Ubuntu
python-levenshtein package

python-levenshtein 0.25.1-2 source package in Ubuntu

Changelog

python-levenshtein (0.25.1-2) experimental; urgency=medium

  * Team Upload.
  * Update d/copyright.

 -- Stuart Prescott <email address hidden>  Tue, 16 Apr 2024 09:24:48 +1000

Upload details

Uploaded by:
Debian Python Team
Uploaded to:
Experimental
Original maintainer:
Debian Python Team
Architectures:
any all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular release universe python
Noble release universe python

Downloads

File Size SHA-256 Checksum
python-levenshtein_0.25.1-2.dsc 2.2 KiB ef81af778c5fe5db71dd250f0a02bbfd8f498b9971b812c93ea039f61a6dfbf3
python-levenshtein_0.25.1.orig.tar.xz 33.9 KiB 705509c919caf701346d0cfa7f0c703fd39854abe314f1f6998cfa91c30bc9b4
python-levenshtein_0.25.1-2.debian.tar.xz 3.8 KiB 2ec634a6cf3375738de615362634e5434f1d5f41c1235abe4b9286744edc1885

No changes file available.

Binary packages built by this source

python-levenshtein-doc: extension for computing string similarities and edit distances (Documentations)

 The Levenshtein module computes Levenshtein distances, similarity ratios,
 generalized medians and set medians of Unicode or non-Unicode strings.
 Because it's implemented in C, it's much faster than the corresponding
 Python library functions and methods.
 .
 The Levenshtein distance is the minimum number of single-character
 insertions, deletions, and substitutions to transform one string into
 another.
 .
 It is useful for spell checking, or fuzzy matching of gettext messages.
 .
 This package contains the documentation.

python3-levenshtein: extension for computing string similarities and edit distances (Python 3)

 The Levenshtein module computes Levenshtein distances, similarity ratios,
 generalized medians and set medians of Unicode or non-Unicode strings.
 Because it's implemented in C, it's much faster than the corresponding
 Python library functions and methods.
 .
 The Levenshtein distance is the minimum number of single-character
 insertions, deletions, and substitutions to transform one string into
 another.
 .
 It is useful for spell checking, or fuzzy matching of gettext messages.
 .
 This package contains Levenshtein for Python 3.

python3-levenshtein-dbgsym: debug symbols for python3-levenshtein