f719

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 19a52a7e903239f5bf844a0d8d364d71f803e63403643094134978f9a796e2a9
MD5 c46e7be51b46949419ae031284de012f
BLAKE2b-256 29a8ee757469b35184c12e423ff0c55511a5f019cba569e0b963d5f211e2e537

See more details on using hashes here.

File details

Details for the file ruptures-1.1.10-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for ruptures-1.1.10-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bd1d6452b8d83af44f92ba76a3c8b9a222eaf68191a74cfd586a62c2997e08fd
MD5 b1cef7fdb302686066c423c235ae0cf3
BLAKE2b-256 9ed8b21d21027f4699ceae02aee624258bc2c5b4dcd553a524cd147738920594

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