Consistent Hashing in Python

Update: This is not really a consistent hash. I'll fix the issues then repost. (Fixed here.)

Consistent Hashing is useful. I'm using it to build a Redis client with support for redundancy, and failover / node insertion.

import hashlib


class ConsistentHash(object):
    def __init__(self, partition_size=2):
        self.partition_size = partition_size 
        self.hashes = []

    def partition(self, arg):
        md5 = hashlib.md5(str(arg)).hexdigest()
        partition = int(md5[:self.partition_size], 16) 
        return partition

    def add(self, hash):
        self.hashes.append(hash)
        self.hashes.sort(cmp=
            lambda a,b: cmp(self.partition(a), self.partition(b)))

    def __getitem__(self, i): 
        return self.hashes[i%len(self.hashes)]

    def hash(self, key):
        i = self.partition(key) % len(self.hashes)
        return self[i], self[i+1], self[i+2]

Testing with the below code produces this beautiful graph. Perfect. :-) If you want to add more weight to a particular hash (server address) just add it more than once.

if __name__ == "__main__":
    from pygooglechart import PieChart2D
    c = ConsistentHash()
    keys = "ABCDEFG"
    print len(keys)
    for k in keys:
        c.add(k)
    d = {}
    for i in xrange(10000):
        h = c.hash(i)[0]
        count = d.get(h, 0)
        d[h] = count + 1 
    chart = PieChart2D(128, 128)
    chart.add_data([d[i] for i in keys])
    print chart.get_url()