Skip to content

seatgeek/thefuzz

This branch is up to date with master.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

83bea3d · Feb 27, 2024

History

65 Commits
Sep 26, 2023
Apr 22, 2021
Jan 20, 2024
Apr 22, 2021
Apr 2, 2022
Nov 2, 2021
Oct 30, 2023
Apr 22, 2021
Sep 26, 2023
Jan 13, 2023
Nov 2, 2021
Oct 30, 2023
Oct 30, 2023
Aug 29, 2023
Jan 13, 2023
May 16, 2022
Sep 26, 2023

Repository files navigation

TheFuzz

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

Requirements

For testing

  • pycodestyle
  • hypothesis
  • pytest

Installation

Using pip via PyPI

pip install thefuzz

Using pip via GitHub

pip install git+git://github.com/seatgeek/[email protected]#egg=thefuzz

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

git+ssh://[email protected]/seatgeek/[email protected]#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)