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  1. RapidFuzz · PyPI

    Mar 18, 2020 · RapidFuzz is a fast string matching library for Python and C++, which is using the string similarity calculations from FuzzyWuzzy. However there are a couple of aspects that set …

  2. RapidFuzz 3.14.3 documentation - GitHub Pages

    RapidFuzz provides a wide range of fundamental algorithms for string matching. In addition it provides an API compatible implementation of all algorithms in thefuzz / fuzzywuzzy.

  3. GitHub - rapidfuzz/RapidFuzz: Rapid fuzzy string matching in …

    The following benchmark gives a quick performance comparison between RapidFuzz and FuzzyWuzzy. More detailed benchmarks for the string metrics can be found in the …

  4. RapidFuzz: A Powerful and High-Performance Fuzzy String …

    May 19, 2025 · RapidFuzz is a high-performance fuzzy string matching library for Python and C++. Built on the string similarity methods of FuzzyWuzzy, it offers significant improvements in …

  5. rapidfuzz Python Guide [2025] | PyPI Tutorial

    Nov 16, 2025 · rapidfuzz is rapid fuzzy string matching that provides essential functionality for Python developers. With >=3.10 support, it offers rapid fuzzy string matching with an intuitive …

  6. rapidfuzz - Rust - Docs.rs

    `RapidFuzz` is a general purpose string matching library with implementations for Rust, C++ and Python.

  7. rapidfuzz.fuzz - RapidFuzz 3.14.3 documentation

    rapidfuzz.fuzz.partial_ratio(s1, s2, *, processor=None, score_cutoff=None) ¶ Searches for the optimal alignment of the shorter string in the longer string and returns the fuzz.ratio for this …

  8. RapidFuzz - GitHub

    RapidFuzz provides libraries for fuzzy string matching in various programming languages.

  9. rapidfuzz/RapidFuzz | DeepWiki

    Apr 21, 2025 · This page provides a comprehensive overview of the RapidFuzz repository, a high-performance string matching library implemented in Python and C++. RapidFuzz enables fast …

  10. Installation - RapidFuzz 3.14.3 documentation

    While there are several ways of install RapidFuzz, the recommended methods are either by using pip (the Python package manager) or conda (an open-source, cross-platform, package manager)