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An efficient algorithm for k-bounded (Damerau-)Levenshtein distance

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mbleven

mbleven is a fast, memory-efficient algorithm to compute k-bounded Levenshtein distance.

If the upper-bound parameter k is small (especially k=1,2), this algorithm runs much faster than the Wagner-Fischer algorithm.

For details, see the documentation.

IMPORTANT NOTICE

This is a proof-of-concept implementation to show how mbleven algorithm works. If you are searching for a practical library to compute Levenshtein distance, please take a look at polyleven.

Installation

Clone this repository and run setup.py

$ git clone https://github.com/fujimotos/mbleven
$ cd mbleven
$ sudo python setup.py install

Usage

This module provides a function named compare(). It takes two strings as arguments and returns an integer, which is...

  • the exact distance between two strings (if they are within two edit distance)
  • -1 (if they are over two edit distance away)

Therefore, the return value should be any one of 0, 1, 2 or -1.

>>> from mbleven import compare
>>> compare("meet", "meat")
1
>>> compare("meet", "eat")
2
>>> compare("meet", "mars")  # distance 3
-1

You can also measure the similarity using Damerau-Levenshtein distance by setting transpose flag true.

>>> compare("meat", "meta", transpose=True)
1
>>> compare("abc", "ca", transpose=True)
2

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An efficient algorithm for k-bounded (Damerau-)Levenshtein distance

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