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@x-tabdeveloping x-tabdeveloping released this 06 Sep 14:48
· 6 commits to main since this release
f338b5d

New in version 0.3.0

Now you can reorder your search results using Levenshtein distance!
Sometimes n-gram processes or vectorized processes don't quite order the results correctly.
In these cases you can retrieve a higher number of examples from the indexed corpus, then refine those results with Levenshtein distance.

This gives you the speed of Neofuzz, with the accuracy of TheFuzz :D

from neofuzz import char_ngram_process

process = char_ngram_process()
process.index(corpus)

top_5 = process.extract("your query", limit=30, refine_levenshtein=True)[:5]