Celery -- 分佈式任務隊列 及實例

Celery 使用場景及實例　

• Celery介紹和基本使用
• 在項目中如何使用celery
• 啓用多個workers
• Celery 定時任務
• 與django結合
• 經過django配置celery periodic task

1、Celery介紹和基本使用

Celery 是一個 基於python開發的分佈式異步消息任務隊列，經過它能夠輕鬆的實現任務的異步處理， 若是你的業務場景中須要用到異步任務，就能夠考慮使用celery， 舉幾個實例場景中可用的例子:

1. 你想對100臺機器執行一條批量命令，可能會花很長時間 ，但你不想讓你的程序等着結果返回，而是給你返回 一個任務ID,你過一段時間只須要拿着這個任務id就能夠拿到任務執行結果， 在任務執行ing進行時，你能夠繼續作其它的事情。 
2. 你想作一個定時任務，好比天天檢測一下大家全部客戶的資料，若是發現今天 是客戶的生日，就給他發個短信祝福

Celery 在執行任務時須要經過一個消息中間件來接收和發送任務消息，以及存儲任務結果， 通常使用rabbitMQ or Redis,後面會講

1.1 Celery有如下優勢：

1. 簡單：一單熟悉了celery的工做流程後，配置和使用仍是比較簡單的
2. 高可用：當任務執行失敗或執行過程當中發生鏈接中斷，celery 會自動嘗試從新執行任務
3. 快速：一個單進程的celery每分鐘可處理上百萬個任務
4. 靈活： 幾乎celery的各個組件均可以被擴展及自定製

Celery基本工做流程圖：

1.2 Celery安裝使用

Celery的默認broker是RabbitMQ, 僅需配置一行就能夠

broker_url = 'amqp://guest:guest@localhost:5672//'

rabbitMQ 沒裝的話請裝一下，安裝看這裏  http://docs.celeryproject.org/en/latest/getting-started/brokers/rabbitmq.html#id3

使用Redis作broker也能夠

安裝redis組件

$ pip install -U "celery[redis]"

配置

Configuration is easy, just configure the location of your Redis database:

app.conf.broker_url = 'redis://localhost:6379/0'

Where the URL is in the format of:

redis://:password@hostname:port/db_number

all fields after the scheme are optional, and will default to localhost on port 6379, using database 0.

若是想獲取每一個任務的執行結果，還須要配置一下把任務結果存在哪

If you also want to store the state and return values of tasks in Redis, you should configure these settings:

app.conf.result_backend = 'redis://localhost:6379/0'

1. 3 開始使用Celery啦　　

安裝celery模塊

$ pip install celery

建立一個celery application 用來定義你的任務列表

建立一個任務文件就叫task.py !!!

from celery import Celery
import subprocess

# 注意 下方的 ‘tasks’ 能夠是任意名稱 並非必須保持任務腳本名同樣 
app = Celery('tasks',
             broker='redis://192.168.14.234',
             backend='redis://192.168.14.234')

@app.task
def add(x, y):
    print("running...", x, y)
    return x + y

@app.task
def run_cmd(cmd):
    cmd_obj = subprocess.Popen(cmd,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE)

啓動Celery Worker來開始監聽並執行任務

$ celery -A task worker --loglevel=info

注意：這裏的 ‘task’要和你的任務文件名一致！！！

操做的時候，若是須要重啓worker 能夠按兩次Ctrl+C。

調用任務

再打開一個終端， 進行命令行模式，調用任務　

>>> from tasks import add
>>> add.delay(4, 4)

看你的worker終端會顯示收到 一個任務，此時你想看任務結果的話，須要在調用 任務時　賦值個變量

>>> result = add.delay(4, 4)

The ready() method returns whether the task has finished processing or not:

用來檢測任務結果是否實行完畢，即任務執行結果是否準備好。

>>> result.ready()
False

You can wait for the result to complete, but this is rarely used since it turns the asynchronous call into a synchronous one:

# get參數能夠設置超時時間，以下，若是設置爲1，則表示1秒以內沒有收到結果，就會報接收超時。

>>> result.get(timeout=1)
8

In case the task raised an exception, get() will re-raise the exception, but you can override this by specifying the propagate argument:

# propagate=False 默認值爲True，設置爲False做用：能夠對異常信息進行格式化輸出。

>>> result.get(propagate=False)

If the task raised an exception you can also gain access to the original traceback:

# traceback用於追蹤錯誤信息，用於調試的時候，定位錯誤信息位置。

>>> result.traceback

上述實例練習截圖：（調用’df -h’命令 查看磁盤空間）

 

