dotify
aioredis
dotify | aioredis | |
---|---|---|
1 | 2 | |
4 | 2,269 | |
- | - | |
0.0 | 0.0 | |
3 days ago | about 1 year ago | |
Python | Python | |
MIT License | MIT License |
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dotify
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Downloading music from Spotify
Inspired by the functionality provided by https://github.com/spotDL/spotify-downloader, I decided to implement https://github.com/billsioros/dotify, a spiritual sibling of it, BUT in the form of heavily object oriented python library. Feel free to check it out. I would greatly appreciate any feedback either directly in this thread or via GitHub Issues. PRs are also welcome !
aioredis
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Pooling in aioredis may be dangerous
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.
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Tips using Redis with FastAPI
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.
What are some alternatives?
falconpy - The CrowdStrike Falcon SDK for Python
pottery - Redis for humans. 🌎🌍🌏
gybe - A simple YAML transpiler for rendering Kubernetes manifests using python type-hints.
uvloop - Ultra fast asyncio event loop.
spotify-downloader - Download your Spotify playlists and songs along with album art and metadata (from YouTube if a match is found).
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
PyJNIus - Access Java classes from Python
Dependency Injector - Dependency injection framework for Python
pydantic - Data validation using Python type hints
fastapi-redis-cache - A simple and robust caching solution for FastAPI that interprets request header values and creates proper response header values (powered by Redis)
redis-py-sansio - A sansio-first approach to a Python Redis Client.
faust - Python Stream Processing. A Faust fork