使用celery和Django处理异步任务的流程分析

介绍

我们可能需要一些可以安排一些任务并定期运行一些任务或异步处理长任务的东西，而这一切都可以通过在Django Project中使用Celery来实现。

什么是Celery？

Celery是 一个专注于实时处理的任务队列，它还支持任务调度。 Celery快速，简单，高度可用且灵活。

Celery需要消息传输来发送和接收消息，这可以由Redis或RabbitMQ完成。

入门

让我们开始在您的virtualenv中安装Celery软件包。

安装Celery

<span class="nv">$ </span>pip <span class="nb">install </span>celery
pip install celery

安装Redis

我们将Message Broker用作Redis，所以我们安装

Linux / Mac用户

您可以从这里下载最新版本

$ wget http://download.redis.io/releases/redis-4.0.8.tar.gz
$ tar xzf redis-4.0.8.tar.gz
$ cd redis-4.0.8
$make

Windows用户

对于Windows用户，您可以从此处获取redis的可执行文件。

安装后，请尝试是否正确安装。

$ redis-cli ping

它应该显示：

pong

同时安装redis的python包

$ pip install redis

Django的第一步

现在您已经成功安装了软件包，现在就开始学习Django Project

settings.py Add some of the setting configuration in your settings.py CELERY_BROKER_URL = 'redis://localhost:6379' CELERY_RESULT_BACKEND = 'redis://localhost:6379' CELERY_ACCEPT_CONTENT = ['application/json'] CELERY_TASK_SERIALIZER = 'json' CELERY_RESULT_SERIALIZER = 'json' CELERY_TIMEZONE = "YOUR_TIMEZONE"

确保您已从YOUR_TIMEZONE更改时区。 您可以从这里获取时区

主Django项目目录中创建celery.py文件

- src/ - manage.py - celery_project/ - __init__.py - settings.py - urls.py - celery.py celery_project/celery.py

在celery.py模块中添加以下代码。 该模块用于定义celery实例。

确保已使用django项目名称更改了项目名称（）

from __future__ import absolute_import, unicode_literals
import os
from celery import Celery
# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', '<your project name>.settings')
app = Celery('<your project name>')
# Using a string here means the worker doesn't have to serialize
# the configuration object to child processes.
# - namespace='CELERY' means all celery-related configuration keys
# should have a `CELERY_` prefix.
app.config_from_object('django.conf:settings', namespace='CELERY')
# Load task modules from all registered Django app configs.
app.autodiscover_tasks()
@app.task(bind=True)
def debug_task(self):
 print('Request: {0!r}'.format(self.request))
celery_project/__init__.py

然后，我们需要将定义celery.py的应用程序导入到主项目目录的__init__.py。 这样，我们可以确保在Django项目启动时已加载应用

from __future__ import absolute_import, unicode_literals
# This will make sure the app is always imported when
# Django starts so that shared_task will use this app.
from .celery import app as celery_app
__all__ = ['celery_app'] 

