Soenneker.Utils.Strings.LevenshteinDistance
3.0.255
Prefix Reserved
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See the version list below for details.
See the version list below for details.
dotnet add package Soenneker.Utils.Strings.LevenshteinDistance --version 3.0.255
NuGet\Install-Package Soenneker.Utils.Strings.LevenshteinDistance -Version 3.0.255
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<PackageReference Include="Soenneker.Utils.Strings.LevenshteinDistance" Version="3.0.255" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Soenneker.Utils.Strings.LevenshteinDistance" Version="3.0.255" />
<PackageReference Include="Soenneker.Utils.Strings.LevenshteinDistance" />
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paket add Soenneker.Utils.Strings.LevenshteinDistance --version 3.0.255
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#r "nuget: Soenneker.Utils.Strings.LevenshteinDistance, 3.0.255"
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#:package Soenneker.Utils.Strings.LevenshteinDistance@3.0.255
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#addin nuget:?package=Soenneker.Utils.Strings.LevenshteinDistance&version=3.0.255
#tool nuget:?package=Soenneker.Utils.Strings.LevenshteinDistance&version=3.0.255
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Soenneker.Utils.Strings.LevenshteinDistance
A utility library for comparing strings via the Levenshtein Distance algorithm
Installation
dotnet add package Soenneker.Utils.Strings.LevenshteinDistance
Why Levenshtein Distance?
Levenshtein Distance, also known as Edit Distance, is a widely used metric for measuring the similarity between two strings. It calculates the minimum number of operations required to transform one string into the other, where operations include:
- Insertion of a character.
- Deletion of a character.
- Substitution of a character.
Levenshtein Distance is particularly useful in applications like:
Flexible String Comparison:
It handles strings of unequal length and allows for more flexible comparisons.
Real-World Scenarios:
It's well-suited for tasks like:
- Fuzzy string matching.
- Spelling correction.
- DNA sequence analysis.
- Natural language processing.
Position-Aware:
It captures positional changes and structural differences more effectively than set-based metrics like Jaccard or Hamming Distance.
Comprehensive Error Handling:
Unlike simpler metrics, it accounts for insertions and deletions, making it robust for strings with typos or omissions.
Usage
var text1 = "kitten";
var text2 = "sitting";
int distance = LevenshteinDistanceUtil.ComputeDistance(text1, text2); // 3
double similarityPercentage = LevenshteinDistanceUtil.CalculatePercentage(text1, text2); // ~57.14
This library is efficient, straightforward, and ideal for handling real-world string similarity comparisons where flexibility and accuracy are key.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net9.0 is compatible. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-windows was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
net9.0
- No dependencies.
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
| Version | Downloads | Last Updated |
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| 3.0.307 | 173 | 9/3/2025 |
| 3.0.306 | 158 | 8/11/2025 |
| 3.0.305 | 114 | 6/27/2025 |
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