Package: ring_redis
RING REDIS===What for:---I want a lightweight, High Available & Extensible cache solution using redis, but nutcracker is too heavy for a system with only 2 or 3 application servers and 2 or 3 redis instances. and there isnt a good enough implementation of consistant hash using pure python. so I wrote this. I used it in 2 project and they are running well till now when half a year passed. so I shared it for people who have the same requirement.Features:---- lightweight & pure python solution- auto eject & rediscover redis nodes- O(log(slice_number)) time complexity for a consistant hash calculation. (slice_number = max(2000, 200 * node_number))- O(slice_number * log(slice_number)) time complexity for hash ring rebuilding.- use O(slice_number) memory space always.API list:---- `redis_dict(redis_confs, prefix='', key=str, expire=None, on_fail=None, on_node_ejected=None, on_node_rediscovered=None, retry_ratio=1e-2, hash_function=crc32)`: construct a redis_dict instance, which can be used as a normal python dict- `some_redis_dict_instance.visit_redis(cmd, k, args)`: visit lower level redis apis- `some_redis_dict_instance.get_entry(k)`: return the really redis entry of k- `some_redis_dict_instance.alive_hash(redis_entry)`: return the node name for redis_entry via alive_hash- `some_redis_dict_instance.total_hash(redis_entry)`: return the node name for redis_entry via total_hash- `len(some_redis_dict_instance.alive_hash)`: return the alive nodes numberInstall---### via pip```shellpip install ring_redis```### via source code```shellcd path/to/ring_redispython setup.py install```How to use:---```python################### your redis configuration #####################REDIS_CONF = {'group0' : {'node0': {'capacity': 50 * 1024 ** 2,'connection': {'host' : '192.168.230.45','port' : 15061,'db': 0,'socket_timeout': 5e-3,},},'node1': {'capacity': 50 * 1024 ** 2,'connection': {'host' : '192.168.230.46','port' : 15061,'db': 0,'socket_timeout': 5e-3,},},},}############################ useage ##############################from ring_redis import redis_dicttest = redis_dict(REDIS_CONF['group0'], prefix='test.', expire=20)test['a'] = 'abc'print("test['a'] : %s" % (test['a']))print("len(test) : %s" % (len(test)))print("test.keys() : %s" % (test.keys()[:100]))print("'a' in test? : %s" % ('a' in test))print("'b' in test? : %s" % ('b' in test))print("test.visit_redis('incr', 'x', 1) : %s" % (test.visit_redis('incr', 'x', 1)))print("test.get_entry('x') : %s" % (test.get_entry('x')))print("test.total_hash(test.get_entry('x')) : %s" % (test.total_hash(test.get_entry('x'))))print("test.alive_hash(test.get_entry('x')) : %s" % (test.alive_hash(test.get_entry('x'))))```Notice:---- The really redis entry equals to the dict key **only if** `prefix + key(dict_key) == redis_entry`- The configuration field 'socket_timeout' in REDIS_CONF **should be choosed carefully**, do some test yourself to findout the expected time(in seconds, depending on your network delay & bandwidth) needed for your biggest data case.- Python built-in function hash is neither consistant nor equally distributed, so **don't use it** as hash_function.- If non instance of the redis cluster available, exception `RedisClusterUnavailable` will be raised, you should pass `on_fail` as argument of redis_dict constructor or catch this exception to **handler this situation yourself**.