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All Samples(3)  |  Call(0)  |  Derive(0)  |  Import(3)
This module implements a bloom filter probabilistic data structure and
an a Scalable Bloom Filter that grows in size as your add more items to it
without increasing the false positive error_rate.

Requires the bitarray library: http://pypi.python.org/pypi/bitarray/

    >>> from pybloom import BloomFilter
    >>> f = BloomFilter(capacity=10000, error_rate=0.001)
    >>> for i in xrange(0, f.capacity):
    ...     _ = f.add(i)(more...)

src/p/y/python-web-HEAD/web.py   python-web(Download)
from lxml import etree
import pybloom
from urllib import quote_plus

src/p/y/pybloomfiltermmap-0.3.14/tests/comparisons/speedtest.py   pybloomfiltermmap(Download)
creators = [create_cbloomfilter]
    import pybloom
except ImportError:

src/p/y/pybloomfiltermmap-0.3.14/tests/comparisons/accuracytest.py   pybloomfiltermmap(Download)
def main():
    global pybloomfilter
    if len(sys.argv) > 1 and sys.argv[1].lower() == '-pybloom':
        import pybloom