aioredis VS pottery

First, it was aioredis library. We are using sentinel based client because with this we can achieve failover easily. Aioredis spawn pool of connections, that transparently reconnects (and here third thing — FOREVER, hello DDOS) to our sentinel nodes, and then to master node. It supposed to do so. Also, we found that if you are not limiting maximum connections count, library will do it for you and set it as 2 ** 31 (here you can see it) — this is fourth thing. Furthermore, pool in our version (2.0.1) not closing automatically, and it makes the problem worse.

I'm hoping to leverage Redis with my project, and I was curious as to if anyone had any general pointers as to how best to manage the DB connection. I'm using aioredis such that I can leverage the async functionality, but I haven't been very happy with the library's documentation surrounding how best to leverage the connection pool. Most of the examples create and tear down the pool immediately without showing how best to manage its lifespan.

However, as an alternative, consider my library, Pottery. Pottery offers some similar functionality to Redis OM, and Pottery is production ready.

This isn’t for Node.js… But if you’re using Python, you might want to check out Pottery. Pottery provides the functionality you’re describing and much more.

Shameless plug: Pottery: Redis for Humans. Its goal it to make Redis far easier to use by exposing Redis functionality via native Pythonic APIs like dicts, sets, lists, locks, etc.

I have a question about https://github.com/brainix/pottery. It provides a nice Pythonic API by wrapping Redis constructs with Python Redis-backed data structures (Dict, Deque, etc.). I am using it in a Fastapi microservice project, which is obviously async.

Pottery — Pythonic Redis utilities, including a distributed lock