editdistpy 0.1.2rc2

Fast Levenshtein and Damerau optimal string alignment algorithms.

editdistpy

editdistpy is a fast implementation of the Levenshtein edit distance and the Damerau-Levenshtein optimal string alignment (OSA) edit distance algorithms. The original C# project can be found at SoftWx.Match.

Installation

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The easiest way to install editdistpy is using pip:

pip install -U editdistpy

Usage

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You can specify the max_distance you care about, if the edit distance exceeds this max_distance, -1 will be returned. Specifying a sensible max distance can result in significant speed improvement.

You can also specify max_distance=sys.maxsize if you wish for the actual edit distance to always be computed.

Levenshtein

import sys

from editdistpy import levenshtein

string_1 = "flintstone"
string_2 = "hanson"

max_distance = 2
print(levenshtein.distance(string_1, string_2, max_distance))
# expected output: -1

max_distance = sys.maxsize
print(levenshtein.distance(string_1, string_2, max_distance))
# expected output: 6

Damerau-Levenshtein OSA

import sys

from editdistpy import damerau_osa

string_1 = "flintstone"
string_2 = "hanson"

max_distance = 2
print(damerau_osa.distance(string_1, string_2, max_distance))
# expected output: -1

max_distance = sys.maxsize
print(damerau_osa.distance(string_1, string_2, max_distance))
# expected output: 6

Benchmark

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A simple benchmark was done on Python 3.8.12 against editdistance which implements the Levenshtein edit distance algorithm.

The script used by the benchmark can be found here.

For clarity, the following string pairs were used.

Short string

"short sentence with words"

"shrtsen tence wit mispeledwords"

Long string

"Lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod rem"

"Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium"

short string
        test_damerau_osa               0.925678600000083
        test_levenshtein               0.6640075999998771
        test_editdistance              0.9197039000000586
        test_damerau_osa_early_cutoff  0.7028707999998005
        test_levenshtein_early_cutoff  0.5697816000001694
long string
        test_damerau_osa               7.7526998000003005
        test_levenshtein               4.262871200000063
        test_editdistance              1.9676684999999452
        test_damerau_osa_early_cutoff  0.9891195999998672
        test_levenshtein_early_cutoff  0.9085431999997127

While max_distance=10 significantly improves the computation time, it may not be a sensible value in some cases.

editdistpy is also seen to perform better with shorter length strings and can be the more suitable library if your use case mainly deals with comparing short strings.

Changelog

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See the changelog for a history of notable changes to edistdistpy.