120 lines
3.0 KiB
Python
120 lines
3.0 KiB
Python
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"""
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Demonstration of the prime number detector example from the
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``concurrent.futures`` docs:
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https://docs.python.org/3/library/concurrent.futures.html#processpoolexecutor-example
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This uses no extra threads or fancy semaphores besides ``tractor``'s
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(TCP) channels.
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"""
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from contextlib import asynccontextmanager
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from typing import List, Callable
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import itertools
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import math
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import time
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import tractor
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import trio
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PRIMES = [
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112272535095293,
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112582705942171,
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112272535095293,
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115280095190773,
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115797848077099,
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1099726899285419]
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def is_prime(n):
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if n < 2:
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return False
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if n == 2:
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return True
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if n % 2 == 0:
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return False
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sqrt_n = int(math.floor(math.sqrt(n)))
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for i in range(3, sqrt_n + 1, 2):
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if n % i == 0:
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return False
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return True
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@asynccontextmanager
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async def worker_pool(workers=4):
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"""Though it's a trivial special case for ``tractor``, the well
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known "worker pool" seems to be the defacto "I want this process
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pattern" for most parallelism pilgrims.
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"""
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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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for i in range(workers):
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# this starts a new sub-actor (process + trio runtime) and
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# stores it's "portal" for later use to "submit jobs" (ugh).
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portals.append(
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await tn.start_actor(
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f'worker_{i}',
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rpc_module_paths=[__name__],
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)
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)
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async def map(
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worker_func: Callable[[int], bool],
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sequence: List[int]
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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 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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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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yield map
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# tear down all "workers"
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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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print(f'{number} is prime: {prime}')
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print(f'processing took {time.time() - start} seconds')
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if __name__ == '__main__':
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start = time.time()
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tractor.run(
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main,
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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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)
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print(f'script took {time.time() - start} seconds')
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