Python asyncio缓冲区和流程数据

Question

我在asyncio事件循环中遇到了一些CPU密集型任务的问题.我在处理维护传入数据缓冲区和从中构建数据包时遇到的麻烦.我已经尝试使用执行程序来执行CPU绑定的东西,但是当从中删除数据包时,无法维护缓冲区的顺序.

我正在寻找一种最佳实践方法来实现以下功能,而无需在事件循环中执行CPU绑定任务.

import asyncio
import struct

class Reader(asyncio.Protocol):
    def __init__(self):
        self.extra = bytearray()

    def data_received(self, data):
        self.extra.extend(data)
        packet = get_packet(bytes(self.extra))
        if packet:
            del self.extra[:len(packet)]
            if verify_hash(packet):  # CPU intensive
                asyncio.async(distribute(packet))  # Some asyncio fan-out callback


def get_packet(data):  # CPU intensive
    if len(data) > HEADER_SIZE:
        payload_size, = struct.unpack_from(HEADER_FORMAT, data)
        if len(data) >= HEADER_SIZE + payload_size:
            return data[:HEADER_SIZE + payload_size]
    return None

loop = asyncio.get_event_loop()
loop.run_until_complete(loop.create_server(Reader, '0.0.0.0', 8000))
loop.run_forever()

Answer 1

您希望能够尽快处理所有数据Reader,但您也不能让多个线程/进程尝试并行处理该数据; 这就是你之前使用执行程序遇到竞争条件的方式.相反,您应该启动一个可以处理所有数据包数据的工作进程,一次一个,使用a multiprocessing.Queue将数据从父进程传递给worker.然后,当worker具有构建,验证并准备分发的有效数据包时,它使用另一个multiprocessing.Queue将其发送回父进程中的线程,该进程可以使用线程安全call_soon_threadsafe方法来安排distribute运行.

这是一个未经测试的示例,可以让您了解如何执行此操作:

import asyncio
import struct
from concurrent.futures.ProcessPoolExecutor
import threading


def handle_result_packets():
    """ A function for handling packets to be distributed.

    This function runs in a worker thread in the main process.

    """
    while True:
        packet = result_queue.get()
        loop.call_soon_threadsafe(asyncio.async, distribute(packet))

def get_packet():  # CPU intensive
    """ Handles processing all incoming packet data.

    This function runs in a separate process.

    """
    extra = bytearray()
    while True:
        data = data_queue.get()
        extra.extend(data)
        if len(data) > HEADER_SIZE:
            payload_size, = struct.unpack_from(HEADER_FORMAT, data)
            if len(data) >= HEADER_SIZE + payload_size:
                packet = data[:HEADER_SIZE + payload_size]
                del extra[:len(packet)]
                if verify_hash(packet):
                    result_queue.put(packet)


class Reader(asyncio.Protocol):
    def __init__(self):
        self.extra = bytearray()
        self.t = threading.Thread(target=handle_result_packets)
        self.t.start()

    def data_received(self, data):
        data_queue.put(data)


if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    data_queue = multiprocessing.Queue()
    result_queue = multiprocessing.Queue()
    p = multiprocessing.Process(target=get_packet)
    p.start()
    loop.run_until_complete(loop.create_server(Reader, '0.0.0.0', 8000))
    loop.run_forever()