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        "author": "Dario Clavijo",
        "author_email": "dclavijo@protonmail.com",
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            "Development Status :: 1 - Planning",
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            "License :: OSI Approved :: GNU General Public License (GPL)",
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            "Programming Language :: Python"
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        "description": "# Simple and fast pythonic bloomfilter\n\nFrom wikipedia: \"A Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set. False positive matches are possible, but false negatives are not \u2013 in other words, a query returns either \"possibly in set\" or \"definitely not in set\". Elements can be added to the set, but not removed (though this can be addressed with a \"counting\" filter); the more elements that are added to the set, the larger the probability of false positives.\"\n\nThis filter supports: \n\n    Saving, reloading, compressed bloomfilter file lrzip like\n        for compression: lz4>lzo>zlib>bz2>lzma\n        for decompression: lzma>bz2>zlib>lzo>lz4\n    Stats\n    Entropy analysis\n    Internal and external hashing of data.\n    raw filter merging\n\nInstalling:\n\n    sudo pip install fastbloomfilter\n\nExternal creating of the bloom filter file:\n\n    python mkbloom.py /tmp/filter.blf\n\nImporting:\n\n    from fastBloomFilter import bloom\n\n    bf = bloom.BloomFilter(filename='/tmp/filter.blf')\n\nAdding data to it:\n\n    bf.add('30000')\n\n    bf.add('1230213')\n\n    bf.add('1')\n    \nAdding data and at the same time querying it:\n\n    print bf.update('1') # True\n\n    print bf.update('1') # True\n    \n    print bf.update('2') # False\n\n    print bf.update('2') # True\n\nPrinting stats:\n\n    bf.stat()\n    \nOr:\n    \n    bf.info()\n\nQuerying data:\n\n    print bf.query('1') # True\n\n    print bf.query('1230213') # True\n\n    print bf.query('12') # False\n",
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