uvicorn-gunicorn-docker | Docker image with Uvicorn | Continuous Deployment library

by tiangolo Python Version: 0.7.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | uvicorn-gunicorn-docker Summary

uvicorn-gunicorn-docker is a Python library typically used in Devops, Continuous Deployment, Fastapi, Docker applications. uvicorn-gunicorn-docker has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However uvicorn-gunicorn-docker build file is not available. You can download it from GitHub.

Python web applications running with Uvicorn (using the "ASGI" specification for Python asynchronous web applications) have shown to have some of the best performances, as measured by third-party benchmarks. The achievable performance is on par with (and in many cases superior to) Go and Node.js frameworks. This image has an auto-tuning mechanism included to start a number of worker processes based on the available CPU cores. That way you can just add your code and get high performance automatically, which is useful in simple deployments.

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Support

uvicorn-gunicorn-docker has a low active ecosystem.

It has 530 star(s) with 245 fork(s). There are 14 watchers for this library.

It had no major release in the last 12 months.

There are 14 open issues and 35 have been closed. On average issues are closed in 258 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of uvicorn-gunicorn-docker is 0.7.0

Quality

uvicorn-gunicorn-docker has 0 bugs and 0 code smells.

Security

uvicorn-gunicorn-docker has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

uvicorn-gunicorn-docker code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

uvicorn-gunicorn-docker is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

uvicorn-gunicorn-docker releases are available to install and integrate.

uvicorn-gunicorn-docker has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

uvicorn-gunicorn-docker saves you 535 person hours of effort in developing the same functionality from scratch.

It has 1253 lines of code, 63 functions and 44 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed uvicorn-gunicorn-docker and discovered the below as its top functions. This is intended to give you an instant insight into uvicorn-gunicorn-docker implemented functionality, and help decide if they suit your requirements.

Sends a message .
Print version information .
Process all environments .
Process tag .
Initialize the request scope .

Get all kandi verified functions for this library.

uvicorn-gunicorn-docker Key Features

No Key Features are available at this moment for uvicorn-gunicorn-docker.

uvicorn-gunicorn-docker Examples and Code Snippets

No Code Snippets are available at this moment for uvicorn-gunicorn-docker.

Community Discussions

Trending Discussions on uvicorn-gunicorn-docker

Python functools LRU cache shared between multiple processes

QUESTION

Python functools LRU cache shared between multiple processes

Asked 2022-Jan-21 at 13:50

Let's say I have 4 load-balanced Python API processes that calculate the factorial of a number.

Let's say factorial returns a Pydantic object or deeply nested dict. I do not want to use Redis for caching because nested dict/list serialization is expensive. So I use the LRU function cache.

Problem: 4 LRU caches exist for each process. When I clear the cache it clears for only 1 process (whichever catches the request).

I want to share the LRU cache between all 4 processes. Would a custom decorator using multiprocessing.shared_memory be possible?
If that is not possible, I want to at least clear the cache of all processes. Using multi-processing Queue or Listener/Client blocks the API functionality as I have to while True.

Multiple Python API processes running this code:

...

ANSWER

Answered 2022-Jan-21 at 13:50

My problem was not the slow JSON/pickle serialization. It was slow value retrieval from Redis storage due to larger cached variable size.

Here's a simple solution to share data between Python processes. This solution converts your Python variables to bytes (pickles them) so if slow serialization is your problem, this might not be for you.

Server (separate Python process that holds the cache):

Source https://stackoverflow.com/questions/70651653

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install uvicorn-gunicorn-docker

You can download it from GitHub.
You can use uvicorn-gunicorn-docker like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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