{ "info": { "author": "Adam Cohen", "author_email": "adam@seatgeek.com", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Developers", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6" ], "description": ".. image:: https://travis-ci.org/seatgeek/fuzzywuzzy.svg?branch=master\n :target: https://travis-ci.org/seatgeek/fuzzywuzzy\n\nFuzzyWuzzy\n==========\n\nFuzzy string matching like a boss. It uses `Levenshtein Distance `_ to calculate the differences between sequences in a simple-to-use package.\n\nRequirements\n============\n\n- Python 2.7 or higher\n- difflib\n- `python-Levenshtein `_ (optional, provides a 4-10x speedup in String\n Matching, though may result in `differing results for certain cases `_)\n\nFor testing\n~~~~~~~~~~~\n- pycodestyle\n- hypothesis\n- pytest\n\nInstallation\n============\n\nUsing PIP via PyPI\n\n.. code:: bash\n\n pip install fuzzywuzzy\n\nor the following to install `python-Levenshtein` too\n\n.. code:: bash\n\n pip install fuzzywuzzy[speedup]\n\n\nUsing PIP via Github\n\n.. code:: bash\n\n pip install git+git://github.com/seatgeek/fuzzywuzzy.git@0.17.0#egg=fuzzywuzzy\n\nAdding to your ``requirements.txt`` file (run ``pip install -r requirements.txt`` afterwards)\n\n.. code:: bash\n\n git+ssh://git@github.com/seatgeek/fuzzywuzzy.git@0.17.0#egg=fuzzywuzzy\n \nManually via GIT\n\n.. code:: bash\n\n git clone git://github.com/seatgeek/fuzzywuzzy.git fuzzywuzzy\n cd fuzzywuzzy\n python setup.py install\n\n\nUsage\n=====\n\n.. code:: python\n\n >>> from fuzzywuzzy import fuzz\n >>> from fuzzywuzzy import process\n\nSimple Ratio\n~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.ratio(\"this is a test\", \"this is a test!\")\n 97\n\nPartial Ratio\n~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.partial_ratio(\"this is a test\", \"this is a test!\")\n 100\n\nToken Sort Ratio\n~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.ratio(\"fuzzy wuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 91\n >>> fuzz.token_sort_ratio(\"fuzzy wuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 100\n\nToken Set Ratio\n~~~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.token_sort_ratio(\"fuzzy was a bear\", \"fuzzy fuzzy was a bear\")\n 84\n >>> fuzz.token_set_ratio(\"fuzzy was a bear\", \"fuzzy fuzzy was a bear\")\n 100\n\nProcess\n~~~~~~~\n\n.. code:: python\n\n >>> choices = [\"Atlanta Falcons\", \"New York Jets\", \"New York Giants\", \"Dallas Cowboys\"]\n >>> process.extract(\"new york jets\", choices, limit=2)\n [('New York Jets', 100), ('New York Giants', 78)]\n >>> process.extractOne(\"cowboys\", choices)\n (\"Dallas Cowboys\", 90)\n\nYou can also pass additional parameters to ``extractOne`` method to make it use a specific scorer. A typical use case is to match file paths:\n\n.. code:: python\n \n >>> process.extractOne(\"System of a down - Hypnotize - Heroin\", songs)\n ('/music/library/good/System of a Down/2005 - Hypnotize/01 - Attack.mp3', 86)\n >>> process.extractOne(\"System of a down - Hypnotize - Heroin\", songs, scorer=fuzz.token_sort_ratio)\n (\"/music/library/good/System of a Down/2005 - Hypnotize/10 - She's Like Heroin.mp3\", 61)\n\n.. |Build Status| image:: https://api.travis-ci.org/seatgeek/fuzzywuzzy.png?branch=master\n :target: https:travis-ci.org/seatgeek/fuzzywuzzy\n\nKnown Ports\n============\n\nFuzzyWuzzy is being ported to other languages too! 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