RapidFuzz
A fast C++ library for fuzzy string matching using Levenshtein Distance, offering MIT licensing and algorithmic improvements.
What is RapidFuzz?
RapidFuzz is a fast fuzzy string matching library for C++ that calculates string similarity using the Levenshtein Distance. It provides the same functionality as FuzzyWuzzy but with significant performance improvements and a permissive MIT license. The library is designed for efficient text comparison tasks, offering various ratio algorithms and cached scorers for optimal speed.
C++ developers and data engineers who need high-performance fuzzy string matching for applications like data deduplication, search engines, or natural language processing.
Developers choose RapidFuzz over alternatives like FuzzyWuzzy for its MIT licensing (avoiding GPL restrictions), C++-based performance optimizations, and algorithmic improvements that deliver faster matching without sacrificing accuracy.
Overview
Rapid fuzzy string matching in C++ using the Levenshtein Distance
Use Cases
Best For
- Data deduplication and record linkage in large datasets
- Implementing fuzzy search functionality in C++ applications
- Text processing pipelines requiring high-speed string similarity calculations
- Integrating fuzzy matching into CMake-based C++ projects
- Parallelizing string comparisons using OpenMP for performance gains
- Replacing FuzzyWuzzy with a faster, MIT-licensed alternative
Not Ideal For
- Teams working in non-C++ environments or without a CMake-based build system
- Projects needing drop-in, pre-built fuzzy matching functions with minimal coding (e.g., out-of-the-box batch processing)
- Applications requiring fuzzy matching with a GUI or interactive tool, as this is a library-level solution
- Scenarios with very small datasets where the performance overhead of C++ integration outweighs benefits
Pros & Cons
Pros
Written in C++ with algorithmic improvements, providing significant speed gains over FuzzyWuzzy, as documented in benchmarks linked from the README.
Allows integration into any project without GPL restrictions, making it suitable for both open-source and commercial use, unlike FuzzyWuzzy's licensing.
Supports multiple ratio calculations (simple, partial, token sort, token set) based on Levenshtein Distance, enabling diverse fuzzy matching scenarios.
Includes CachedRatio for repeated comparisons against multiple strings, reducing computation time in batch operations, as shown in usage examples.
Easily integrates with OpenMP for multithreading, boosting performance on large datasets with example code provided in the README.
Cons
Unlike the Python version, C++ lacks ready-to-use modules like process.extract; users must manually implement these functions, as admitted in the README.
Heavy reliance on CMake for installation and linking can be a barrier for projects using alternative build systems or requiring simple package manager support.
For common tasks like comparing a string to a list, additional code is needed, increasing development time compared to more out-of-the-box libraries.
Open Source Alternative To
RapidFuzz is an open-source alternative to the following products:
Frequently Asked Questions
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