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Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.

Levenshtein edit distance is a measure of the similarity between two strings. Edit distance is the the minimum number of character deletions, insertions, substitutions, and transpositions required to transform string1 into string2. In essence, the function is used to perform a fuzzy or approximate string search. This is very handy for trying to find the "correct" string for one that has been entered incorrectly, mistyped, etc. The code has been optimized to find strings that are very similar. A "limit" parameter is provided so the function will quickly reject strings that contain more than k mismatches.