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asyncio vs gevent: What are the differences?

Introduction:

In the world of Python, there are two popular options for asynchronous programming: asyncio and gevent. Both provide ways to write asynchronous code, but they have some key differences. In this article, we will explore these differences.

  1. Programming Model: The key difference between asyncio and gevent lies in their programming models. asyncio follows the "async/await" model, which is based on coroutines and allows for structured and readable asynchronous code. On the other hand, gevent follows the "greenlet" model, which is based on cooperative multitasking and relies on monkey-patching standard library modules. This difference in programming models leads to variations in how code is written and executed.

  2. Concurrency Model: In terms of concurrency, asyncio and gevent take different approaches. asyncio is based on an event loop, where tasks are scheduled and executed cooperatively. It provides a shared event loop that runs tasks one after another, which makes it suitable for I/O-bound operations. On the other hand, gevent uses greenlets, lightweight independent units of execution, that are managed by a hub. The hub schedules the greenlets to run concurrently, making it suitable for both I/O-bound and CPU-bound operations.

  3. Standard Library Compatibility: Another difference between asyncio and gevent lies in their compatibility with the standard library. asyncio is part of the Python standard library since Python 3.4, which means it has the advantage of being well-integrated and maintained. It provides a rich set of libraries and tools that can be used for various tasks. Gevent, on the other hand, is an external library that needs to be installed separately. While it provides compatibility with most of the standard library modules, there might be some modules that require additional monkey-patching.

  4. Performance: When it comes to performance, both asyncio and gevent have their strengths and weaknesses. asyncio provides good performance for I/O-bound operations due to its event loop-based concurrency model. However, it might not perform as well for CPU-bound operations due to the Global Interpreter Lock (GIL) in CPython. On the other hand, gevent's use of greenlets allows for high-performance concurrency, making it suitable for both I/O-bound and CPU-bound operations. However, it might not always outperform asyncio in terms of raw performance.

  5. Community and Ecosystem: Another aspect to consider is the community and ecosystem surrounding asyncio and gevent. asyncio has gained popularity and has a larger community as it is part of the Python standard library. It has a rich ecosystem with numerous libraries and frameworks built on top of it. Gevent, while not as popular as asyncio, still has a dedicated community and a good number of libraries available. However, the ecosystem might not be as extensive as asyncio.

  6. Compatibility with Libraries and Frameworks: Lastly, the compatibility of asyncio and gevent with existing libraries and frameworks can vary. As asyncio is part of the Python standard library, many libraries and frameworks have added asyncio support or have been built specifically with asyncio in mind. On the other hand, gevent's compatibility might be affected by the need for monkey-patching standard library modules. Some libraries and frameworks might not work seamlessly with gevent or might require additional modifications.

In Summary, asyncio and gevent have different programming and concurrency models, asyncio is part of the Python standard library with a larger community and ecosystem, while gevent provides high-performance concurrency and compatibility might be affected by monkey-patching.

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Pros of asyncio
Pros of gevent
  • 4
    Cooperative Multitasking
  • 4
    I/O Wait
  • 3
    Network Call
  • 2
    I/O bound computation
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    Cons of asyncio
    Cons of gevent
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      • 1
        Not native

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      What tools integrate with asyncio?
      What tools integrate with gevent?
      What are some alternatives to asyncio and gevent?
      Flask
      Flask is intended for getting started very quickly and was developed with best intentions in mind.
      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.
      Node.js
      Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
      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 is an event-driven networking engine written in Python and licensed under the open source ​MIT 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.
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