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fuzzysearch is useful for finding approximate subsequence matches

Project description

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Fuzzy search: Find parts of long text or data, allowing for some changes/typos.

Easy, fast, and just works!

>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1)
[Match(start=3, end=9, dist=1, matched="PATERN")]
  • Two simple functions to use: one for in-memory data and one for files

    • Fastest search algorithm is chosen automatically

  • Levenshtein Distance metric with configurable parameters

    • Separately configure the max. allowed distance, substitutions, deletions and/or insertions

  • Advanced algorithms with optional C and Cython optimizations

  • Properly handles Unicode; special optimizations for binary data

  • Simple installation:
    • pip install fuzzysearch just works

    • pure-Python fallbacks for compiled modules

    • only one dependency (attrs)

  • Extensively tested

  • Free software: MIT license

For more info, see the documentation.

Installation

fuzzysearch supports Python versions 2.7 and 3.5+.

$ pip install fuzzysearch

This will work even if installing the C and Cython extensions fails, using pure-Python fallbacks.

Usage

Just call find_near_matches() with the sub-sequence you’re looking for, the sequence to search, and the matching parameters:

>>> from fuzzysearch import find_near_matches
# search for 'PATTERN' with a maximum Levenshtein Distance of 1
>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1)
[Match(start=3, end=9, dist=1, matched="PATERN")]

To search in a file, use find_near_matches_in_file() similarly:

>>> from fuzzysearch import find_near_matches_in_file
>>> with open('data_file', 'rb') as f:
...     find_near_matches_in_file(b'PATTERN', f, max_l_dist=1)
[Match(start=3, end=9, dist=1, matched="PATERN")]

Examples

fuzzysearch is great for ad-hoc searches of genetic data, such as DNA or protein sequences, before reaching for “heavier”, domain-specific tools like BioPython:

>>> sequence = '''\
GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA
TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA
CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG
GGGATAGG'''
>>> subsequence = 'TGCACTGTAGGGATAACAAT' # distance = 1
>>> find_near_matches(subsequence, sequence, max_l_dist=2)
[Match(start=3, end=24, dist=1, matched="TAGCACTGTAGGGATAACAAT")]

BioPython sequences are also supported:

>>> from Bio.Seq import Seq
>>> from Bio.Alphabet import IUPAC
>>> sequence = Seq('''\
GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA
TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA
CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG
GGGATAGG''', IUPAC.unambiguous_dna)
>>> subsequence = Seq('TGCACTGTAGGGATAACAAT', IUPAC.unambiguous_dna)
>>> find_near_matches(subsequence, sequence, max_l_dist=2)
[Match(start=3, end=24, dist=1, matched="TAGCACTGTAGGGATAACAAT")]

Matching Criteria

The search function supports four possible match criteria, which may be supplied in any combination:

  • maximum Levenshtein distance (max_l_dist)

  • maximum # of subsitutions

  • maximum # of deletions (“delete” = skip a character in the sub-sequence)

  • maximum # of insertions (“insert” = skip a character in the sequence)

Not supplying a criterion means that there is no limit for it. For this reason, one must always supply max_l_dist and/or all other criteria.

>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1)
[Match(start=3, end=9, dist=1, matched="PATERN")]

# this will not match since max-deletions is set to zero
>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1, max_deletions=0)
[]

# note that a deletion + insertion may be combined to match a substution
>>> find_near_matches('PATTERN', '---PAT-ERN---', max_deletions=1, max_insertions=1, max_substitutions=0)
[Match(start=3, end=10, dist=1, matched="PAT-ERN")] # the Levenshtein distance is still 1

# ... but deletion + insertion may also match other, non-substitution differences
>>> find_near_matches('PATTERN', '---PATERRN---', max_deletions=1, max_insertions=1, max_substitutions=0)
[Match(start=3, end=10, dist=2, matched="PATERRN")]

When to Use Other Tools

  • Use case: Search through a list of strings for almost-exactly matching strings. For example, searching through a list of names for possible slight variations of a certain name.

    Suggestion: Consider using fuzzywuzzy.

History

0.7.1 (2020-04-05)

  • Dropped support for Python 3.4.

  • Removed deprecation warning with Python 3.8.

  • Fixed a couple of nasty bugs.

0.7.0 (2020-01-14)

  • Added matched attribue to Match objects containing the matched part of the sequence.

  • Added support for CPython 3.8. Now supporting CPython 2.7 and 3.4-3.8.

0.6.2 (2019-04-22)

  • Fix calling search_exact() without passing end_index.

  • Fix edge case: max. dist >= sub-sequence length.

0.6.1 (2018-12-08)

  • Fixed some C compiler warnings for the C and Cython modules

0.6.0 (2018-12-07)

  • Dropped support for Python versions 2.6, 3.2 and 3.3

  • Added support and testing for Python 3.7

  • Optimized the n-grams Levenshtein search for long sub-sequences

  • Further optimized the n-grams Levenshtein search

  • Cython versions of the optimized parts of the n-grams Levenshtein search

0.5.0 (2017-09-05)

  • Fixed search_exact_byteslike() to support supplying start and end indexes

  • Added support for lists, tuples and other Sequence types to search_exact()

  • Fixed a bug where find_near_matches() could return a wrong Match.end with max_l_dist=0

  • Added more tests and improved some existing ones.

0.4.0 (2017-07-06)

  • Added support and testing for Python 3.5 and 3.6

  • Many small improvements to README, setup.py and CI testing

0.3.0 (2015-02-12)

  • Added C extensions for several search functions as well as internal functions

  • Use C extensions if available, or pure-Python implementations otherwise

  • setup.py attempts to build C extensions, but installs without if build fails

  • Added --noexts setup.py option to avoid trying to build the C extensions

  • Greatly improved testing and coverage

0.2.2 (2014-03-27)

  • Added support for searching through BioPython Seq objects

  • Added specialized search function allowing only subsitutions and insertions

  • Fixed several bugs

0.2.1 (2014-03-14)

  • Fixed major match grouping bug

0.2.0 (2013-03-13)

  • New utility function find_near_matches() for easier use

  • Additional documentation

0.1.0 (2013-11-12)

  • Two working implementations

  • Extensive test suite; all tests passing

  • Full support for Python 2.6-2.7 and 3.1-3.3

  • Bumped status from Pre-Alpha to Alpha

0.0.1 (2013-11-01)

  • First release on PyPI.

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Details for the file fuzzysearch-0.7.1-cp27-cp27m-macosx_10_9_x86_64.whl.

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