今天介绍一下如何在django项目中使用celery搭建一个有两个节点的任务队列(一个主节点一个子节点;主节点发布任务,子节点收到任务并执行。搭建3个或者以上的节点就类似了),使用到了celery,rabbitmq。这里不会单独介绍celery和rabbitmq中的知识了。
1.项目基础环境:
两个ubuntu18.04虚拟机、python3.6.5、django2.0.4、celery3.1.26post2
2.主节点django项目结构:
3.settings.py中关于celery的配置:
import djcelery
# 此处的Queue和Exchange都涉及到RabbitMQ中的概念,这里不做介绍
from kombu import Queue, Exchange
djcelery.setup_loader()
BROKER_URL = 'amqp://test:test@192.168.43.6:5672/testhost'
CELERY_RESULT_BACKEND = 'amqp://test:test@192.168.43.6:5672/testhost'
CELERY_TASK_RESULT_EXPIRES=3600
CELERY_TASK_SERIALIZER='json'
CELERY_RESULT_SERIALIZER='json'
# CELERY_ACCEPT_CONTENT = ['json', 'pickle', 'msgpack', 'yaml']
CELERY_DEFAULT_EXCHANGE = 'train'
CELERY_DEFAULT_EXCHANGE_TYPE = 'direct'
CELERY_IMPORTS = ("proj.celery1.tasks", )
CELERY_QUEUES = (
Queue('train', routing_key='train'),
Queue('predict', routing_key='predict'),
)
4.celery.py中的配置:
# coding:utf8
from __future__ import absolute_import
import os
from celery import Celery
from django.conf import settings
# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')
app = Celery('proj')
# Using a string here means the worker will not have to
# pickle the object when using Windows.
app.config_from_object('django.conf:settings')
# app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)
app.autodiscover_tasks(settings.INSTALLED_APPS)
@app.task(bind=True)
def debug_task(self):
print('Request: {0!r}'.format(self.request))
5.proj/init.py中的配置:
from __future__ import absolute_import
from .celery import app as celery_app
6.celery1/tasks.py:(主节点中的任务不会执行,只执行子节点中的任务)
from __future__ import absolute_import
from celery import task
@task
def do_train(x, y):
return x + y
7.celery1/views.py:
from .tasks import do_train
class Test1View(APIView):
def get(self, request):
try:
# 这里的queue和routing_key也涉及到RabiitMQ中的知识
# 关键,在这里控制向哪个queue中发送任务,子节点通过这个执行对应queue中的任务
ret = do_train.apply_async(args=[4, 2], queue="train", routing_key="train")
# 获取结果
data = ret.get()
except Exception as e:
return Response(dict(msg=str(e), code=10001))
return Response(dict(msg="OK", code=10000, data=data))
8.子节点目录结构:
9.子节点中celery1/celery.py:
from __future__ import absolute_import
from celery import Celery
CELERY_IMPORTS = ("celery1.tasks", )
app = Celery('myapp',
# 此处涉及到RabbitMQ的知识,RabbitMQ是对应主节点上的
broker='amqp://test:test@192.168.43.6:5672/testhost',
backend='amqp://test:test@192.168.43.6:5672/testhost',
include=['celery1.tasks'])
app.config_from_object('celery1.config')
if __name__ == '__main__':
app.start()
10.子节点中celery1/config.py:
from __future__ import absolute_import
from kombu import Queue,Exchange
from datetime import timedelta
CELERY_TASK_RESULT_EXPIRES=3600
CELERY_TASK_SERIALIZER='json'
CELERY_RESULT_SERIALIZER='json'
CELERY_ACCEPT_CONTENT = ['json','pickle','msgpack','yaml']
CELERY_DEFAULT_EXCHANGE = 'train'
# exchange type可以看RabbitMQ中的相关内容
CELERY_DEFAULT_EXCHANGE_TYPE = 'direct'
CELERT_QUEUES = (
Queue('train',exchange='train',routing_key='train'),
)
11.子节点celery1/tasks.py:(这个是要真正执行的task,每个节点可以不同)
from __future__ import absolute_import
from celery1.celery import app
import time
from celery import task
@task
def do_train(x, y):
"""
训练
:param data:
:return:
"""
time.sleep(3)
return dict(data=str(x+y),msg="train")
12.启动子节点中的celery:
celery1是项目,-Q train表示从train这个queue中接收任务
celery -A celery1 worker -l info -Q train
13.启动主节点中的django项目:
python manage.py runserver
14.使用Postman请求对应的view
请求url:http://127.0.0.1:8000/api/v1/celery1/test/
返回的结果是:
{
"msg": "OK",
"code": 10000,
"data": {
"data": "6",
"msg": "train"
}
}
15.遇到的问题:
1)celery队列报错: AttributeError: ‘str’ object has no attribute ‘items’
解决:将redis库从3.0回退到了2.10,pip install redis==2.10
解决方法参考链接:https://stackoverflow.com/que...
今天就说到这里,如有疑问,欢迎交流。
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