Question: I would like to read from multiple simultanous HTTP streaming requests inside coroutines using httpx, and yield the data back to my non-async function running the event loop, rather than just returning the final data. But if I make my async functions yield instead of return, I get complaints that asyncio.as_completed() and loop.run_until_complete() expects a coroutine or a Future, not an async generator. So the only way I can get this to work at all is by collecting all the streamed data inside each coroutine, returning all data once the request finishes. Then collect all the coroutine results and finally returning that to the non-async calling function. Which means I have to keep everything in memory, and wait until the slowest request has completed before I get all my data, which defeats the whole point of streaming http requests. Is there any way I can accomplish something like this? My current silly implementation looks like this: def collect_data(urls): """Non-async function wishing it was a non-async generator""" async def stream(async_client, url, payload): data = [] async with async_client.stream("GET", url=url) as ar: ar.raise_for_status() async for line in ar.aiter_lines(): data.append(line) # would like to yield each line here return data async def execute_tasks(urls): all_data = [] async with httpx.AsyncClient() as async_client: tasks = [stream(async_client, url) for url in urls] for coroutine in asyncio.as_completed(tasks): all_data += await coroutine # would like to iterate and yield each line here return all_events try: loop = asyncio.get_event_loop() data = loop.run_until_complete(execute_tasks(urls=urls)) return data # would like to iterate and yield the data here as it becomes available finally: loop.close()  I've tried some solutions using asyncio.Queue and trio memory channels as well, but since I can only read from those in an async scope it doesn't get me any closer to a solution. The reason I want to use this from a non-asyncronous generator is that I want to use it from a Django app using a Django Rest Framework streaming API.

Answer: Normally you should just make collect_data async, and use async code throughout - that's how asyncio was designed to be used. But if that's for some reason not feasible, you can iterate an async iterator manually by applying some glue code: def iter_over_async(ait, loop): ait = ait.__aiter__() # helper async fn that just gets the next element # from the async iterator async def get_next(): try: obj = await ait.__anext__() return False, obj except StopAsyncIteration: return True, None # actual sync iterator (implemented using a generator) while True: done, obj = loop.run_until_complete(get_next()) if done: break yield obj  The way the above works is by providing an async closure that keeps retrieving the values from the async iterator using the __anext__ magic method and returning the objects as they arrive. This async closure is invoked with run_until_complete() in a loop inside an ordinary sync generator. (The closure actually returns a pair of done indicator and actual object in order to avoid propagating StopAsyncIteration through run_until_complete, which might be unsupported.) With this in place, you can make your execute_tasks an async generator (async def with yield) and iterate over it using: for chunk in iter_over_async(execute_tasks(urls), loop): ...  Just note that this approach is incompatible with asyncio.run, and assumes the event loop can only be run "occasionally". This might cause issues in more complex async code which might want to set up some background tasks - but for simple code it should be fine.