redisbloom-py is a package that gives developers easy access to several probabilistic data structures. The package extends redis-py's interface with RedisBloom's API.
$ pip install redisbloom
# Using Bloom Filter
from redisbloom.client import Client
rb = Client()
rb.bfCreate('bloom', 0.01, 1000)
rb.bfAdd('bloom', 'foo') # returns 1
rb.bfAdd('bloom', 'foo') # returns 0
rb.bfExists('bloom', 'foo') # returns 1
rb.bfExists('bloom', 'noexist') # returns 0
# Using Cuckoo Filter
from redisbloom.client import Client
rb = Client()
rb.cfCreate('cuckoo', 1000)
rb.cfAdd('cuckoo', 'filter') # returns 1
rb.cfAddNX('cuckoo', 'filter') # returns 0
rb.cfExists('cuckoo', 'filter') # returns 1
rb.cfExists('cuckoo', 'noexist') # returns 0
# Using Count-Min Sketch
from redisbloom.client import Client
rb = Client()
rb.cmsInitByDim('dim', 1000, 5)
rb.cmsIncrBy('dim', ['foo'], [5])
rb.cmsIncrBy('dim', ['foo', 'bar'], [5, 15])
rb.cmsQuery('dim', 'foo', 'bar') # returns [10, 15]
# Using Top-K
from redisbloom.client import Client
rb = Client()
rb.topkReserve('topk', 3, 20, 3, 0.9)
rb.topkAdd('topk', 'A', 'B', 'C', 'D', 'E', 'A', 'A', 'B',
'C', 'G', 'D', 'B', 'D', 'A', 'E', 'E')
rb.topkQuery('topk', 'A', 'B', 'C', 'D') # returns [1, 1, 0, 1]
rb.topkCount('topk', 'A', 'B', 'C', 'D') # returns [4, 3, 2, 3]
rb.topkList('topk') # returns ['D', 'A', 'B']
For complete documentation about RedisBloom's commands, refer to RedisBloom's website.