celery

Why does celery needs a message broker?

由 瘦欲@ 提交于 2020-12-01 09:38:09
问题 As celery is a job queue/task queue, name illustrates that it can maintain its tasks and process them. Then why does it needs a message broker like rabbitmq or redis? 回答1: Celery is a Distributed Task Queue that means that the system can reside across multiple computers across multiple locations the basic architecture is as follows: workers - processes that can take jobs from the bus (task queue) and process the data, it can put the result in the bus for farther processing by a different

What is the meaning of bind = True keyword in celery?

由 牧云@^-^@ 提交于 2020-11-30 06:16:06
问题 What is the meaning of bind=True in below celery code? When to use it and when not? @app.task(bind=True) def send_twitter_status(self, oauth, tweet): try: twitter = Twitter(oauth) twitter.update_status(tweet) except (Twitter.FailWhaleError, Twitter.LoginError) as exc: raise self.retry(exc=exc) 回答1: Just a small addition to other answers. As already stated, bound tasks have access to the task instance. One use case when this is needed are retries: @celery.task(bind=True, max_retries=5) def

AirFlow-Install

由 a 夏天 提交于 2020-11-29 14:24:37
AirFlow-Installation https://airflow.incubator.apache.org/installation.html Getting Airflow The easiest way to install the latest stable version of Airflow is with pip : pip install apache-airflow You can also install Airflow with support for extra features like s3 or postgres : pip install "apache-airflow[s3, postgres]" Extra Packages The apache-airflow PyPI basic package only installs what’s needed to get started. Subpackages can be installed depending on what will be useful in your environment. For instance, if you don’t need connectivity with Postgres, you won’t have to go through the

airflow

由 馋奶兔 提交于 2020-11-29 11:49:54
教程： https://airflow.apache.org/docs/stable/index.html 官网： http://airflow.incubator.apache.org/index.html airflow源码：https://github.com/apache/incubator-airflow 参考资料：http://www.open-open.com/lib/view/open1452002876105.html 简介：http://www.cnblogs.com/xianzhedeyu/p/8047828.html 重要参数介绍：http://www.cnblogs.com/skyrim/p/7456166.html http://blog.csdn.net/permike/article/details/52184621 FAQ :http://blog.csdn.net/yingkongshi99/article/details/52658660 容器：docker pull puckel/docker-airflow 启动dag调度器, 注意启动调度器, 并不意味着dag会被马上触发, dag触发需要符合它自己的schedule规则 如果缺省了END_DATE参数, END_DATE等同于START_DATE . 使用 DummyOperator

python用Django+Celery+Redis 监视程序(一)

由 淺唱寂寞╮ 提交于 2020-11-26 03:50:44
C盘创建一个目录就叫DjangoDemo，然后开始在该目录下操作。 1.新建Django工程与应用 运行pip install django 安装django 这里我们建一个名为 demo 的项目和 home 应用。 django-admin startproject demo 创建 demo 项目 然后进入demo文件夹运行命令，manage.py startapp home 创建home应用。 2.编辑 settings.py 文件 在demo文件夹下的settings.py文件的最后添加如下代码： ###配置Broker BROKER_URL = 'redis://127.0.0.1:6379/0' BROKER_TRANSPORT = 'redis' 3.新建 celery.py 文件 在demo文件夹下创建 celery.py 文件，文件内容如下: from __future__ import absolute_import import os import django from celery import Celery from django.conf import settings # os.environ.setdefault(“DJANGO_SETTINGS_MODULE”, “djtest.settings”) # # 设置默认的配置文件的环境变量DJANGO
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