Lodestar.Text 0.3.2. This page is frozen at that release. Read the current documentation for what main says now. A link to a decision or a migration page follows main, and leaves the archive.

Counts the fewest insertions and deletions that turn one string into the other, with substitution not allowed.

public static int Distance(ReadOnlySpan<char> a, ReadOnlySpan<char> b, TextElement element = TextElement.Utf16Unit)
public static int Distance<T>(ReadOnlySpan<T> a, ReadOnlySpan<T> b) where T : IEquatable<T>

Parameters — a and b are the two strings to compare. element says what counts as one character: TextElement.Utf16Unit by default, or TextElement.CodePoint for Python's answer outside the Basic Multilingual Plane. The second overload compares any two spans of an IEquatable<T>.

Returns — int, the number of insertions and deletions. Zero when the two are equal, and never negative.

Example — five insertions and deletions where Levenshtein, allowed to substitute, needs only three edits.

using Lodestar.Text.Distances;

int d = Indel.Distance("kitten", "sitting");   // => 5

Remarks — every substitution costs two here, one delete and one insert, so this is always at least as large as Levenshtein and usually larger. That is the point: it is the measure that weights a replaced character as heavily as a lost one, which is what makes it match how people judge two versions of a longer text rather than two mis-keyed short names.

It is exactly len(a) + len(b) - 2 × Lcs.SubsequenceLength(a, b), so Lcs is the thing to reach for when you want the shared run itself rather than a score over it.

The trap is a naming one, and it is the most common confusion in this area: fuzz.ratio in rapidfuzz is this measure normalized, not Levenshtein. Porting fuzz.ratio(a, b) to Levenshtein.NormalizedSimilarity(a, b) * 100 silently produces different numbers on almost every pair. Indel.NormalizedSimilarity(a, b) * 100 is the port.

Applies to — net10.0, netstandard2.0.

See also — Indel.NormalizedSimilarity, Lcs.SubsequenceLength, Levenshtein.Distance, the Python equivalence table.