Installation¶

Just install using pip:

$ pip install fuzzysearch

Features¶

• Fuzzy sub-sequence search: Find parts of a sequence which match a given sub-sequence up to a given maximum Levenshtein distance.
• Set individual limits for the number of substitutions, insertions and/or deletions allowed for a near-match.
• Includes optimized implementations for specific use-cases, e.g. only allowing substitutions in near-matches.

Simple Example¶

You can usually just use the find_near_matches() utility function, which chooses a suitable fuzzy search implementation according to the given parameters:

>>> from fuzzysearch import find_near_matches
>>> find_near_matches('PATTERN', 'aaaPATERNaaa', max_l_dist=1)
[Match(start=3, end=9, dist=1)]

Advanced Example¶

If needed you can choose a specific search implementation, such as find_near_matches_with_ngrams():

>>> sequence = '''\
GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA
TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA
CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG
GGGATAGG'''
>>> subsequence = 'TGCACTGTAGGGATAACAAT' #distance 1
>>> max_distance = 2

>>> from fuzzysearch import find_near_matches_with_ngrams
>>> find_near_matches_with_ngrams(subsequence, sequence, max_distance)
[Match(start=3, end=24, dist=1)]

Simple Example¶

You can usually just use the find_near_matches() utility function, which chooses a suitable fuzzy search implementation according to the given parameters:

>>> from fuzzysearch import find_near_matches
>>> find_near_matches('PATTERN', 'aaaPATERNaaa', max_l_dist=1)
[Match(start=3, end=9, dist=1)]

Advanced Example¶

If needed you can choose a specific search implementation, such as find_near_matches_with_ngrams():

>>> sequence = '''\
GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA
TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA
CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG
GGGATAGG'''
>>> subsequence = 'TGCACTGTAGGGATAACAAT' #distance 1
>>> max_distance = 2

>>> from fuzzysearch import find_near_matches_with_ngrams
>>> find_near_matches_with_ngrams(subsequence, sequence, max_distance)
[Match(start=3, end=24, dist=1)]

Types of Contributions¶

Get Started!¶

Ready to contribute? Here’s how to set up fuzzysearch for local development.

1. Fork the fuzzysearch repo on GitHub.

2. Clone your fork locally:

   $ git clone git@github.com:your_name_here/fuzzysearch.git
   

3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:

   $ mkvirtualenv fuzzysearch
   $ cd fuzzysearch/
   $ python setup.py develop
   

4. Create a branch for local development:

   $ git checkout -b name-of-your-bugfix-or-feature
   

Now you can make your changes locally.

5. When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

  $ flake8 fuzzysearch tests
        $ python setup.py test
  $ tox

To get flake8 and tox, just pip install them into your virtualenv.

6. Commit your changes and push your branch to GitHub:

   $ git add .
   $ git commit -m "Your detailed description of your changes."
   $ git push origin name-of-your-bugfix-or-feature
   

7. Submit a pull request through the GitHub website.

Pull Request Guidelines¶

Before you submit a pull request, check that it meets these guidelines:

1. The pull request should include tests.
2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
3. The pull request should work for Python 2.6, 2.7, and 3.3, and for PyPy. Check https://travis-ci.org/taleinat/fuzzysearch/pull_requests and make sure that the tests pass for all supported Python versions.

Tips¶

To run a subset of tests:

$ python -m unittest tests.test_fuzzysearch

Development Lead¶

• Tal Einat <taleinat@gmail.com>

Contributors¶

None yet. Why not be the first?

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.