A managed pool of coroutine functions.
Project description
asyncio-pool-ng
About
AsyncioPoolNG takes the ideas used in asyncio-pool and wraps them around an asyncio.TaskGroup.
AsyncioPool has three main functions spawn, map, and itermap.
spawn: Schedule an async function on the pool and get a future back which will eventually have either the result or the exception from the function.map: Spawn an async function for each item in an iterable object, and return a set containing a future for each item.
asyncio.wait()can be used to wait for the set of futures to complete.- When the
AsyncioPoolcloses, it will wait for all tasks to complete. All pending futures will be complete once it is closed.
itermap: Works similarly tomapbut returns an Async Generator which yields each future as it completes.
Differences from asyncio-pool
asyncio-pool-ngimplements Python typing and passes validation checks with mypy's strict mode. This helps IDEs and static type checkers know what type of result to expect when getting data from a completed future.asyncio-pooluses callbacks to process data before returning it;asyncio-pool-ngonly returns Future instances directly. The future will contain either a result or an exception which can then be handled as needed.- While
asyncio-poolschedules Coroutine instances directly,asyncio-pool-ngtakes the callable and arguments, and creates the Coroutine instance at execution time.
Example
import asyncio
import logging
from random import random
from asyncio_pool import AsyncioPool
logging.basicConfig(level=logging.INFO)
async def worker(number: int) -> int:
await asyncio.sleep(random() / 2)
return number * 2
async def main() -> None:
result: int = 0
results: list[int] = []
async with AsyncioPool(2) as pool:
"""spawn task and wait for the results"""
result = await pool.spawn(worker, 5)
assert result == 10
logging.info(f"results for pool.spawn(worker, 5): {result}")
"""spawn task and get results later"""
future: asyncio.Future[int] = pool.spawn(worker, 5)
# do other stuff
result = await future
assert result == 10
"""map an async function to a set of values"""
futures: set[asyncio.Future[int]] = pool.map(worker, range(10))
await asyncio.wait(futures)
results = [x.result() for x in futures]
logging.info(f"results for pool.map(worker, range(10)): {results}")
results.sort()
assert results == [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
"""iterate futures as they complete"""
logging.info("results for pool.itermap(worker, range(10)):")
results = []
async for future in pool.itermap(worker, range(10)):
results.append(future.result())
logging.info(f"> {future.result()}")
results.sort()
assert results == [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
asyncio.run(main())
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