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    "info": {
        "author": "Grey Lee",
        "author_email": "bcse@bcse.tw",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.5",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.1",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "===============================\r\nString Score\r\n===============================\r\n\r\n.. image:: https://badge.fury.io/py/stringscore.png\r\n    :alt: PyPI version\r\n    :target: http://badge.fury.io/py/stringscore\r\n\r\n.. image:: https://travis-ci.org/bcse/stringscore.png?branch=master\r\n    :alt: Build Status\r\n    :target: https://travis-ci.org/bcse/stringscore\r\n\r\n.. image:: https://coveralls.io/repos/bcse/stringscore/badge.png\r\n    :alt: Coverage Status\r\n    :target: https://coveralls.io/r/bcse/stringscore\r\n\r\n.. image:: https://pypip.in/d/stringscore/badge.png\r\n    :alt: Downloads\r\n    :target: https://crate.io/packages/stringscore?version=latest\r\n\r\n\r\nAn algorithm provides scores between 0.0 (no match) to 1.0 (perfect match) for a comparison of two strings.\r\n\r\nThe algorithm is designed for auto-completion. For string similarity, please check `Levenshtein distance`_ (`Wagner\u2013Fischer algorithm`_).\r\n\r\n.. _Levenshtein distance: https://en.wikipedia.org/wiki/Levenshtein_distance\r\n.. _Wagner\u2013Fischer algorithm: https://en.wikipedia.org/wiki/Wagner%E2%80%93Fischer_algorithm\r\n\r\nUsage\r\n-----\r\n\r\nInclude the library:\r\n\r\n::\r\n\r\n    from stringscore import liquidmetal\r\n\r\n\r\nScore any string against an abbreviation:\r\n\r\n::\r\n\r\n    >>> liquidmetal.score('FooBar', 'foo')\r\n    0.95\r\n    >>> liquidmetal.score('FooBar', 'fb')\r\n    0.916666666667\r\n    >>> liquidmetal.score('Foo Bar', 'fb')\r\n    0.928571428571\r\n    >>> liquidmetal.score('Foo Bar', 'baz')\r\n    0.0\r\n    >>> liquidmetal.score('Foo Bar', '')\r\n    0.8\r\n\r\n\r\nSimilar Works\r\n-------------\r\n\r\n* Quicksilver's scoreForAbbreviation_ algorithm by Alcor (Blacktree, Inc)\r\n* LiquidMetal_ by Ryan McGeary\r\n* string_score_ by Joshaven Potter\r\n* `jQuery.fuzzyMatch`_ by Rapportive_\r\n\r\n.. _scoreForAbbreviation: https://github.com/quicksilver/Quicksilver/blob/master/Quicksilver/Code-QuickStepFoundation/NSString_BLTRExtensions.m#L53\r\n.. _LiquidMetal: https://github.com/rmm5t/liquidmetal\r\n.. _string_score: https://github.com/joshaven/string_score\r\n.. _jQuery.fuzzyMatch: https://github.com/rapportive-oss/jquery-fuzzymatch\r\n.. _Rapportive: http://rapportive.com/\r\n\r\nLicense\r\n-------\r\n\r\nString Score is released under the `MIT License`_.\r\n\r\n.. _MIT License: http://opensource.org/licenses/MIT\r\n\r\nCredits\r\n-------\r\n\r\n| Copyright \u00a9 2003 Blacktree, Inc (Original author of Quicksilver_)\r\n| Copyright \u00a9 2009 Ryan McGeary (Author of LiquidMetal_)\r\n| Copyright \u00a9 2013 Grey Lee\r\n\r\n.. _Quicksilver: https://github.com/quicksilver/Quicksilver\r\n\r\n\r\n.. image:: https://d2weczhvl823v0.cloudfront.net/bcse/stringscore/trend.png\r\n    :alt: Bitdeli badge\r\n    :target: https://bitdeli.com/free\r\n\r\nHistory\r\n-------\r\n\r\n0.1.0 (2013-02-25)\r\n++++++++++++++++++\r\n\r\n* First release.",
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        "summary": "An algorithm provides scores between 0.0 (no match) to 1.0 (perfect match) for a comparison of two strings.",
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