Metadata-Version: 1.1
Name: fastBloomFilter
Version: 0.0.3
Summary: A fast and simple probabilistic bloom filter that supports compression
Home-page: http://github.com/daedalus/bloomfilter
Author: Dario Clavijo
Author-email: dclavijo@protonmail.com
License: UNKNOWN
Download-URL: http://github.com/daedalus/bloomfilter/tarball/0.0.3
Description: # Simple and fast pythonic bloomfilter
        
        From 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 – 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."
        
        This filter supports: 
        
            Saving, reloading, compressed bloomfilter file lrzip like
                for compression: lz4>lzo>zlib>bz2>lzma
                for decompression: lzma>bz2>zlib>lzo>lz4
            Stats
            Entropy analysis
            Internal and external hashing of data.
            raw filter merging
        
        Installing:
        
            sudo pip install fastbloomfilter
        
        External creating of the bloom filter file:
        
            python mkbloom.py /tmp/filter.blf
        
        Importing:
        
            bf = BloomFilter(filename='/tmp/filter.blf')
        
        Adding data to it:
        
            bf.add('30000')
            bf.add('1230213')
            bf.add('1')
            
        Adding data and at the same time querying it:
        
            print bf.update('1') # True
            print bf.update('1') # True
            
            print bf.update('2') # False
            print bf.update('2') # True
        
        Printing stats:
        
            bf.stat()
            
        Or:
            
            bf.info()
        
        Querying data:
        
            print bf.query('1') # True
            print bf.query('1230213') # True
            print bf.query('12') # False
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
