Implementation of Levensthtein and Damerau-Levenshtein edit distances (and similarity) weighted on the QWERTY keyboard proximity.
Not all edits are equal! Insertions and substitutions of characters should be considered differently if the characters are close to each other in a standard QWERTY keyboard.
This library it gives different distances based on the closeness of characters in the keyboard and it returns the Levensthtein edit distance (insertion, deletion, substition of characters) as well as Damerau-Levenshtein distance (insertion, deletion, substition and transpositions of adjacent characters).
It also provides similarity scores from 0.0 to 1.0 denoting how similar the two strings are.
pip install qwerty-weighted-levenshtein
Basic use:
from qwerty_weighted_levenshtein import qwerty_weighted_levenshtein
qwerty_weighted_levenshtein("test", "pest") # It returns 1.0 as it requires one substitution (t > p = 1.0)
qwerty_weighted_levenshtein("test", "yest") # It returns 0.7 as t and y are close in the keyboard (t > y = 0.7)- Weighting Edit Distance to Improve Spelling Correction in Music Entity Search: Master's thesis of A. Samuellson implementing same principle for Spotify Search engine and showing correlation between physical position of keys on the keyboard and spelling mistakes.
- infoscout/weighted-levenshtein: Cython library implementing weighted Levensthein distance function.
- Damerau-Levenshtein distance
Released under the MIT license.
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Copyright (c) 2022 Daniele Volpi
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