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    "info": {
        "author": "Malthe Borch",
        "author_email": "mborch@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: C",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "SkipDict\n========\n\nA skip dict is a Python dictionary which is permanently sorted by\nvalue. This package provides a fast, idiomatic implementation written\nin C with an extensive test suite.\n\nThe data structure uses a `skip list\n<http://en.wikipedia.org/wiki/Skip_list>`_ internally.\n\nAn example use is a leaderboard where the skip dict provides\nlogarithmic access to the score and ranking of each user, as well as\nefficient iteration in either direction from any node.\n\nCompatible with Python 2.7+ and Python 3.3+.\n\n\nUsage\n-----\n\nThe skip dict works just like a normal dictionary except it maps only\nto floating point values::\n\n  from skipdict import SkipDict\n\n  skipdict = SkipDict(maxlevel=4)\n\n  skipdict['foo'] = 1.0\n  skipdict['bar'] = 2.0\n\nThe ``SkipDict`` optionally takes a dictionary or a sequence of\n``(key, value)`` pairs::\n\n  skipdict = SkipDict({'foo': 1.0, 'bar': 2.0})\n  skipdict = SkipDict(('foo', 1.0), ('bar', 1.0), ('bar', 1.0))\n\nNote that duplicates are automatically aggregated to a sum. To\nillustrate this, we can count the occurrences of letters in a text::\n\n  skipdict = SkipDict(\n      (char, 1) for char in\n      \"Everything popular is wrong. - Oscar Wilde\"\n  )\n\n  # The most frequent letter is a space.\n  skipdict.keys()[-1] == \" \"\n\nThe ``skipdict`` is sorted by value which means that iteration and\nstandard mapping protocol methods such as ``keys()``, ``values()`` and\n``items()`` return items in sorted order.\n\nEach of these methods have been extended with optional range arguments\n``min`` and ``max`` which limit iteration based on value. In addition,\nthe iterator objects support the item and slice protocols:\n\n>>> skipdict.keys(min=2.0)[0]\n'bar'\n>>> skipdict.keys(max=2.0)[1:]\n['bar']\n\nNote that the methods always return an iterator. Use ``list`` to\nexpand to a sequence:\n\n>>> iterator = skipdict.keys()\n>>> list(iterator)\n['bar']\n\nThe ``index(value)`` method returns the first key that has exactly the\nrequired value. If the value is not found then a ``KeyError``\nexception is raised.\n\n>>> skipdict.index(2.0)\n'bar'\n\n\nAlternatives\n------------\n\nFrancesco Romani wrote `pyskiplist\n<https://bitbucket.org/mojaves/pyskiplist>`_ which also provides an\nimplementation of the skip list datastructure for CPython written\nin C.\n\nPaul Colomiets wrote `sortedsets\n<https://github.com/tailhook/sortedsets>`_ which is an implementation\nin pure Python. The randomized test cases were adapted from this\npackage.\n\n\nLicense\n-------\n\nCopyright (c) 204 Malthe Borch <mborch@gmail.com>\n\nThis software is provided \"as-is\" under the BSD License.\n\n\nChanges\n-------\n\n1.0 (2014-09-26)\n----------------\n\n- Initial public release.",
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