为啥在 python 中对 asyncio 服务器的多个请求的时间会增加？

Posted 2023-03-30

技术标签:

【中文标题】为啥在 python 中对 asyncio 服务器的多个请求的时间会增加？【英文标题】：why is time rising for more than one request to asyncio server in python?为什么在 python 中对 asyncio 服务器的多个请求的时间会增加？ 【发布时间】：2018-07-04 12:51:19 【问题描述】：

我用套接字编写了一个 pythonic 服务器。它应该同时（并行）接收请求并并行响应它们。当我向它发送多个请求时，回复的时间比我预期的要长。

服务器：

import datetime
import asyncio, timeit
import json, traceback
from asyncio import get_event_loop

requestslist = []
loop = asyncio.get_event_loop()

async def handleData(reader, writer):
    message = ''
    clientip = ''
    data = bytearray()
    print("Async HandleData", datetime.datetime.utcnow())


    try:
        start = timeit.default_timer()
        data = await reader.readuntil(separator=b'\r\n\r\n')
        msg = data.decode(encoding='utf-8')
        len_csharp_message = int(msg[msg.find('content-length:') + 15:msg.find(';dmnid'):])
        data = await reader.read(len_csharp_message)
        message = data.decode(encoding='utf-8')

        clientip = reader._transport._extra['peername'][0]
        clientport = reader._transport._extra['peername'][1]
        print('\nData Received from:', clientip, ':', clientport)
        if (clientip, message) in requestslist:
            reader._transport._sock.close()

        else:
            requestslist.append((clientip, message))

            # adapter_result = parallel_members(message_dict, service, dmnid)
            adapter_result = '''["name": "data": "data", "type": "str"]'''
            body = json.dumps(adapter_result, ensure_ascii=False)
            print(body)

            contentlen = len(bytes(str(body), 'utf-8'))
            header = bytes('Content-Length:'.format(contentlen), 'utf-8')
            result = header + bytes('\r\n\r\n', 'utf-8') + body + bytes('', 'utf-8')
            stop = timeit.default_timer()
            print('total_time:', stop - start)
            writer.write(result)
            writer.close()
        writer.close()
        # del writer
    except Exception as ex:
        writer.close()
        print(traceback.format_exc())
    finally:
        try:
            requestslist.remove((clientip, message))
        except:
            pass


def main(*args):
    print("ready")
    loop = get_event_loop()
    coro = asyncio.start_server(handleData, 'localhost', 4040, loop=loop, limit=204800000)
    srv = loop.run_until_complete(coro)
    loop.run_forever()


if __name__ == '__main__':
    main()

当我发送单个请求时，需要 0.016 秒。但是对于更多的请求，这次增加。

cpu 信息：intel xeon x5650

客户：

import multiprocessing, subprocess
import time
from joblib import Parallel, delayed


def worker(file):
    subprocess.Popen(file, shell=False)


def call_parallel (index):
    print('begin ' , index)
    p = multiprocessing.Process(target=worker(index))
    p.start()
    print('end ' , index)

path = r'python "/test-Client.py"'     # ## client address
files = [path, path, path, path, path, path, path, path, path, path, path, path]
Parallel(n_jobs=-1, backend="threading")(delayed(call_parallel)(i) for index,i  in  enumerate(files))

对于这个同步发送 12 个请求的客户端，每个请求的总时间为 0.15 秒。

我希望任何数量的请求，时间都是固定的。

【问题讨论】：

【参考方案1】：