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SymSpell - 1 million times faster through Symmetric Delete spelling correction algorithm

  •    CSharp

Spelling correction & Fuzzy search: 1 million times faster through Symmetric Delete spelling correction algorithm The Symmetric Delete spelling correction algorithm reduces the complexity of edit candidate generation and dictionary lookup for a given Damerau-Levenshtein distance. It is six orders of magnitude faster (than the standard approach with deletes + transposes + replaces + inserts) and language independent.

Buffer - Swift μ-framework for efficient array diffs, collection observation and cell configuration.

  •    Swift

Swift μ-framework for efficient array diffs, collection observation and data source implementation. Buffer is designed to be very granular and has APIs with very different degrees of abstraction.

levenshtein.c - Levenshtein algorithm in C

  •    C

Vladimir Levenshtein’s edit distance algorithm1 as a C library. There’s also a CLI: levenshtein(1), and a JavaScript version.Or clone the repo.

LinSpell - Fast approximate strings search & spelling correction

  •    CSharp

The LinSpell spelling correction algorithm does not require edit candidate generation or specialized data structures like BK-tree or Norvig's algorithm. In most cases LinSpell is faster and requires less memory compared to BK-tree or Norvig's algorithm. LinSpell is language and character set independent. The word frequency list was created by intersecting the two lists mentioned below. By reciprocally filtering only those words which appear in both lists are used. Additional filters were applied and the resulting list truncated to ≈ 80,000 most frequent words.

SymSpellCompound - SymSpellCompound: compound aware automatic spelling correction


SymSpellCompound supports compound aware automatic spelling correction of multi-word input strings. It is built on top of SymSpell's 1 million times faster spelling correction algorithm. Splitting errors, concatenation errors, substitution errors, transposition errors, deletion errors and insertion errors can by mixed within the same word.

strsim-rs - :abc: Rust implementations of string similarity metrics

  •    Rust

You can change the version in the url to see the documentation for an older version in the changelog. If you don't want to install Rust itself, you can run $ ./dev for a development CLI if you have Docker installed.

Quickenshtein - Making the quickest and most memory efficient implementation of Levenshtein Distance with SIMD and Threading support

  •    CSharp

Quickenshtein gets its speed and memory efficiency from a number of different optimizations. To get the most performance out of the library, you will need .NET Core 3 or higher as this has support for hardware intrinsics. Quickenshtein takes advantage of the following hardware intrinsics. On any recent x86 system, you will likely have these available.

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