2、在項目中如何使用celery　

能夠把celery配置成一個應用，實現配置文件和任務文件的分離。

目錄格式以下：

proj/__init__.py
    /celery.py
    /tasks.py

proj/celery.py內容

下方的broker 和 backend 設置，根據本身的環境寫，能夠用RabbitMQ，amqp，Redis等；

broker='amqp://',

backend='amqp://',

from __future__ import absolute_import, unicode_literals
from celery import Celery

app = Celery('proj',
             broker='amqp://',
             backend='amqp://',
             include=['proj.tasks'])
 
# Optional configuration, see the application user guide.
app.conf.update(
    result_expires=3600,
)
 
if __name__ == '__main__':
    app.start()

proj/tasks.py中的內容

from __future__ import absolute_import, unicode_literals
from .celery import app

@app.task
def add(x, y):
    return x + y
@app.task
def mul(x, y):
    return x * y
@app.task
def xsum(numbers):
    return sum(numbers)

啓動worker  (注意：這裏啓動的任務名稱，要用項目名：proj，而不是上邊的單獨任務文件名！！！)

$ celery -A proj worker -l info

輸出：

-------------- celery@jessonPC v4.0.2 (latentcall)
---- **** ----- 
--- * ***  * -- Linux-3.19.0-25-generic-x86_64-with-Ubuntu-14.04-trusty 2017-02-22 12:55:17
-- * - **** --- 
- ** ---------- [config]
- ** ---------- .> app:         proj:0x7fb1183dbdd8
- ** ---------- .> transport:   redis://192.168.14.234:6379//
- ** ---------- .> results:     redis://192.168.14.234/
- *** --- * --- .> concurrency: 1 (prefork)
-- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
--- ***** ----- 
-------------- [queues]
                .> celery           exchange=celery(direct) key=celery

後臺啓動worker

In the background

In production you’ll want to run the worker in the background, this is described in detail in the daemonization tutorial.

The daemonization scripts uses the celery multi command to start one or more workers in the background:

# 開啓後臺多個任務進程

$ celery multi start w1 -A proj -l info
celery multi v4.0.0 (latentcall)
> Starting nodes...
    > w1.halcyon.local: OK

You can restart it too:

# restart  重啓相關的任務進程

$ celery  multi restart w1 -A proj -l info
celery multi v4.0.0 (latentcall)
> Stopping nodes...
    > w1.halcyon.local: TERM -> 64024
> Waiting for 1 node.....
    > w1.halcyon.local: OK
> Restarting node w1.halcyon.local: OK
celery multi v4.0.0 (latentcall)
> Stopping nodes...
    > w1.halcyon.local: TERM -> 64052

or stop it: # stop終止相關的任務進程

$ celery multi stop w1    # 後邊的參數能夠省略 -A proj -l info

The stop command is asynchronous so it won’t wait for the worker to shutdown. You’ll probably want to use the stopwait command instead, this ensures all currently executing tasks is completed before exiting:

$ celery multi stopwait w1 -A proj -l info

3、Celery 定時任務

celery支持定時任務，設定好任務的執行時間，celery就會定時自動幫你執行， 這個定時任務模塊叫celery beat。

寫一個腳本：periodic_task.py

from celery import Celery
from celery.schedules import crontab
 
app = Celery()
 
@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
    # Calls test('hello') every 10 seconds.
    sender.add_periodic_task(10.0, test.s('hello'), name='add every 10')
 
    # Calls test('world') every 30 seconds
    sender.add_periodic_task(30.0, test.s('world'), expires=10)
 
    # Executes every Monday morning at 7:30 a.m.
    sender.add_periodic_task(
        crontab(hour=7, minute=30, day_of_week=1),
        test.s('Happy Mondays!'),
    )
 
@app.task
def test(arg):
    print(arg)

add_periodic_task 會添加一條定時任務

上面是經過調用函數添加定時任務，也能夠像寫配置文件 同樣的形式添加， 下面是每30s執行的任務。

app.conf.beat_schedule = {
    'add-every-30-seconds': {
        'task': 'tasks.add',
        'schedule': 30.0,
        'args': (16, 16)
    },
}
app.conf.timezone = 'UTC'

任務添加好了，須要讓celery單獨啓動一個進程來定時發起這些任務， 注意， 這裏是發起任務，不是執行，這個進程只會不斷的去檢查你的任務計劃， 每發現有任務須要執行了，就發起一個任務調用消息，交給celery worker去執行。

啓動任務調度器 celery beat

$ celery -A periodic_task beat

輸出like below

celery beat v4.0.2 (latentcall) is starting.
__    -    ... __   -        _
LocalTime -> 2017-02-08 18:39:31
Configuration ->
    . broker -> redis://localhost:6379//
    . loader -> celery.loaders.app.AppLoader
    . scheduler -> celery.beat.PersistentScheduler
    . db -> celerybeat-schedule
    . logfile -> [stderr]@%WARNING
    . maxinterval -> 5.00 minutes (300s)

