asyncoro is a Python framework for asynchronous, concurrent, distributed programming using coroutines, asynchronous completions and message passing. Programs developed with asyncoro have same logic and structure as programs with threads, except for a few syntactic changes - mostly using yield with asynchronous completions that give control to asyncoro’s scheduler, which interleaves executions of coroutines, similar to the way an operating system executes multiple processes.

Unlike threads, creating processes (coroutines) with asyncoro is very efficient. Moreover, with asyncoro context switch occurs only when coroutines use yield (typically with an asychronous call), so there is no need for locking and there is no overhead of unnecessary context switches.

asyncoro features include:

  • No callbacks or event loops! No need to lock critical sections either,
  • Efficient polling mechanisms epoll, kqueue, /dev/poll, Windows I/O Completion Ports (IOCP) for high performance and scalability,
  • Asynchronous (non-blocking) sockets and pipes, for concurrent processing of I/O,
  • SSL for security,
  • Asynchronous timers, including non-blocking sleep,
  • Asynchronous locking primitives similar to Python threading module,
  • Message passing for (local and remote) coroutines to exchange messages one-to-one with Message Queue Pattern or through broadcasting channels with Publish-Subscribe Pattern,
  • Location transparency with naming and locating resources,
  • Remote execution of coroutines for distributed/parallel programming with Remote Coroutine Invocation RCI and message passing,
  • Monitoring and restarting of (local or remote) coroutines, for fault detection and fault-tolerance,
  • Hot-swapping of coroutine functions, for dynamic system reconfiguration,
  • Distributing computation fragments for remote execution of coroutines with Distributed / Parallel Computing,
  • Thread pools with asynchronous task completions, for executing time consuming synchronous tasks,

For reference purposes, asyncoro with Python 2.7 on Ubuntu Linux 12.04 running the concurrent program:

import asyncoro, resource, time
def coro_proc(coro=None):
    yield coro.suspend()

coros = [asyncoro.Coro(coro_proc) for i in xrange(100000)]
ru = resource.getrusage(resource.RUSAGE_SELF)
print('Max RSS: %.1f MB' % (ru.ru_maxrss / 1024.0))
for coro in coros:

shows that 100,000 coroutines take about 200 MB of resident memory (RSS field).

asyncoro has been tested with Linux, Mac OS X and Windows. asyncoro is implemented with standard modules in Python. Under Windows efficient polling notifier I/O Completion Ports is supported only if pywin32 is installed; otherwise, inefficient ‘select’ notifier is used.


asyncoro package is available in Python Package Index (PyPI) so it can be installed for Python 2.7+ with:

pip install asyncoro

and/or for Python 3.1+ with:

pip3 install asyncoro

asyncoro can also be downloaded from Sourceforge Files.


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