RapidFuzz

Rapid fuzzy string matching in Python using various string metrics

cpp hacktoberfest levenshtein levenshtein-distance python starred-maxbachmann-repo starred-repo string-comparison string-matching string-similarity

Go to file

maxbachmann 3137df9e96 remove boost::optional dependency		2020-05-22 14:38:13 +02:00
.github	add missing files to tarball	2020-04-15 23:17:35 +02:00
bench	update submodule and benchmark results	2020-05-12 21:59:14 +02:00
docs/img	add first flowchart	2020-05-13 21:27:08 +02:00
extern/variant	reduce string copies and tarball size	2020-05-22 13:28:38 +02:00
src	remove boost::optional dependency	2020-05-22 14:38:13 +02:00
.gitattributes	release 0.6.0	2020-04-04 06:15:37 +02:00
.gitignore	reduce template usage to a minimum	2020-03-31 15:16:03 +02:00
.gitmodules	move cpp into submodule	2020-04-13 08:50:35 +02:00
Benchmarks.md	The cpp version is now always used	2020-05-19 18:39:16 +02:00
LICENSE	add license preamble	2020-04-10 15:06:57 +02:00
MANIFEST.in	remove boost::optional dependency	2020-05-22 14:38:13 +02:00
README.md	fix performance degradation and use the same interface everywhere	2020-04-09 09:32:29 +02:00
VERSION	remove boost::optional dependency	2020-05-22 14:38:13 +02:00
setup.py	reduce string copies and tarball size	2020-05-22 13:28:38 +02:00

README.md

Rapid fuzzy string matching in Python and C++ using the Levenshtein Distance

Description • Installation • Usage • License

Description

RapidFuzz is a fast string matching library for Python and C++, which is using the string similarity calculations from FuzzyWuzzy. However there are two aspects that set RapidFuzz apart from FuzzyWuzzy:

It is MIT licensed so it can be used whichever License you might want to choose for your project, while you're forced to adopt the GPL license when using FuzzyWuzzy
It is mostly written in C++ and on top of this comes with a lot of Algorithmic improvements to make string matching even faster, while still providing the same results. More details on these performance improvements in form of benchmarks can be found here

Installation

RapidFuzz can be installed using pip

$ pip install rapidfuzz

There are pre-built binaries (wheels) for RapidFuzz and its dependencies for MacOS (10.9 and later), Linux x86_64 and Windows.

For any other architecture/os RapidFuzz can be installed from the source distribution. To do so, a C++14 capable compiler must be installed before running the pip install rapidfuzz command. While Linux and MacOs usually come with a compiler it is required to install C++-Buildtools on Windows.

Usage

> from rapidfuzz import fuzz
> from rapidfuzz import process

Simple Ratio

> fuzz.ratio("this is a test", "this is a test!")
96.55171966552734

Partial Ratio

> fuzz.partial_ratio("this is a test", "this is a test!")
100.0

Token Sort Ratio

> fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
90.90908813476562
> fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
100.0

Token Set Ratio

> fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
83.8709716796875
> fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
100.0

Process

> choices = ["Atlanta Falcons", "New York Jets", "New York Giants", "Dallas Cowboys"]
> process.extract("new york jets", choices, limit=2)
[('new york jets', 100), ('new york giants', 78.57142639160156)]
> process.extractOne("cowboys", choices)
("dallas cowboys", 90)

License

RapidFuzz is licensed under the MIT license since I believe that everyone should be able to use it without being forced to adopt the GPL license. Thats why the library is based on an older version of fuzzywuzzy that was MIT licensed as well. This old version of fuzzywuzzy can be found here.