unsync

Unsynchronize asyncio by using an ambient event loop in a separate thread.

Rules for unsync

1. Mark all async functions with @unsync. May also mark regular functions to execute in a separate thread.
   • All @unsync functions, async or not, return an Unfuture
2. All Futures must be Unfutures which includes the result of an @unsync function call, or wrapping Unfuture(asyncio.Future) or Unfuture(concurrent.Future). Unfuture combines the behavior of asyncio.Future and concurrent.Future:
   • Unfuture.set_value is threadsafe unlike asyncio.Future
   • Unfuture instances can be awaited, even if made from concurrent.Future
   • Unfuture.result() is a blocking operation except in unsync.loop/unsync.thread where it behaves like asyncio.Future.result and will throw an exception if the future is not done
3. Functions will execute in different contexts:
   • @unsync async functions will execute in an event loop in unsync.thread
   • @unsync regular functions will execute in unsync.thread_executor, a ThreadPoolExecutor
   • @unsync(cpu_bound=True) regular functions will execute in unsync.process_executor, a ProcessPoolExecutor

Examples

Simple Sleep

A simple sleeping example with asyncio:

async def sync_async():
    await asyncio.sleep(0.1)
    return 'I hate event loops'

annoying_event_loop = asyncio.get_event_loop()
future = asyncio.ensure_future(sync_async(), loop=annoying_event_loop)
annoying_event_loop.run_until_complete(future)
print(future.result())

Same example with unsync:

@unsync
async def unsync_async():
    await asyncio.sleep(0.1)
    return 'I like decorators'

print(unsync_async().result())

Threading a synchronous function

Synchronous functions can be made to run asynchronously by executing them in a concurrent.ThreadPoolExecutor. This can be easily accomplished by marking the regular function @unsync.

@unsync
def non_async_function(seconds):
    time.sleep(seconds)
    return 'Run in parallel!'

start = time.time()
tasks = [non_async_function(0.1) for _ in range(10)]
print([task.result() for task in tasks])
print('Executed in {} seconds'.format(time.time() - start))

Which prints:

['Run in parallel!', 'Run in parallel!', ...]
Executed in 0.10807514190673828 seconds

Continuations

Using Unfuture.then chains asynchronous calls and returns an Unfuture that wraps both the source, and continuation. The continuation is invoked with the source Unfuture as the first argument. Continuations can be regular functions (which will execute synchronously), or @unsync functions.

@unsync
async def initiate(request):
    await asyncio.sleep(0.1)
    return request + 1

@unsync
async def process(task):
    await asyncio.sleep(0.1)
    return task.result() * 2

start = time.time()
print(initiate(3).then(process).result())
print('Executed in {} seconds'.format(time.time() - start))

Which prints:

8
Executed in 0.20314741134643555 seconds

Mixing methods

We'll start by converting a regular synchronous function into a threaded Unfuture which will begin our request.

@unsync
def non_async_function(num):
    time.sleep(0.1)
    return num, num + 1

We may want to refine the result in another function, so we define the following continuation.

@unsync
async def result_continuation(task):
    await asyncio.sleep(0.1)
    num, res = task.result()
    return num, res * 2

We then aggregate all the results into a single dictionary in an async function.

@unsync
async def result_processor(tasks):
    output = {}
    for task in tasks:
        num, res = await task
        output[num] = res
    return output

Executing the full chain of non_async_function→result_continuation→result_processor would look like:

start = time.time()
print(result_processor([non_async_function(i).then(result_continuation) for i in range(10)]).result())
print('Executed in {} seconds'.format(time.time() - start))

Which prints:

{0: 2, 1: 4, 2: 6, 3: 8, 4: 10, 5: 12, 6: 14, 7: 16, 8: 18, 9: 20}
Executed in 0.22115683555603027 seconds