asyncoro is a Python framework for asynchronous, concurrent, distributed programming using generator functions, asynchronous completions and message passing. asyncoro API can be used to create coroutines with generator functions, similar to the way threads are created with functions with Python’s threading module. Thus, 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 generators, 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:
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)] time.sleep(5) ru = resource.getrusage(resource.RUSAGE_SELF) print('Max RSS: %.1f MB' % (ru.ru_maxrss / 1024.0)) for coro in coros: coro.resume()
shows that 100,000 coroutines take about 200 MB of resident memory (RSS field).
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 works with Python 2.7+ and Python 3.1+ and tested on Linux, Mac OS X and Windows; it may work on other platforms too. asyncoro works with PyPy as well.
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.