iredis
aioredis
Our great sponsors
| iredis | aioredis | |
|---|---|---|
| 1 | 2 | |
| 2,486 | 2,269 | |
| - | - | |
| 7.8 | 0.0 | |
| 4 days ago | about 1 year ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
iredis
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5 Useful Database Command Line Tools
wget https://github.com/laixintao/iredis/releases/latest/download/iredis.tar.gz \ && tar -xzf iredis.tar.gz \ && ./iredis
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?
R3CON1Z3R - R3con1z3r is a lightweight Web information gathering tool with an intuitive features written in python. it provides a powerful environment in which open source intelligence (OSINT) web-based footprinting can be conducted quickly and thoroughly.
pottery - Redis for humans. 🌎🌍🌏
kube-shell - Kubernetes shell: An integrated shell for working with the Kubernetes
uvloop - Ultra fast asyncio event loop.
litecli - CLI for SQLite Databases with auto-completion and syntax highlighting
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
shiv - shiv is a command line utility for building fully self contained Python zipapps as outlined in PEP 441, but with all their dependencies included.
Dependency Injector - Dependency injection framework for Python
spline - Spline is a tool that is capable of running locally as well as part of well known pipelines like Jenkins (Jenkinsfile), Travis CI (.travis.yml) or similar ones.
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)
shell-functools - Functional programming tools for the shell
redis-py-sansio - A sansio-first approach to a Python Redis Client.