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A Python 3.3+ library that integrates the multiprocessing module with asyncio.

Project Description
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`aioprocessing` provides asynchronous, [`asyncio`]( compatible, coroutine
versions of many blocking instance methods on objects in the [`multiprocessing`](
library. Here's an example demonstrating the `aioprocessing` versions of
`Event`, `Queue`, and `Lock`:

import time
import asyncio
import aioprocessing
import multiprocessing

def func(queue, event, lock, items):
""" Demo worker function.

This worker function runs in its own process, and uses
normal blocking calls to aioprocessing objects, exactly
the way you would use oridinary multiprocessing objects.

with lock:
for item in items:

def example(queue, event, lock):
l = [1,2,3,4,5]
p = aioprocessing.AioProcess(target=func, args=(queue, event, lock, l))
while True:
result = yield from queue.coro_get()
if result is None:
print("Got result {}".format(result))
yield from p.coro_join()

def example2(queue, event, lock):
yield from event.coro_wait()
with (yield from lock):
yield from queue.coro_put(78)
yield from queue.coro_put(None) # Shut down the worker

if __name__ == "__main__":
loop = asyncio.get_event_loop()
queue = aioprocessing.AioQueue()
lock = aioprocessing.AioLock()
event = aioprocessing.AioEvent()
tasks = [
asyncio.async(example(queue, event, lock)),
asyncio.async(example2(queue, event, lock)),

Python 3.5 syntax is supported, too. This means the `example2` function above
could look like this:

async def example2(queue, event, lock):
await event.coro_wait()
async with lock:
await queue.coro_put(78)
await queue.coro_put(None) # Shut down the worker

The aioprocessing objects can be used just like their multiprocessing
equivalents - as they are in `func` above - but they can also be
seamlessly used inside of `asyncio` coroutines, without ever blocking
the event loop.

How does it work?

In most cases, this library makes blocking calls to `multiprocessing` methods
asynchronous by executing the call in a [`ThreadPoolExecutor`](, using
It does *not* re-implement multiprocessing using asynchronous I/O. This means
there is extra overhead added when you use `aioprocessing` objects instead of
`multiprocessing` objects, because each one is generally introducing a
`ThreadPoolExecutor` containing at least one [`threading.Thread`]( It also means
that all the normal risks you get when you mix threads with fork apply here, too
(See for more info).

The one exception to this is `aioprocessing.AioPool`, which makes use of the
existing `callback` and `error_callback` keyword arguments in the various
[`Pool.*_async`]( methods to run them as `asyncio` coroutines. Note that
`multiprocessing.Pool` is actually using threads internally, so the thread/fork
mixing caveat still applies.

Each `multiprocessing` class is replaced by an equivalent `aioprocessing` class,
distinguished by the `Aio` prefix. So, `Pool` becomes `AioPool`, etc. All methods
that could block on I/O also have a coroutine version that can be used with `asyncio`. For example, `multiprocessing.Lock.acquire()` can be replaced with `aioprocessing.AioLock.coro_acquire()`. You can pass an `asyncio` EventLoop object to any `coro_*` method using the `loop` keyword argument. For example, `lock.coro_acquire(loop=my_loop)`.

Note that you can also use the `aioprocessing` synchronization primitives as replacements
for their equivalent `threading` primitives, in single-process, multi-threaded programs
that use `asyncio`.

What parts of multiprocessing are supported?

Most of them! All methods that could do blocking I/O in the following objects
have equivalent versions in `aioprocessing` that extend the `multiprocessing`
versions by adding coroutine versions of all the blocking methods.

- `Pool`
- `Process`
- `Pipe`
- `Lock`
- `RLock`
- `Semaphore`
- `BoundedSemaphore`
- `Event`
- `Condition`
- `Barrier`
- `connection.Connection`
- `connection.Listener`
- `connection.Client`
- `Queue`
- `JoinableQueue`
- `SimpleQueue`
- All `managers.SyncManager` `Proxy` versions of the items above (`SyncManager.Queue`, `SyncManager.Lock()`, etc.).

What versions of Python are compatible?

`aioprocessing` will work out of the box on Python 3.4+, and will also work with Python
3.3 if you install the [PyPI version]( of `asyncio`.
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