Module datafusion_strsim 

Adopted from strsim-rs for string similarity metrics

Functions

levenshtein

Calculates the minimum number of insertions, deletions, and substitutions required to change one string into the other.

levenshtein_with_buffer

Calculates the Levenshtein distance using a reusable cache buffer. This avoids allocating a new Vec for each call, improving performance when computing many distances.

normalized_levenshtein

Calculates the normalized Levenshtein distance between two strings. The normalized distance is a value between 0.0 and 1.0, where 1.0 indicates that the strings are identical and 0.0 indicates no similarity.