forked from goodboy/tractor
Yield results on demand using a mem chan
parent
3c320f467f
commit
9b07e9ad7c
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@ -24,7 +24,8 @@ PRIMES = [
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112272535095293,
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115280095190773,
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115797848077099,
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1099726899285419]
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1099726899285419,
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]
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def is_prime(n):
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@ -50,17 +51,10 @@ async def worker_pool(workers=4):
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"""
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async with tractor.open_nursery(
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loglevel='ERROR',
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# uncomment to use ``multiprocessing`` fork server backend
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# which gives a startup time boost at the expense of nested
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# processs scalability
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# start_method='forkserver')
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) as tn:
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async with tractor.open_nursery() as tn:
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portals = []
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results = []
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snd_chan, recv_chan = trio.open_memory_channel(len(PRIMES))
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for i in range(workers):
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@ -79,35 +73,37 @@ async def worker_pool(workers=4):
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) -> List[bool]:
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# define an async (local) task to collect results from workers
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async def collect_portal_result(func, value, portal):
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results.append((value, await portal.run(func, n=value)))
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async def send_result(func, value, portal):
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await snd_chan.send((value, await portal.run(func, n=value)))
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async with trio.open_nursery() as n:
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for value, portal in zip(sequence, itertools.cycle(portals)):
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n.start_soon(
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collect_portal_result,
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send_result,
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worker_func,
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value,
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portal
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)
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return results
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# deliver results as they arrive
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for _ in range(len(sequence)):
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yield await recv_chan.receive()
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yield map
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# tear down all "workers"
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# tear down all "workers" on pool close
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await tn.cancel()
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async def main():
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async with worker_pool() as actor_map:
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start = time.time()
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# for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):
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for number, prime in await actor_map(is_prime, PRIMES):
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async for number, prime in actor_map(is_prime, PRIMES):
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print(f'{number} is prime: {prime}')
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print(f'processing took {time.time() - start} seconds')
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