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python-pomegranate package

python-pomegranate 0.14.8-4 source package in Ubuntu

Changelog

python-pomegranate (0.14.8-4) unstable; urgency=medium

  * Team upload.
  
  [ Andreas Tille ]
  * Restrict upstream version to 0.14.8 series since this package has the
    only purpose to work with cnvkit which requires this version based on
    Cython and not on PyTorch
  * Build-Depends: s/dh-python/dh-sequence-python3/ (routine-update)
  * d/rules: call dh_numpy3
  * Verify test works properly
    Closes: #1056492

  [ Bas Couwenberg ]
  * Switch to cython3-legacy
    Closes: #1056867

 -- Andreas Tille <email address hidden>  Fri, 15 Dec 2023 12:06:50 +0100

Upload details

Uploaded by:
Debian Python Team
Uploaded to:
Sid
Original maintainer:
Debian Python Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

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File Size SHA-256 Checksum
python-pomegranate_0.14.8-4.dsc 2.5 KiB 47e7f19611a3227b74bdef8a623df55d5f0d0de14ab4e89b8eeb88833e926be2
python-pomegranate_0.14.8.orig.tar.gz 26.1 MiB a34595fca1a269f454f7b5d10b91e0279e69bb21e75815803e16c7df4780987d
python-pomegranate_0.14.8-4.debian.tar.xz 38.2 KiB 12247c9916689919391c3f864397e5cd725b40d57820f5f597f3de3bc9a22657

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Binary packages built by this source

python-pomegranate-doc: documentation accompanying probabilistic modelling library

 pomegranate is a package for probabilistic models in Python that is
 implemented in cython for speed. It's focus is on merging the easy-to-use
 scikit-learn API with the modularity that comes with probabilistic
 modeling to allow users to specify complicated models without needing to
 worry about implementation details. The models are built from the ground
 up with big data processing in mind and so natively support features
 like out-of-core learning and parallelism.
 .
 This is the common documentation package.

python3-pomegranate: Fast, flexible and easy to use probabilistic modelling

 pomegranate is a package for probabilistic models in Python that is
 implemented in cython for speed. It's focus is on merging the easy-to-use
 scikit-learn API with the modularity that comes with probabilistic
 modeling to allow users to specify complicated models without needing to
 worry about implementation details. The models are built from the ground
 up with big data processing in mind and so natively support features
 like out-of-core learning and parallelism.

python3-pomegranate-dbgsym: debug symbols for python3-pomegranate