Python 乌维康+；Gunicorn&x2B；Starlette上菜时卡住了，可以'；t在没有sigkill的情况下重新启动服务

我通过gunicorn+uvicorn在虚拟机上为一个模型提供服务

它由supervisord自动启动，运行

api.sh

api.sh

包含：

source /home/asd/.virtual_envs/myproject/bin/activate

/home/asd/.virtual_envs/myproject/bin/gunicorn --max-requests-jitter 30 -w 6 -b 0.0.0.0:4080 api:app -k uvicorn.workers.UvicornWorker

在不深入了解api.py的情况下，它包含以下主要部分：

from starlette.applications import Starlette
from models import SomeModelClass


app = Starlette(debug=False)
model = SomeModelClass()


@app.route('/do_things', methods=['GET', 'POST', 'HEAD'])
async def add_styles(request):
    if request.method == 'GET':
        params = request.query_params
    elif request.method == 'POST':
        params = await request.json()
    elif request.method == 'HEAD':
        return UJSONResponse([])

    # Doing things
    result = model(params)
    return UJSONResponse(result)

发生的情况是，api运行几天后，我开始出现以下错误：

[INFO] Starting gunicorn 20.0.3
[ERROR] Connection in use: ('0.0.0.0', 4080)
[ERROR] Retrying in 1 second.
[ERROR] Connection in use: ('0.0.0.0', 4080)
[ERROR] Retrying in 1 second.
[ERROR] Connection in use: ('0.0.0.0', 4080)
[ERROR] Retrying in 1 second.
[ERROR] Connection in use: ('0.0.0.0', 4080)
[ERROR] Retrying in 1 second.
...

在supervisord中重新启动api没有任何作用，我得到了与上面相同的消息。我发现有效的唯一方法是：

在supervisord中停止api

查看4080端口上运行的pid（一个

python3.8

进程）：

sudo netstat-tulpn|grep LISTEN

停止运行

Kill-9[PID]

重复步骤2-3 1-2次，直到4080端口无任何占用

在supervisord中启动api

---

您对如何解决这个问题有什么想法吗？

实际使用的代码是

多处理中的
池
，这很可能是导致此问题的原因

例如：

from starlette.applications import Starlette
from models import SomeModelClass
from multiprocessing import Pool
from utils import myfun


app = Starlette(debug=False)
model = SomeModelClass()


@app.route('/do_things', methods=['GET', 'POST', 'HEAD'])
async def add_styles(request):
    if request.method == 'GET':
        params = request.query_params
    elif request.method == 'POST':
        params = await request.json()
    elif request.method == 'HEAD':
        return UJSONResponse([])

    # Doing things
    result = model(params)
    # Start of the offending code
    pool = Pool(4)
    result = pool.map(myfun, result, chunksize=1)
    # End of the offending code
    return UJSONResponse(result)

解决方案是用并发性取代多处理：

from starlette.applications import Starlette
from models import SomeModelClass
import concurrent.futures
from utils import myfun


app = Starlette(debug=False)
model = SomeModelClass()


@app.route('/do_things', methods=['GET', 'POST', 'HEAD'])
async def add_styles(request):
    if request.method == 'GET':
        params = request.query_params
    elif request.method == 'POST':
        params = await request.json()
    elif request.method == 'HEAD':
        return UJSONResponse([])

    # Doing things
    result = model(params)
    # Start of the fix
    with concurrent.futures.ThreadPoolExecutor(max_workers=4) as executor:
        result = executor.map(myfun, result)
    result = list(result)
    # End of the fix
    return UJSONResponse(result)