📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
-
Updated
Sep 9, 2024 - Python
📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm
Rapid fuzzy string matching in Python using various string metrics
Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity ...
Python port of SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm
Fuzzy string matching, grouping, and evaluation.
Pure Python Spell Checking http://pyspellchecker.readthedocs.io/en/latest/
📚 String comparison and edit distance algorithms library, featuring : Levenshtein, LCS, Hamming, Damerau levenshtein (OSA and Adjacent transpositions algorithms), Jaro-Winkler, Cosine, etc...
Spelling corrector in python
A .NET port of java-string-similarity
Go implementation to calculate Levenshtein Distance.
Swift μ-framework for efficient array diffs and datasource adapters.
Text2Text Language Modeling Toolkit
The Levenshtein Python C extension module contains functions for fast computation of Levenshtein distance and string similarity
Making the quickest and most memory efficient implementation of Levenshtein Distance with SIMD and Threading support
🦀📏 Rust library to compare strings (or any sequences). 25+ algorithms, pure Rust, common interface, Unicode support.
String metrics library written in Go.
A CLI spelling corrector for when you're unsure
Python BK-tree data structure to allow fast querying of "close" matches
Removes most frequent words (stop words) from a text content. Based on a Curated list of language statistics.
Add a description, image, and links to the levenshtein-distance topic page so that developers can more easily learn about it.
To associate your repository with the levenshtein-distance topic, visit your repo's landing page and select "manage topics."