Celery

Celery

pip3 install celery

Celery是一个简单、灵活且可靠的，处理大量消息的分布式系统，专注于实时处理的异步任务队列，同时也支持任务调度。

组成

• 消息中间件（rabbitmq,redis)
• 任务执行单元
• 任务执行结果存储(redis)

执行命令语法

celery worker -A celery_app_task -l info
celery worker -A celery_app_task -l info -P eventlet

异步执行

单目录

定义任务 celery_task.py

import celery
import time

broker = 'redis://127.0.0.1:6379/1'
backend = 'redis://127.0.0.1:6379/2'

cel = celery.Celery('test', backend=backend, broker=broker)


@cel.task
def send_email(name):
    print('发邮件')
    time.sleep(5)
    print('完成%s' % name)
    return 'ok'

创建任务执行 produce_task.py

from celery_task import send_email
result = send_email.delay("yuan")
print(result.id)
result2 = send_email.delay("alex")
print(result2.id)　　

获取结果 get_res.py

from celery.result import AsyncResult
from celery_task import cel

async_result=AsyncResult(id="c6ddd5b7-a662-4f0e-93d4-ab69ec2aea5d", app=cel)

if async_result.successful():
    result = async_result.get()
    print(result)
    # result.forget() # 将结果删除
elif async_result.failed():
    print('执行失败')
elif async_result.status == 'PENDING':
    print('任务等待中被执行')
elif async_result.status == 'RETRY':
    print('任务异常后正在重试')
elif async_result.status == 'STARTED':
    print('任务已经开始被执行')

多目录

celery worker -A celery_task -l info -P eventlet

• celery.py: 写配置
• task1 task2 ： 写任务
• get_res : 获取结果
• produce_taks : 生产任务

celery.py 配置

from celery import Celery

cel = Celery('celery_demo',
             broker='redis://127.0.0.1:6379/1',
             backend='redis://127.0.0.1:6379/2',
             # 包含以下两个任务文件，去相应的py文件中找任务，对多个任务做分类
             include=['celery_tasks.task1',
                      'celery_tasks.task2'
                      ])

# 时区
cel.conf.timezone = 'Asia/Shanghai'
# 是否使用UTC
cel.conf.enable_utc = False

定义任务 task1 task2

from celery_tasks.celery import cel
import time


@cel.task
def send_msg(name):
    print('短信')
    time.sleep(5)
    print('完成%s' % name)
    return "短信"

创建任务执行 product_task

from celery_tasks.task1 import send_msg
from celery_tasks.task2 import send_email

# 立即告知celery去执行test_celery任务，并传入一个参数
result = send_email.delay('yuan')
print(result.id)
result = send_msg.delay('yuan')
print(result.id)

获取结果 get_res.py

from celery.result import AsyncResult
from celery_tasks.celery import cel

while True:
    async_result = AsyncResult(id=input(">>"), app=cel)
    if async_result.successful():
        result = async_result.get()
        print(result)
        # result.forget() # 将结果删除
    elif async_result.failed():
        print('执行失败')
    elif async_result.status == 'PENDING':
        print('任务等待中被执行')
    elif async_result.status == 'RETRY':
        print('任务异常后正在重试')
    elif async_result.status == 'STARTED':
        print('任务已经开始被执行')

定时任务

单目录

celery_task.py

from celery_tasks.celery import cel
import time


@cel.task
def send_msg(name):
    print('短信')
    time.sleep(5)
    print('完成%s' % name)
    return "短信"

produce_task.py(邮件运行)

from celery_task import send_email
from datetime import datetime

# 方式一 某一固定时间
# v1 = datetime(2020, 3, 11, 16, 19, 00)
# print(v1)
# v2 = datetime.utcfromtimestamp(v1.timestamp())
# print(v2)
# result = send_email.apply_async(args=["egon",], eta=v2)
# print(result.id)

# 方式二 固定时间以后
ctime = datetime.now()
# 默认用utc时间
utc_ctime = datetime.utcfromtimestamp(ctime.timestamp())
from datetime import timedelta
time_delay = timedelta(seconds=10)
task_time = utc_ctime + time_delay

# 使用apply_async并设定时间
result = send_email.apply_async(args=["egon"], eta=task_time)
print(result.id)

get_Res.py

from celery.result import AsyncResult
from celery_task import cel

async_result=AsyncResult(id="c6ddd5b7-a662-4f0e-93d4-ab69ec2aea5d", app=cel)

if async_result.successful():
    result = async_result.get()
    print(result)
    # result.forget() # 将结果删除
elif async_result.failed():
    print('执行失败')
elif async_result.status == 'PENDING':
    print('任务等待中被执行')
elif async_result.status == 'RETRY':
    print('任务异常后正在重试')
elif async_result.status == 'STARTED':
    print('任务已经开始被执行')

多目录

和 produce_task.py 没关系

celery.py

from datetime import timedelta
from celery import Celery
from celery.schedules import crontab

cel = Celery('tasks', broker='redis://127.0.0.1:6379/1', backend='redis://127.0.0.1:6379/2', include=[
    'celery_tasks.task01',
    'celery_tasks.task02',
])
cel.conf.timezone = 'Asia/Shanghai'
cel.conf.enable_utc = False

cel.conf.beat_schedule = {
    # 名字随意命名
    'add-every-10-seconds': {
        # 执行tasks1下的test_celery函数
        'task': 'celery_tasks.task01.send_email',
        # 每隔2秒执行一次
        # 'schedule': 1.0,
        # 'schedule': crontab(minute="*/1"),
        'schedule': timedelta(seconds=6),
        # 传递参数
        'args': ('张三',)
    },
    # 'add-every-12-seconds': {
    #     'task': 'celery_tasks.task01.send_email',
    #     每年4月11号，8点42分执行
    #     'schedule': crontab(minute=42, hour=8, day_of_month=11, month_of_year=4),
    #     'args': ('张三',)
    # },
} 

produce_task.py 命令

此时和produce无关
通过命令来启动
celery beat -A celery_tasks
进程会读取配置文件的内容，周期性的将配置中到期需要执行的任务发送给任务队列
周期性的向队列插入任务