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I have a simple aiohttp-server with two handlers. First one does some computations in the async for loop. Second one just returns text response. not_so_long_operation returns 30-th fibonacci number with the slowest recursive implementation, which takes something about one second.

def not_so_long_operation(): return fib(30) class arange: def __init__(self, n): self.n = n self.i = 0 async def __aiter__(self): return self async def __anext__(self): i = self.i self.i += 1 if self.i <= self.n: return i else: raise StopAsyncIteration # GET / async def index(request): print('request!') l = [] async for i in arange(20): print(i) l.append(not_so_long_operation()) return aiohttp.web.Response(text='%d\n' % l[0]) # GET /lol/ async def lol(request): print('request!') return aiohttp.web.Response(text='just respond\n')

When I'm trying to fetch / and then /lol/, it gives me response for the second one only when the first one gets finished.
What am I doing wrong and how to make index handler release the ioloop on each iteration?

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3 Answers 3

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Your example has no yield points (await statements) for switching between tasks. Asynchronous iterator allows to use await inside __aiter__/__anext__ but don't insert it automatically into your code.

Say,

class arange: def __init__(self, n): self.n = n self.i = 0 async def __aiter__(self): return self async def __anext__(self): i = self.i self.i += 1 if self.i <= self.n: await asyncio.sleep(0) # insert yield point return i else: raise StopAsyncIteration

should work as you expected.

In real application most likely you don't need await asyncio.sleep(0) calls because you will wait on database access and similar activities.

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2 Comments

So, as far as I understood, according to PEP-492, async for was added to avoid collisions with StopIteration, used in coroutines internally?
Not exactly. async for uses __aiter__/__anext__ pair of coroutines. Let's assume we read bulk of data from DB (like redis iscan command ). It fetches a bulk of data, returns it item by item and fetch next bulk on data exhausting. You may perform I/O in __aiter__ coroutine with help of await statement but cannot do it in old-good __iter__ method.
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Since, fib(30) is CPU bound and sharing little data, you should probably use a ProcessPoolExecutor (as opposed to a ThreadPoolExecutor):

async def index(request): loop = request.app.loop executor = request.app["executor"] result = await loop.run_in_executor(executor, fib, 30) return web.Response(text="%d" % result)

Setup executor when you create the app:

app = Application(...) app["exector"] = ProcessPoolExector()
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fib(30) is just an example of operation, which runs not so long once, but long enough while running in the loop. CPU-bound operation was not the best idea, but thank you for your snippet!
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An asynchronous iterator is not really needed here. Instead you can simply give the control back to the event loop inside your loop. In python 3.4, this is done by using a simple yield:

@asyncio.coroutine def index(self): for i in range(20): not_so_long_operation() yield

In python 3.5, you can define an Empty object that basically does the same thing:

class Empty: def __await__(self): yield

Then use it with the await syntax:

async def index(request): for i in range(20): not_so_long_operation() await Empty()

Or simply use asyncio.sleep(0) that has been recently optimized:

async def index(request): for i in range(20): not_so_long_operation() await asyncio.sleep(0)

You could also run the not_so_long_operation in a thread using the default executor:

async def index(request, loop): for i in range(20): await loop.run_in_executor(None, not_so_long_operation)
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2 Comments

is it necessary to construct Empty object each time? Is it ok to create next_tick = Empty() and then use it with await next_tick?
@MichaelIhnatenko Sure it's fine, though I'm surprised there's no standard way to give the control back to the event loop in python 3.5.

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