uvloop VS aioredis

I wound up on a different team with pre-existing Python code so temporarily shelved my use of Go for a bit, and we used Sanic (an async Python framework built on top of the excellent uvloop & libuv that also powers Node.js) to build some APIs for live channel management & operations. We hand-wrote our OpenAPI and used it to generate documentation and a CLI, which was an improvement over what was there (or not) before. Other teams used the OpenAPI document to generate SDKs to interact with our service.

If you're looking for maximum requests per second you can change the asyncio event loop with one like UVLoop.

An optional package uvloop can also be install if working on Linux:

The source code from the project resides in the github, with more than 8.6k stars and 596 forks is a very popular github, but no new releases are made since 2018, looks pure much not maintained anymore, no PR's are accepted no Issues are closed, still without windows or macOS Silicon, or PyPy3 support. Japronto it self uses uvloop with more than 9k stars and 521 forks and different from japronto is seems to be well maintained.

If you are building server-side applications using Python 3 and async API and if you didn't use https://github.com/MagicStack/uvloop, you are missing out on performance big time.

Also, if you happen to build microservices, don't forget to try PyPy, that's another easy performance booster (if it's compatible to your app).

Not that bad actually, with a different event loop implementation (such as https://github.com/MagicStack/uvloop). Not sure how well it will perform in a browser though

And so I did some searching, and found that SearX isn't officially supported on Windows. Not to be deterred, I did another quick search and found that with pip and/or docker, you should be able to install SearX straightforwardly on Windows. After trying this for a bit, I realized that uvloop, a (questionably optional dependency of SearX) is not supported on Windows. I tried a couple things to get it to work, but they didn't end up working for me either through user error, ignorance, or plain old not working.

they also wrote uvloop [0] which is fantastic and advances the cutting edge of what can be done with modern asyncio-based Python. I saw a ~3x improvement in the throughput of a microservice I wrote when I first tried it out years ago. currently at $dayjob we just use it by default in every Python service, whether or not we expect that service to be performance-critical.

0: https://github.com/MagicStack/uvloop

If you manage to grok how uvloop works as well as Python's default asyncio loop scheduler, you'll understand this style. It is not by itself a parallelism enabler, but network I/O the coroutines triggered would run in parallel nevertheless, though CPU bound computations would not by default.

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.