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This module provide metrics to compare Text starting as an API rexporting main functions of the great lib text-metrics of Mark Karpov

Levenshtein Similarity In information theory, Linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. See: https://en.wikipedia.org/wiki/Levenshtein_distance

Return normalized Levenshtein distance between two Text values. Result is a non-negative rational number (represented as Ratio Natural), where 0 signifies no similarity between the strings, while 1 means exact match.

Return Damerau-Levenshtein distance between two Text values. The function works like levenshtein, but the collection of allowed operations also includes transposition of two adjacent characters. See also: https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance

Return overlap coefficient for two Text values. Returned value is in the range from 0 (no similarity) to 1 (exact match). Return 1 if both Text values are empty.

See also: https://en.wikipedia.org/wiki/Overlap_coefficient.

Jaccard distance measures dissimilarity between sample sets

Hamming Similarity In information theory, the Hamming distance between two strings of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other See: https://en.wikipedia.org/wiki/Hamming_distance