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    "info": {
        "author": "Bram Gerritsen",
        "author_email": "b.gerritsen@uu.nl",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: Text Processing :: Indexing",
            "Topic :: Text Processing :: Linguistic"
        ],
        "description": "vtrie\n=====\n\nTrie structure supporting approximate string matching (substitutions only) for\nPython (2.x and 3.x).\n\n.. NOTE::\n\n        Only ascii strings are supported. Hence, Python 3 users should use\n        'b' prefix to insert strings into the trie.\n\nInstallation\n============\n\n::\n\n        pip install vtrie\n\nFeatures\n========\n\n* It is similar to a dict() in general usage, and supports much of the dict()\n  interface:\n\n  * __len__(): number of items in the trie\n  * __contains()__\n  * __getitem()__\n  * __setitem()__\n  * __delitem()__\n  * __sizeof()__: size of the trie in bytes\n  * __repr()__: dict-like output, showing contents of the trie\n  * has_key()\n  * setdefault()\n  * get()\n  * pop()\n  * popitem()\n  * keys()\n  * values()\n  * items()\n  * iterkeys()\n  * itervalues()\n  * iteritems()\n\n* Trie-specific methods:\n\n  * num_nodes(): number of nodes\n  * longest_prefix(k): find longest key matching the beginning of k,\n    returning (key, value) pair as a 2-tuple. None is returned if no match.\n  * suffixes(k): iterate over all (suffix, value) pairs as 2-tuples, that\n    have k as a prefix.\n  * neighbors(key = k, maxhd = n): iterate over all\n    (Hamming distance, key, value) triples, as 3 tuples, where key and k\n    differ by at least 1, but maximally n characters.\n    Note, one can only search for neighbors of *existing* keys.\n  * pairs(keylen = l, maxhd = n): iterate over *ALL*\n    (Hamming distance, key1, value1, key2, value2) 5-tuples where key1 and key2\n    differ by at least 1, but maximally n characters. Note, pairs() returns a\n    dirty iterator, meaning that nodes in the trie are modified while the\n    iterator is running. An exception will be thrown when iterating with more\n    than one dirty iterator.\n\n* Pickling\n\nUsage\n=====\n\nCreate a trie::\n\n        >>> from vtrie import Trie\n        >>> t = Trie()\n\nAdd strings to the trie. Currently, only ascii strings are supported::\n\n        >>> t[b\"Hello\"] = 123\n        >>> t[b\"World\"] = {\"my\": \"dict\"}\n        >>> t[b\"foo\"] = None\n\nCheck if \"Hello\" is in the trie::\n\n        >>> b\"Hello\" in t\n        True\n\nShow all inserted strings sharing the same prefix::\n\n        >>> t[b\"foo\"] = 0\n        >>> t[b\"foobar\"] = 1\n        >>> t[b\"fooo\"] = 2\n        >>> t[b\"hello\"] = 3\n        >>> list(t.suffixes(b\"fo\"))\n        [('o', 0), ('obar', 1), ('oo', 2)]\n\nSearch for keys that differ by less than a given number of substitutions from\nthe provided key. The results are tuples with first the Hamming distance\nbetween the given key and the found key, then the found key and its value::\n\n        >>> t[b\"hello world\"] = 0\n        >>> t[b\"*ello world\"] = \"a\"\n        >>> t[b\"*ell* world\"] = \"b\"\n        >>> t[b\"*ell* w*rld\"] = \"c\"\n        >>> t[b\"hell* w*rl*\"] = \"d\"\n        >>> list(t.neighbors(b\"hello world\", maxhd = 1))\n        [(1, '*ello world', 'a')]\n        >>> list(t.neighbors(b\"hello world\", maxhd = 2))\n        [(1, '*ello world', 'a'), (2, '*ell* world', 'b')]\n        >>> print(\"\\n\".join(map(str,list(t.neighbors(b\"hello world\", 3)))))\n        (3, 'hell* w*rl*', 'd')\n        (1, '*ello world', 'a')\n        (2, '*ell* world', 'b')\n        (3, '*ell* w*rld', 'c')\n\nSearch for all keys of a certain length that are within a certain Hamming of\neach other. The results are tuples with first the Hamming distance between the\nfound keys, then the first key and its value, and then the second key and\nits value::\n\n        >>> print(\"\\n\".join(map(str,list(t.pairs(keylen = 11, maxhd = 2)))))\n        (1, 'hello world', 0, '*ello world', 'a')\n        (2, 'hello world', 0, '*ell* world', 'b')\n        (2, 'hell* w*rl*', 'd', '*ell* w*rld', 'c')\n        (1, '*ello world', 'a', '*ell* world', 'b')\n        (2, '*ello world', 'a', '*ell* w*rld', 'c')\n        (1, '*ell* world', 'b', '*ell* w*rld', 'c')",
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        "license": "GPLv3",
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        "name": "vtrie",
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        "summary": "A trie structure supporting fuzzy string searches.",
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