fuzzysearch/README.rst

128 lines
4.2 KiB
ReStructuredText

===========
fuzzysearch
===========
.. image:: https://img.shields.io/pypi/v/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch
:alt: Latest Version
.. image:: https://img.shields.io/travis/taleinat/fuzzysearch.svg?branch=master
:target: https://travis-ci.org/taleinat/fuzzysearch/branches
:alt: Build & Tests Status
.. image:: https://img.shields.io/coveralls/taleinat/fuzzysearch.svg?branch=master
:target: https://coveralls.io/r/taleinat/fuzzysearch?branch=master
:alt: Test Coverage
.. image:: https://img.shields.io/pypi/dm/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch
:alt: Downloads
.. image:: https://img.shields.io/pypi/wheel/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch
:alt: Wheels
.. image:: https://img.shields.io/pypi/pyversions/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch
:alt: Supported Python versions
.. image:: https://img.shields.io/pypi/implementation/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch
:alt: Supported Python implementations
.. image:: https://img.shields.io/pypi/l/fuzzysearch.svg?style=flat
:target: https://pypi.python.org/pypi/fuzzysearch/
:alt: License
**Easy fuzzy search that just works, fast!**
.. code:: python
>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1)
[Match(start=3, end=9, dist=1)]
* approximate sub-string searches
* single, simple function to use
* chooses the fastest available search mechanism based on the given input
* uses the Levenshtein Distance metric with configurable parameters
* separately configure the max. allowed distance, substitutions, deletions
and insertions
* optional, highly optimized C and Cython implementations
* extensively tested
* free software: `MIT license <LICENSE>`_
For more info, see the `documentation <http://fuzzysearch.rtfd.org>`_.
Installation
------------
.. code::
$ 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:
.. code:: python
>>> 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)]
.. code:: python
>>> 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)]
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.
.. code:: python
>>> find_near_matches('PATTERN', '---PATERN---', max_l_dist=1)
[Match(start=3, end=9, dist=1)]
# 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)] # 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)]