Alternatives to gevent logo

Alternatives to gevent

asyncio, Gunicorn, Tornado, Twisted, and Celery are the most popular alternatives and competitors to gevent.
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What is gevent and what are its top alternatives?

It is a coroutine -based Python networking library that uses greenlet to provide a high-level synchronous API on top of the libev or libuv event loop.
gevent is a tool in the Web Servers category of a tech stack.
gevent is an open source tool with GitHub stars and GitHub forks. Here’s a link to gevent's open source repository on GitHub

Top Alternatives to gevent

  • asyncio

    asyncio

    This module provides infrastructure for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, running network clients and servers, and other related primitives. ...

  • Gunicorn

    Gunicorn

    Gunicorn is a pre-fork worker model ported from Ruby's Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resources, and fairly speedy. ...

  • Tornado

    Tornado

    By using non-blocking network I/O, Tornado can scale to tens of thousands of open connections, making it ideal for long polling, WebSockets, and other applications that require a long-lived connection to each user. ...

  • Twisted

    Twisted

    Twisted is an event-driven networking engine written in Python and licensed under the open source ‚ÄčMIT license. Twisted runs on Python 2 and an ever growing subset also works with Python 3. Twisted also supports many common network protocols, including SMTP, POP3, IMAP, SSHv2, and DNS. ...

  • Celery

    Celery

    Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. ...

  • Waitress

    Waitress

    It is meant to be a production-quality pure-Python WSGI server with very acceptable performance. It has no dependencies except ones which live in the Python standard library. It runs on CPython on Unix and Windows under Python 2.7+ and Python 3.4+. It is also known to run on PyPy 1.6.0 on UNIX. ...

  • uWSGI

    uWSGI

    The uWSGI project aims at developing a full stack for building hosting services. ...

  • NGINX

    NGINX

    nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...

gevent alternatives & related posts

asyncio logo

asyncio

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Asynchronous I/O, event loop, coroutines and tasks
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related asyncio posts

Jelena Dedovic

Investigating Tortoise ORM and GINO ORM...

I need to introduce some async ORM with the current stack: Tornado with asyncio loop, AIOHTTP, with PostgreSQL and MSSQL. This project revolves heavily around realtime and due to the realtime requirements, blocking during database access is not acceptable.

Considering that these ORMs are both young projects, I wondered if anybody had some experience with similar stack and these async ORMs?

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Gunicorn logo

Gunicorn

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A Python WSGI HTTP Server for UNIX
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PROS OF GUNICORN
CONS OF GUNICORN
    No cons available

    related Gunicorn posts

    Pierre Chapuis

    Unlike our frontend, we chose Flask, a microframework, for our backend. We use it with Python 3 and Gunicorn.

    One of the reasons was that I have significant experience with this framework. However, it also was a rather straightforward choice given that our backend almost only serves REST APIs, and that most of the work is talking to the database with SQLAlchemy .

    We could have gone with something like Hug but it is kind of early. We might revisit that decision for new services later on.

    See more

    I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

    uWSGI ‚Äúaims at developing a full stack for building hosting services‚ÄĚ - if that‚Äôs a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the ‚Äúhosting service‚ÄĚ is provided and managed for me.

    See more
    Tornado logo

    Tornado

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    A Python web framework and asynchronous networking library, originally developed at FriendFeed
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    related Tornado posts

    Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

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    Twisted logo

    Twisted

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    Event-driven networking engine written in Python
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    related Twisted posts

    Celery logo

    Celery

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    Distributed task queue
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    related Celery posts

    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 1.1M views
    Shared insights
    on
    Celery
    RabbitMQ
    at

    As Sentry runs throughout the day, there are about 50 different offline tasks that we execute‚ÄĒanything from ‚Äúprocess this event, pretty please‚ÄĚ to ‚Äúsend all of these cool people some emails.‚ÄĚ There are some that we execute once a day and some that execute thousands per second.

    Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

    #MessageQueue

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    Michael Mota
    Founder at AlterEstate · | 6 upvotes · 227.1K views

    Automations are what makes a CRM powerful. With Celery and RabbitMQ we've been able to make powerful automations that truly works for our clients. Such as for example, automatic daily reports, reminders for their activities, important notifications regarding their client activities and actions on the website and more.

    We use Celery basically for everything that needs to be scheduled for the future, and using RabbitMQ as our Queue-broker is amazing since it fully integrates with Django and Celery storing on our database results of the tasks done so we can see if anything fails immediately.

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    Waitress logo

    Waitress

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    A production-quality pure-Python WSGI server
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    PROS OF WAITRESS
      No pros available
      CONS OF WAITRESS
        No cons available

        related Waitress posts

        uWSGI logo

        uWSGI

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        uWSGI application server container
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        PROS OF UWSGI
        CONS OF UWSGI
          No cons available

          related uWSGI posts

          I find I really like using GitHub because its issue tracker integrates really well into my project flow and the projects feature allows me to organize different efforts into boards. The automation features allow my issues to automatically progress through some states on the boards when I merge pull requests.

          My Python / Django app is deployed on Heroku with PostgreSQL database and uWSGI webserver.

          See more

          I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

          uWSGI ‚Äúaims at developing a full stack for building hosting services‚ÄĚ - if that‚Äôs a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the ‚Äúhosting service‚ÄĚ is provided and managed for me.

          See more

          related NGINX posts

          Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

          We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

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          Gabriel Pa
          Shared insights
          on
          Traefik
          NGINX
          at

          We switched to Traefik so we can use the REST API to dynamically configure subdomains and have the ability to redirect between multiple servers.

          We still use nginx with a docker-compose to expose the traffic from our APIs and TCP microservices, but for managing routing to the internet Traefik does a much better job

          The biggest win for naologic was the ability to set dynamic configurations without having to restart the server

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