150 lines
3.8 KiB
Plaintext
150 lines
3.8 KiB
Plaintext
Metadata-Version: 2.1
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Name: thefuzz
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Version: 0.19.0
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Summary: Fuzzy string matching in python
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Home-page: https://github.com/seatgeek/thefuzz
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Author: Adam Cohen
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Author-email: adam@seatgeek.com
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License: GPLv2
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Platform: UNKNOWN
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 2.7
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.4
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Classifier: Programming Language :: Python :: 3.5
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Classifier: Programming Language :: Python :: 3.6
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Provides-Extra: speedup
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Requires-Dist: python-levenshtein (>=0.12) ; extra == 'speedup'
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.. image:: https://github.com/seatgeek/thefuzz/actions/workflows/ci.yml/badge.svg
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:target: https://github.com/seatgeek/thefuzz
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TheFuzz
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==========
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Fuzzy string matching like a boss. It uses `Levenshtein Distance <https://en.wikipedia.org/wiki/Levenshtein_distance>`_ to calculate the differences between sequences in a simple-to-use package.
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Requirements
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============
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- Python 2.7 or higher
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- difflib
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- `python-Levenshtein <https://github.com/ztane/python-Levenshtein/>`_ (optional, provides a 4-10x speedup in String
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Matching, though may result in `differing results for certain cases <https://github.com/seatgeek/thefuzz/issues/128>`_)
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For testing
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~~~~~~~~~~~
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- pycodestyle
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- hypothesis
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- pytest
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Installation
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============
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Using PIP via PyPI
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.. code:: bash
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pip install thefuzz
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or the following to install `python-Levenshtein` too
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.. code:: bash
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pip install thefuzz[speedup]
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Using PIP via Github
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.. code:: bash
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pip install git+git://github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz
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Adding to your ``requirements.txt`` file (run ``pip install -r requirements.txt`` afterwards)
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.. code:: bash
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git+ssh://git@github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz
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Manually via GIT
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.. code:: bash
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git clone git://github.com/seatgeek/thefuzz.git thefuzz
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cd thefuzz
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python setup.py install
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Usage
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=====
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.. code:: python
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>>> from thefuzz import fuzz
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>>> from thefuzz import process
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Simple Ratio
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~~~~~~~~~~~~
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.. code:: python
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>>> fuzz.ratio("this is a test", "this is a test!")
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97
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Partial Ratio
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~~~~~~~~~~~~~
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.. code:: python
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>>> fuzz.partial_ratio("this is a test", "this is a test!")
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100
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Token Sort Ratio
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~~~~~~~~~~~~~~~~
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.. code:: python
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>>> fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
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91
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>>> fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
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100
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Token Set Ratio
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~~~~~~~~~~~~~~~
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.. code:: python
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>>> fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
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84
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>>> fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
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100
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Process
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~~~~~~~
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.. code:: python
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>>> choices = ["Atlanta Falcons", "New York Jets", "New York Giants", "Dallas Cowboys"]
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>>> process.extract("new york jets", choices, limit=2)
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[('New York Jets', 100), ('New York Giants', 78)]
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>>> process.extractOne("cowboys", choices)
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("Dallas Cowboys", 90)
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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:
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.. code:: python
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>>> process.extractOne("System of a down - Hypnotize - Heroin", songs)
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('/music/library/good/System of a Down/2005 - Hypnotize/01 - Attack.mp3', 86)
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>>> process.extractOne("System of a down - Hypnotize - Heroin", songs, scorer=fuzz.token_sort_ratio)
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("/music/library/good/System of a Down/2005 - Hypnotize/10 - She's Like Heroin.mp3", 61)
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.. |Build Status| image:: https://github.com/seatgeek/thefuzz/actions/workflows/ci.yml/badge.svg
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:target: https://github.com/seatgeek/thefuzz
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