芹菜 - 每个任务/流程只有一个实例?

时间:2015-02-04 06:18:36

标签: python celery celery-task celerybeat

在芹菜文档中,实例化(http://celery.readthedocs.org/en/latest/userguide/tasks.html#custom-task-classes)部分说明如下:

  

没有为每个请求实例化任务,但是在任务注册表中将任务注册为全局实例。

     

这意味着每个进程只会调用一次init构造函数,并且任务类在语义上更接近于Actor。

然而,当我运行以下示例时,我看到 init 方法被调用至少3次。设置有什么问题? CELERYD_CONCURRENCY = 1应该确保每个工作只有一个进程,对吧?

$ celery -A proj beat

celery beat v3.1.17 (Cipater) is starting.
init Task1
40878160
x=1.0
init Task1
40878352
x=1.0
init Task1
40879312
x=1.0
__    -    ... __   -        _
Configuration ->
    . broker -> amqp://guest:**@localhost:5672//
    . loader -> celery.loaders.app.AppLoader
    . scheduler -> celery.beat.PersistentScheduler
    . db -> celerybeat-schedule
    . logfile -> [stderr]@%INFO
    . maxinterval -> now (0s)
[2015-02-05 23:05:21,875: INFO/MainProcess] beat: Starting...
[2015-02-05 23:05:21,971: INFO/MainProcess] Scheduler: Sending due task    task1-every-5-seconds (proj.tasks.t1)
[2015-02-05 23:05:26,972: INFO/MainProcess] Scheduler: Sending due task task1-every-5-seconds (proj.tasks.t1)

celery.py:

from __future__ import absolute_import
from datetime import timedelta
from celery import Celery

app = Celery('proj',
             broker='amqp://guest@localhost//',
             backend='amqp://',
             include=['proj.tasks'])
app.conf.update(
    CELERY_REDIRECT_STDOUTS=True,
    CELERY_TASK_RESULT_EXPIRES=60,
    CELERYD_CONCURRENCY = 1,
    CELERYBEAT_SCHEDULE = {
        'task1-every-5-seconds': {
            'task': 'proj.tasks.t1',
            'schedule': timedelta(seconds=5)
            },
        },
    CELERY_TIMEZONE = 'GMT',
)

if __name__ == '__main__':
    app.start()

tasks.py:

from __future__ import absolute_import
from proj.celery import app
from celery import Task
import time

class Foo():
    def __init__(self, x):
        self.x = x

class Task1(Task):
    abstract = True
    def __init__(self):
        print "init Task1"
        print id(self)
        self.f = Foo(1.0)
        print "x=1.0"

@app.task(base=Task1)
def t1():
    t1.f.x +=1
    print t1.f.x

1 个答案:

答案 0 :(得分:0)

因此,根据您的评论,您需要为每个线程维护一个连接。

为什么不使用线程存储呢?在您的情况下, 应该是一个安全的解决方案。

from threading import local

thread_storage = local()

def get_or_create_conntection(*args, **kwargs):
    if not hasattr(thread_storage, 'connection'):
        thread_storage.connection = Connection(*args, **kwargs)
    return thread_storage.connection

@app.task()
def do_stuff():
    connection = get_or_create_connection('some', connection='args')
    connection.ping()