55 lines
1.7 KiB
ReStructuredText
55 lines
1.7 KiB
ReStructuredText
===============================
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fuzzysearch
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===============================
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.. image:: https://badge.fury.io/py/fuzzysearch.png
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:target: http://badge.fury.io/py/fuzzysearch
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.. image:: https://travis-ci.org/taleinat/fuzzysearch.png?branch=master
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:target: https://travis-ci.org/taleinat/fuzzysearch
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.. image:: https://pypip.in/d/fuzzysearch/badge.png
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:target: https://crate.io/packages/fuzzysearch?version=latest
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fuzzysearch is useful for finding approximate subsequence matches
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* Free software: MIT license
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* Documentation: http://fuzzysearch.rtfd.org.
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Features
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--------
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* Fuzzy sub-sequence search: Find parts of a sequence which match a given sub-sequence up to a given maximum Levenshtein distance.
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Simple Example
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--------------
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You can usually just use the `find_near_matches()` utility function, which
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chooses a suitable fuzzy search implementation according to the given
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parameters:
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.. code:: python
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>>> from fuzzysearch import find_near_matches
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>>> find_near_matches('PATTERN', 'aaaPATERNaaa', max_l_dist=1)
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[Match(start=3, end=9, dist=1)]
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Advanced Example
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----------------
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If needed you can choose a specific search implementation, such as
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`find_near_matches_with_ngrams()`:
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.. code:: python
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>>> sequence = '''\
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GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA
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TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA
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CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG
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GGGATAGG'''
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>>> subsequence = 'TGCACTGTAGGGATAACAAT' #distance 1
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>>> max_distance = 2
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>>> from fuzzysearch import find_near_matches_with_ngrams
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>>> find_near_matches_with_ngrams(subsequence, sequence, max_distance)
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[Match(start=3, end=24, dist=1)]
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