68 lines
1.8 KiB
ReStructuredText
68 lines
1.8 KiB
ReStructuredText
=========
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jellyfish
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=========
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.. image:: https://travis-ci.org/jamesturk/jellyfish.svg?branch=master
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:target: https://travis-ci.org/jamesturk/jellyfish
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.. image:: https://coveralls.io/repos/jamesturk/jellyfish/badge.png?branch=master
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:target: https://coveralls.io/r/jamesturk/jellyfish
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.. image:: https://img.shields.io/pypi/v/jellyfish.svg
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:target: https://pypi.python.org/pypi/jellyfish
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.. image:: https://readthedocs.org/projects/jellyfish/badge/?version=latest
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:target: https://readthedocs.org/projects/jellyfish/?badge=latest
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:alt: Documentation Status
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.. image:: https://ci.appveyor.com/api/projects/status/github/jamesturk/jellyfish?branch=master&svg=true
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:target: https://ci.appveyor.com/project/jamesturk/jellyfish/
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Jellyfish is a python library for doing approximate and phonetic matching of strings.
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Written by James Turk <james.p.turk@gmail.com> and Michael Stephens.
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See https://github.com/jamesturk/jellyfish/graphs/contributors for contributors.
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Source is available at http://github.com/jamesturk/jellyfish.
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Included Algorithms
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===================
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String comparison:
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* Levenshtein Distance
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* Damerau-Levenshtein Distance
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* Jaro Distance
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* Jaro-Winkler Distance
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* Match Rating Approach Comparison
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* Hamming Distance
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Phonetic encoding:
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* American Soundex
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* Metaphone
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* NYSIIS (New York State Identification and Intelligence System)
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* Match Rating Codex
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Example Usage
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=============
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>>> import jellyfish
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>>> jellyfish.levenshtein_distance('jellyfish', 'smellyfish')
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2
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>>> jellyfish.jaro_distance('jellyfish', 'smellyfish')
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0.89629629629629637
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>>> jellyfish.damerau_levenshtein_distance('jellyfish', 'jellyfihs')
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1
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>>> jellyfish.metaphone('Jellyfish')
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'JLFX'
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>>> jellyfish.soundex('Jellyfish')
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'J412'
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>>> jellyfish.nysiis('Jellyfish')
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'JALYF'
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>>> jellyfish.match_rating_codex('Jellyfish')
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'JLLFSH'
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