asyncoro

Asyncoro

asyncoro is an open-source Python library for asynchronous programming using coroutines. It allows writing concurrent code in a sequential manner by automatically suspending and resuming coroutines. Useful for I/O-bound tasks and high concurrency scenarios.
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python asyncio concurrency coroutines iobound

asyncoro: Open-Source Python Library for Asynchronous Programming

asyncoro is an open-source Python library for asynchronous programming using coroutines. It allows writing concurrent code in a sequential manner by automatically suspending and resuming coroutines. Useful for I/O-bound tasks and high concurrency scenarios.

What is Asyncoro?

asyncoro is an open-source Python library that aims to simplify asynchronous programming by enabling a sequential coding style using coroutines. It abstracts away callback-based APIs and event loops, allowing developers to write concurrent code as if it were sequential.

Some key features of asyncoro include:

  • Lightweight coroutines (similar to Python's native async/await) to suspend and resume tasks.
  • High performance from carefully optimized C and Cython components.
  • Integration with networking, subprocesses, threads, timers.
  • Familiar sequential control flow using generators, loops, exceptions.
  • Easy concurrent design patterns like pipelines, worker pools.

asyncoro works by executing a set of coroutines concurrently on top of an event loop. When a coroutine awaits on a future, it yields control allowing other coroutines to run. This makes asyncoro ideal for I/O bound workloads and high concurrency scenarios.

Overall, asyncoro simplifies async programming for Python developers by enabling a sequential coding style. It's useful for building responsive network services, scraping jobs, claiming APIs, and other tasks requiring concurrency and parallelism.

Asyncoro Features

Features

  1. Coroutine-based asynchronous programming
  2. Automatic suspending and resuming of coroutines
  3. AsyncIO compatibility layer
  4. Async generators and context managers
  5. Synchronization primitives like Locks, Events, Semaphores
  6. Asynchronous networking and subprocesses
  7. Async-native threading and multiprocessing

Pricing

  • Open Source

Pros

Simplifies asynchronous code

Makes concurrent code look sequential

High performance for I/O-bound tasks

Better utilization of system resources

Cons

Steeper learning curve than threads/multiprocessing

Not ideal for CPU-bound tasks

Limited debugger support

Requires Python 3.5 or later


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