上传日期:2024-04-02 13:15:05
上 传 者sh-1993
说明:  协同程序函数池。
(A pool of coroutine functions.)


# asyncio-pool-ng [![PyPI version](]( [![Python Versions](]( [![License: MIT](]( [![](]( [![Code style: black](]( ## 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`. 1. `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. 2. `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 `AsyncioPool` closes, it will wait for all tasks to complete. All pending futures will be complete once it is closed. 3. `itermap`: Works similarly to `map` but returns an [Async Generator]( "Async Generator") which yields each future as it completes. ## Differences from asyncio-pool 1. `asyncio-pool-ng` implements [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. 2. `asyncio-pool` uses callbacks to process data before returning it; `asyncio-pool-ng` only returns [Future]( instances directly. The future will contain either a result or an exception which can then be handled as needed. 3. While `asyncio-pool` schedules [Coroutine]( instances directly, `asyncio-pool-ng` takes the callable and arguments, and creates the Coroutine instance at execution time. ## Example ```python title="" 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"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]] =, range(10)) await asyncio.wait(futures) results = [x.result() for x in futures]"results for, range(10)): {results}") results.sort() assert results == [0, 2, 4, 6, 8, 10, 12, 14, 16, 18] """iterate futures as they complete""""results for pool.itermap(worker, range(10)):") results = [] async for future in pool.itermap(worker, range(10)): results.append(future.result())"> {future.result()}") results.sort() assert results == [0, 2, 4, 6, 8, 10, 12, 14, 16, 18] ```