thefuzz

Project Links

Meta

Author: Adam Cohen

Requires Python: >=3.8

Classifiers

Intended Audience

Developers

License

OSI Approved :: MIT License

Programming Language

Python
Python :: 3
Python :: 3.8
Python :: 3.9
Python :: 3.10
Python :: 3.11
Python :: 3.12
Python :: 3 :: Only

Fuzzy string matching like a boss. It uses Levenshtein Distance to calculate the differences between sequences in a simple-to-use package.

Requirements

Python 3.8 or higher
rapidfuzz

For testing

pycodestyle
hypothesis
pytest

Installation

Using pip via PyPI

pip install thefuzz

Using pip via GitHub

pip install git+git://github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz

Adding to your requirements.txt file (run pip install -r requirements.txt afterwards)

git+ssh://git@github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz

Manually via GIT

git clone git://github.com/seatgeek/thefuzz.git thefuzz
cd thefuzz
python setup.py install

Usage

>>> from thefuzz import fuzz
>>> from thefuzz import process

Simple Ratio

>>> fuzz.ratio("this is a test", "this is a test!")
    97

Partial Ratio

>>> fuzz.partial_ratio("this is a test", "this is a test!")
    100

Token Sort Ratio

>>> fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
    91
>>> fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
    100

Token Set Ratio

>>> fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
    84
>>> fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
    100

Partial Token Sort Ratio

>>> fuzz.token_sort_ratio("fuzzy was a bear", "wuzzy fuzzy was a bear")
    84
>>> fuzz.partial_token_sort_ratio("fuzzy was a bear", "wuzzy fuzzy was a bear")
    100

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)]
>>> process.extractOne("cowboys", choices)
    ("Dallas Cowboys", 90)

You can also pass additional parameters to extractOne method to make it use a specific scorer. A typical use case is to match file paths:

>>> process.extractOne("System of a down - Hypnotize - Heroin", songs)
    ('/music/library/good/System of a Down/2005 - Hypnotize/01 - Attack.mp3', 86)
>>> process.extractOne("System of a down - Hypnotize - Heroin", songs, scorer=fuzz.token_sort_ratio)
    ("/music/library/good/System of a Down/2005 - Hypnotize/10 - She's Like Heroin.mp3", 61)