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Fast Python phonetic algorithms

Project description

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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 Cython) for speed.

The algorithms are:

Installation

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 Cython 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$

Usage

The functions are quite easy to use!

>>> import fuzzy
>>> soundex = fuzzy.Soundex(4)
>>> soundex('fuzzy')
'F200'
>>> dmeta = fuzzy.DMetaphone()
>>> dmeta('fuzzy')
['FS', None]
>>> fuzzy.nysiis('fuzzy')
'FASY'

Performance

Fuzzy’s Double Metaphone was ~10 times faster than the pure python implementation by Andrew Collins in some recent 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 module for fast, C based string distance/similarity metrics. Among others functions it includes:

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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for Fuzzy, version 1.2
Filename, size File type Python version Upload date Hashes
Filename, size Fuzzy-1.2.tar.gz (15.3 kB) File type Source Python version None Upload date Hashes View hashes

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