此時還差一步，就是還須要啓動一個worker,負責執行celery beat發起的任務。

啓動celery worker來執行任務

$ celery -A periodic_task worker
  
 -------------- celery@Alexs-MacBook-Pro.local v4.0.2 (latentcall)
---- **** -----
--- * ***  * -- Darwin-15.6.0-x86_64-i386-64bit 2017-02-08 18:42:08
-- * - **** ---
- ** ---------- [config]
- ** ---------- .> app:         tasks:0x104d420b8
- ** ---------- .> transport:   redis://localhost:6379//
- ** ---------- .> results:     redis://localhost/
- *** --- * --- .> concurrency: 8 (prefork)
-- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
--- ***** -----
 -------------- [queues]
                .> celery           exchange=celery(direct) key=celery

 

OK，此時觀察worker的輸出，是否是每隔一小會，就會執行一次定時任務呢！
注意：Beat needs to store the last run times of the tasks in a local database file (named celerybeat-schedule by default), so it needs access to write in the current directory, or alternatively you can specify a custom location for this file:

$ celery -A periodic_task beat -s /home/celery/var/run/celerybeat-schedule

更復雜的定時配置　　

上面的定時任務比較簡單，只是每多少s執行一個任務，但若是你想要每週一三五的早上8點給你發郵件怎麼辦呢？哈，其實也簡單，用crontab功能，跟linux自帶的crontab功能是同樣的，能夠個性化定製任務執行時間：

linux crontab http://www.cnblogs.com/peida/archive/2013/01/08/2850483.html

from celery.schedules import crontab
 
app.conf.beat_schedule = {
    # Executes every Monday morning at 7:30 a.m.
    'add-every-monday-morning': {
        'task': 'tasks.add',
        'schedule': crontab(hour=7, minute=30, day_of_week=1),
        'args': (16, 16),
    },
}

上面的這條意思是每週1的早上7.30執行tasks.add任務

還有更多定時配置方式以下：

Example	Meaning
crontab()	Execute every minute.
crontab(minute=0, hour=0)	Execute daily at midnight.
crontab(minute=0, hour='*/3')	Execute every three hours: midnight, 3am, 6am, 9am, noon, 3pm, 6pm, 9pm.
crontab(minute=0, hour='0,3,6,9,12,15,18,21')	Same as previous.
crontab(minute='*/15')	Execute every 15 minutes.
crontab(day_of_week='sunday')	Execute every minute (!) at Sundays.
crontab(minute='*', hour='*', day_of_week='sun')	Same as previous.
crontab(minute='*/10', hour='3,17,22', day_of_week='thu,fri')	Execute every ten minutes, but only between 3-4 am, 5-6 pm, and 10-11 pm on Thursdays or Fridays.
crontab(minute=0,hour='*/2,*/3')	Execute every even hour, and every hour divisible by three. This means: at every hour except: 1am, 5am, 7am, 11am, 1pm, 5pm, 7pm, 11pm
crontab(minute=0, hour='*/5')	Execute hour divisible by 5. This means that it is triggered at 3pm, not 5pm (since 3pm equals the 24-hour clock value of 「15」, which is divisible by 5).
crontab(minute=0, hour='*/3,8-17')	Execute every hour divisible by 3, and every hour during office hours (8am-5pm).
crontab(0, 0,day_of_month='2')	Execute on the second day of every month.
crontab(0, 0, day_of_month='2-30/3')	Execute on every even numbered day.
crontab(0, 0, day_of_month='1-7,15-21')	Execute on the first and third weeks of the month.
crontab(0, 0,day_of_month='11', month_of_year='5')	Execute on the eleventh of May every year.
crontab(0, 0, month_of_year='*/3')	Execute on the first month of every quarter.

 

上面能知足你絕大多數定時任務需求了，甚至還能根據潮起潮落來配置定時任務， 具體看 http://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html#solar-schedules 　　

 

4、最佳實踐之與django結合

django 能夠輕鬆跟celery結合實現異步任務，只需簡單配置便可

If you have a modern Django project layout like:

- proj/
  - proj/__init__.py
  - proj/settings.py
  - proj/urls.py
- manage.py

 

 

 

django + celery 配置注意事項

說生產環境中不建議 django項目的settings文件開啓debug模式，由於這樣可能會致使服務器內存泄露。

PS：內存泄露 和 內存溢出的區別

修改建議：將django settings中的DEBUG參數設置爲False