创建任务

现在创建一些任务

在您在INSTALLED_APPS中注册的任何应用程序中创建一个新文件

my_app/tasks.py
from __future__ import absolute_import, unicode_literals
from celery import shared_task
@shared_task(name = "print_msg_with_name")
def print_message(name, *args, **kwargs):
 print("Celery is working!! {} have implemented it correctly.".format(name))
@shared_task(name = "add_2_numbers")
def add(x, y):
 print("Add function has been called!! with params {}, {}".format(x, y))
 return x+y
 ```

<p><span style="color: #ff0000"><strong>开始程序</strong></span></p>
<p>打开一个NEW终端并运行以下命令以运行celery的worker实例，并将目录更改为您的主项目目录所在的位置，即，将manage.py文件放置的目录，并确保您已经 激活您的virtualenv（如果已创建）。</p>
<p>用您的项目名称更改项目名称</p>
<p><code>$ celery -A <your project name> worker -l info</code></p>
<p>输出：</p>
<blockquote>
<p>-------------- <a rel="external nofollow" href="mailto:celery@root">celery@root</a> v4.1.0 (latentcall) ---- **** ----- --- * *** * -- Linux-4.13.0-32-generic-x86_64-with-Ubuntu-17.10-artful 2018-02-17 08:09:37 -- * - **** --- - ** ---------- [config] - ** ---------- .> app: celery_project:0x7f9039886400 - ** ---------- .> transport: redis://localhost:6379// - ** ---------- .> results: redis://localhost:6379/ - *** --- * --- .> concurrency: 4 (prefork) -- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker) --- ***** ----- -------------- [queues] .> celery exchange=celery(direct) key=celery [tasks] . add_2_numbers . celery_project.celery.debug_task . print_msg_with_name [2018-02-17 08:09:37,877: INFO/MainProcess] Connected to redis://localhost:6379// [2018-02-17 08:09:37,987: INFO/MainProcess] mingle: searching for neighbors [2018-02-17 08:09:39,084: INFO/MainProcess] mingle: all alone [2018-02-17 08:09:39,121: WARNING/MainProcess] /home/jai/Desktop/demo/lib/python3.6/site-packages/celery/fixups/django.py:202: UserWarning: Using settings.DEBUG leads to a memory leak, never use this setting in production environments! warnings.warn('Using settings.DEBUG leads to a memory leak, never ' [2018-02-17 08:09:39,121: INFO/MainProcess] <a rel="external nofollow" href="mailto:celery@root">celery@root</a> ready.</p>
</blockquote>
<p>注意：检查上面的[tasks]，它应该包含您在task.py模块中创建的任务的名称。</p>
<p>有关更多信息和日志，您还可以在DEBUG MODE中运行worker实例</p>
<blockquote>
<p>celery <span class="nt">-A</span> <your project name> worker <span class="nt">-l</span> info <span class="nt">--loglevel</span><span class="o">=</span>DEBUG celery -A <your project name> worker -l info --loglevel=DEBUG</p>
</blockquote>
<p>注意：请勿关闭此终端，应保持打开状态！！</p>
<p><span style="color: #ff0000"><strong>测试任务</strong></span></p>
<p>现在让我们从django shell运行任务打开Django shell</p>
<p><code>$ python3 manage.py shell</code></p>
<p>用delay方法运行函数：</p>

```python  
>>> from my_app.tasks import print_message, add
>>> print_message.delay("Jai Singhal")
<AsyncResult: fe4f9787-9ee4-46da-856c-453d36556760>
>>> add.delay(10, 20)
<AsyncResult: ca5d2c50-87bc-4e87-92ad-99d6d9704c30>

当检查您的celery worker实例正在运行的第二个终端时，您将获得此类型的输出，显示您的任务已收到且任务已成功完成

[2018-02-17 08:12:14,375: INFO/MainProcess] Received task: my_app.tasks.print_message[fe4f9787-9ee4-46da-856c-453d36556760] [2018-02-17 08:12:14,377: WARNING/ForkPoolWorker-4] Celery is working!! Jai Singhal have implemented it correctly. [2018-02-17 08:12:14,382: INFO/ForkPoolWorker-4] Task my_app.tasks.print_message[fe4f9787-9ee4-46da-856c-453d36556760] succeeded in 0.004476275000342866s: None [2018-02-17 08:12:28,344: INFO/MainProcess] Received task: my_app.tasks.add[ca5d2c50-87bc-4e87-92ad-99d6d9704c30] [2018-02-17 08:12:28,349: WARNING/ForkPoolWorker-3] Add function has been called!! with params 10, 20 [2018-02-17 08:12:28,358: INFO/ForkPoolWorker-3] Task my_app.tasks.add[ca5d2c50-87bc-4e87-92ad-99d6d9704c30] succeeded in 0.010077004999857309s: 30

总结

以上所述是小编给大家介绍的使用celery和Django处理异步任务的流程分析，希望对大家有所帮助，也非常感谢大家对python博客网站的支持！