FileSizeSHA1Type
pybloom.py12K51ad230731340af36a0144236ad8ba7c2042905eASCII Java program text
This software is Public Domain. To view a copy of the public domain dedication,
visit http://creativecommons.org/licenses/publicdomain/ or send a letter to
Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

I ask and expect, but do not require, that you contribute any bug fixes and strongly 
related additional features back to me with the same license.
 
 
pybloom		index
/home/agl/pybloom/pybloom.py

# Bloom filters in Python
# Adam Langley <agl@imperialviolet.org>

 
Modules
       
array
struct

 
Classes
       
__builtin__.object
Bloom
CountedBloom

 
class Bloom(__builtin__.object)
    Bloom filters provide a fast and compact way of checking set membership. They do this by introducing a risk of a 
false positive (but there are no false negatives).
 
For more information see http://www.cs.wisc.edu/~cao/papers/summary-cache/node8.html
 
  Methods defined here:
__contains__(self, val)
__init__(self, bytes, hashes)
@bytes is the size of the bloom filter in 8-bit bytes and @hashes is the number of hash functions to use. Consult the
web page linked above for values to use. If in doubt, bytes = num_elements and hashes = 4
insert(self, val)
Data and other attributes defined here:
__dict__ = <dictproxy object>
dictionary for instance variables (if defined)
__weakref__ = <attribute '__weakref__' of 'Bloom' objects>
list of weak references to the object (if defined)
bitmask = [128, 64, 32, 16, 8, 4, 2, 1]

 
class CountedBloom(Bloom)
    Just like a Bloom filter, but provides counting (e.g. you can delete as well). This uses 4 bits per bucket, so is
generally four times larger than the same non-counted bloom filter.
 
 
Method resolution order:
CountedBloom
Bloom
__builtin__.object
Methods defined here:
__contains__(self, val)
__delitem__(self, val)
__init__(self, buckets, hashes)
Please note that @buckets must be even. Also note that with a Bloom object you give the number of *bytes* and each byte is 8 buckets. Here you're giving the number of buckets.
insert(self, val)
Data and other attributes inherited from Bloom:
__dict__ = <dictproxy object>
dictionary for instance variables (if defined)
__weakref__ = <attribute '__weakref__' of 'Bloom' objects>
list of weak references to the object (if defined)
bitmask = [128, 64, 32, 16, 8, 4, 2, 1]

 
Functions
       
mixarray_init(mixarray)

 
Data
        __all__ = ['Bloom']
mixarray = array('B', [49, 118, 63, 252, 13, ...])

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