python-jieba 0.42.1-2 source package in Ubuntu

Changelog

python-jieba (0.42.1-2) unstable; urgency=low

  [ Debian Janitor ]
  * Set upstream metadata fields: Bug-Database.

  [ Boyuan Yang ]
  * Rebuild with python3.9 only.
  * debian/control:
    + Bump Standards-Version to 4.5.1.
    + Bump debhelper compat to v13.

 -- Boyuan Yang <email address hidden>  Tue, 08 Dec 2020 16:35:34 -0500

Upload details

Uploaded by:
Debian Chinese Team
Uploaded to:
Sid
Original maintainer:
Debian Chinese Team
Architectures:
all
Section:
misc
Urgency:
Low Urgency

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Series Pocket Published Component Section

Builds

Hirsute: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
python-jieba_0.42.1-2.dsc 2.1 KiB 62e289bcb6ddba4efae72d35b83b765736f65dd19c8c712757bf2c154d7807da
python-jieba_0.42.1.orig.tar.gz 23.3 MiB 607dd88ab9ac78b09d475cf19a3729539beaaecdf42fd5e46f933ffaedaa428e
python-jieba_0.42.1-2.debian.tar.xz 3.1 KiB c2efd7e089edf3f98b26c92f702e5ac7f13e935cf3ebc4bcb77eec64773cd600

Available diffs

No changes file available.

Binary packages built by this source

python-jieba-doc: Jieba Chinese text segmenter (common documentation)

 "Jieba" (Chinese for "to stutter")is a high-accuracy Chinese text segmenteran
 based on HMM-model and Viterbi algorithm. It uses dynamic programming to find
 the most probable combination based on the word frequency.
 .
 This is the common documentation package.

python3-jieba: Jieba Chinese text segmenter (Python 3)

 "Jieba" (Chinese for "to stutter")is a high-accuracy Chinese text segmenteran
 based on HMM-model and Viterbi algorithm. It uses dynamic programming to find
 the most probable combination based on the word frequency.
 .
 It supports three types of segmentation mode:
  * Accurate Mode attempts to cut the sentence into the most accurate
    segmentations, which is suitable for text analysis.
  * Full Mode gets all the possible words from the sentence. Fast but not
    accurate.
  * Search Engine Mode, based on the Accurate Mode, attempts to cut long words
    into several short words, which can raise the recall rate. Suitable for
    search engines.
 Traditional Chinese and customized dictionaries are also supported.
 .
 This package installs the library for Python 3.