fuzzy / README

.. -*- restructuredtext -*-


Fuzzy is a python library implementing common phonetic algorithms quickly.
Typically this is in string similarity exercises, but they're pretty versatile.

It uses C Extensions (via Pyrex) for speed. 

The algorithms are:

 * `Soundex <http://en.wikipedia.org/wiki/Soundex>`_
 * `NYSIIS <http://en.wikipedia.org/wiki/NYSIIS>`_
 * `Double Metaphone <http://en.wikipedia.org/wiki/Metaphone>`_ Based on Maurice
   Aubrey's C code from his perl implementation.

Installation should be easy if you have a C compiler such as gcc. All you should
need to do is `easy_install`/`pip install` it. If you have Pyrex it will
regenerate the C code, otherwise it will use the pre-generated code. Here's a 
basic installation on a clean virtualenv::

    (fuzzy_cean)Kotai:~ chmullig$ pip install https://bitbucket.org/yougov/fuzzy/get/1.0.tar.gz
    Downloading/unpacking https://bitbucket.org/yougov/fuzzy/get/1.0.tar.gz
      Downloading 1.0.tar.gz
      Running setup.py egg_info for package from https://bitbucket.org/yougov/fuzzy/get/1.0.tar.gz
    Installing collected packages: Fuzzy
      Running setup.py install for Fuzzy
        building 'fuzzy' extension
        gcc-4.2 -fno-strict-aliasing -fno-common -dynamic -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes 
            -DENABLE_DTRACE -arch i386 -arch ppc -arch x86_64 -pipe -I/System/Library/Frameworks/Python.framework/Versions/2.6/include/python2.6
            -c src/fuzzy.c -o build/temp.macosx-10.6-universal-2.6/src/fuzzy.o
        gcc-4.2 -fno-strict-aliasing -fno-common -dynamic -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes
            -DENABLE_DTRACE -arch i386 -arch ppc -arch x86_64 -pipe -I/System/Library/Frameworks/Python.framework/Versions/2.6/include/python2.6
            -c src/double_metaphone.c -o build/temp.macosx-10.6-universal-2.6/src/double_metaphone.o
        gcc-4.2 -Wl,-F. -bundle -undefined dynamic_lookup -arch i386 -arch ppc -arch x86_64
            build/temp.macosx-10.6-universal-2.6/src/fuzzy.o build/temp.macosx-10.6-universal-2.6/src/double_metaphone.o
            -o build/lib.macosx-10.6-universal-2.6/fuzzy.so
    Successfully installed Fuzzy
    Cleaning up...
    (fuzzy_cean)Kotai:~ chmullig$ 

The functions are quite easy to use!

>>> import fuzzy
>>> soundex = fuzzy.Soundex(4)
>>> soundex('fuzzy')
>>> dmeta = fuzzy.DMetaphone()
>>> dmeta('fuzzy')
['FS', None]
>>> fuzzy.nysiis('fuzzy')

Fuzzy's Double Metaphone was ~10 times faster than the pure python
implementation by  `Andrew Collins <http://www.atomodo.com/code/double-metaphone>`_
in some recent `testing <http://chmullig.com/2011/03/pypy-testing/>`_. 
Soundex and NYSIIS should be similarly faster. Using iPython's timeit::

  In [3]: timeit soundex('fuzzy')
  1000000 loops, best of 3: 326 ns per loop
  In [4]: timeit dmeta('fuzzy')
  100000 loops, best of 3: 2.18 us per loop
  In [5]: timeit fuzzy.nysiis('fuzzy')
  100000 loops, best of 3: 13.7 us per loop

Distance Metrics

We recommend the `Python-Levenshtein <http://code.google.com/p/pylevenshtein/>`_
module for fast, C based string distance/similarity metrics. Among others
functions it includes:

 * `Levenshtein <http://en.wikipedia.org/wiki/Levenshtein_distance>`_ edit distance
 * `Jaro <http://en.wikipedia.org/wiki/Jaro_distance>`_ distance
 * `Jaro-Winkler <http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance>`_ distance
 * `Hamming distance <http://en.wikipedia.org/wiki/Hamming_distance>`_

In testing it's been several times faster than comparable pure python
implementations of those algorithms.
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