fuzzysearch 0.7.0

fuzzysearch is useful for finding approximate subsequence matches

Easy Python fuzzy search that just works, fast!

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

• Approximate sub-string searches

• 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 insertions

• Advanced algorithms with optional C and Cython optimizations

• Properly handles Unicode; special optimizations for binary data

• Extensively tested

• Free software: MIT license

For more info, see the documentation.

Installation

$ 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

0.7.0 (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.