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Python extension for computing string edit distances and similarities.

Project description

Levenshtein

Continous Integration PyPI package version Python versions Documentation GitHub license

Introduction

The Levenshtein Python C extension module contains functions for fast computation of:

  • Levenshtein (edit) distance, and edit operations
  • string similarity
  • approximate median strings, and generally string averaging
  • string sequence and set similarity

This is a fork of ztane/python-Levenshtein, since the original project is no longer actively maintained.

Requirements

  • Python 2.7 or later

Installation

pip install levenshtein

Documentation

The documentation for the current version can be found at https://maxbachmann.github.io/Levenshtein/

License

Levenshtein is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

See the file COPYING for the full text of GNU General Public License version 2.

Changelog

v0.16.0

  • Add support for Python 3.10

v0.15.0

  • Update SequenceMatcher interface to support the autojunk parameter

v0.14.0

  • Drop Python 2 support
  • Fixed free of non heap object due caused by zero offset on a heap object
  • Fixed warnings about missing type conversions
  • Fix segmentation fault in subtract_edit when incorrect input types are used
  • Fixed unchecked memory allocations
  • Implement distance/ratio/hamming/jaro/jaro_winkler using rapidfuzz instead of providing a own implementation
  • Implement Wrapper for inverse/editops/opcodes/matching_blocks/subtract_edit/apply_edit using Cython to simplify support for new Python versions

v0.13.0

  • Maintainership passed to Max Bachmann
  • use faster bitparallel implementations for distance and ratio
  • avoid string copies in distance, ratio and hamming
  • Fix usage of deprecated Unicode APIs in distance, ratio and hamming
  • Fixed incorrect window size inside Jaro and Jaro-Winkler implementation
  • Fixed incorrect exception messages
  • Removed unused functions and compiler specific hacks
  • Split the Python and C implementations to simplify building of the C library
  • Fixed multiple bugs which prevented the use as C library, since some functions only got defined when compiling for Python
  • Build and deliver python wheels for the library
  • Fixed incorrect allocation size in lev_editops_matching_blocks and lev_opcodes_matching_blocks

v0.12.1

  • Fixed handling of numerous possible wraparounds in calculating the size of memory allocations; incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

v0.12.0

  • Fixed a bug in StringMatcher.StringMatcher.get_matching_blocks / extract_editops for Python 3; now allow only str editops on both Python 2 and Python 3, for simpler and working code.
  • Added documentation in the source distribution and in GIT
  • Fixed the package layout: renamed the .so/.dll to _levenshtein, and made it reside inside a package, along with the StringMatcher class.
  • Fixed spelling errors.

v0.11.2

  • Fixed a bug in setup.py: installation would fail on Python 3 if the locale did not specify UTF-8 charset (Felix Yan).

  • Added COPYING, StringMatcher.py, gendoc.sh and NEWS in MANIFEST.in, as they were missing from source distributions.

v0.11.1

  • Added Levenshtein.h to MANIFEST.in

v0.11.0

  • Python 3 support, maintainership passed to Antti Haapala

v0.10.2

  • Made python-Lehvenstein Git compatible and use setuptools for PyPi upload
  • Created HISTORY.txt and made README reST compatible

v0.10.1

  • apply_edit() broken for Unicodes was fixed (thanks to Radovan Garabik)
  • subtract_edit() function was added

v0.10.0

  • Hamming distance, Jaro similarity metric and Jaro-Winkler similarity metric were added
  • ValueErrors raised on wrong argument types were fixed to TypeErrors

v0.9.0

  • a poor-but-fast generalized median method quickmedian() was added
  • some auxiliary functions added to the C api (lev_set_median_index, lev_editops_normalize, ...)

v0.8.2

  • fixed missing `static' in the method list

v0.8.1

  • some compilation problems with non-gcc were fixed

v0.8.0

  • median_improve(), a generalized median improving function, was added
  • an arbitrary length limitation imposed on greedy median() result was removed
  • out of memory should be handled more gracefully (on systems w/o memory overcomitting)
  • the documentation now passes doctest

v0.7.0

  • fixed greedy median() for Unicode characters > U+FFFF, it's now usable with whatever integer type wchar_t happens to be
  • added missing MANIFEST
  • renamed exported C functions, all public names now have lev_, LEV_ or Lev prefix; defined lev_byte, lev_wchar, and otherwise santinized the (still unstable) C interface
  • added edit-ops group of functions, with two interfaces: native, useful for string averaging, and difflib-like for interoperability
  • added an example SequenceMatcher-like class StringMatcher

v0.6.0

  • a segfault in seqratio()/setratio() on invalid input has been fixed to an exception
  • optimized ratio() and distance() (about 20%)
  • Levenshtein.h header file was added to make it easier to actually use it as a C library

v0.5.0

  • a segfault in setratio() was fixed
  • median() handles all empty strings situation more gracefully

v0.4.0

  • new functions seqratio() and setratio() computing similarity between string sequences and sets
  • Levenshtein optimizations (affects all routines except median())
  • all Sequence objects are accepted, not just Lists

v0.3.0

  • setmedian() finding set median was added
  • median() initial overhead for Unicodes was reduced

v0.2.0

  • ratio() and distance() now accept both Strings and Unicodes
  • removed uratio() and udistance()
  • Levenshtein.c is now compilable as a C library (with -DNO_PYTHON)
  • a median() function finding approximate weighted median of a string set was added

v0.1.0

  • Inital release

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