基本的两种task调用方式：

apply_async()和delay()，前者要把参数放在元组或字典中，后者直接使用参数

快速参考：

T.delay(arg, kwarg=value)

always a shortcut to .apply_async.

T.apply_async((arg, ), {'kwarg': value})

T.apply_async(countdown=10)

executes 10 seconds from now.

T.apply_async(eta=now + timedelta(seconds=10))

executes 10 seconds from now, specifed using eta

T.apply_async(countdown=60, expires=120)

executes in one minute from now, but expires after 2 minutes.

T.apply_async(expires=now + timedelta(days=2))

expires in 2 days, set using datetime.

例子：

task.delay(arg1, arg2, kwarg1='x', kwarg2='y')

task.apply_async(args=[arg1, arg2], kwargs={'kwarg1': 'x', 'kwarg2': 'y'})

其他的特性：

##任务延时（设置countdown参数）##

>>> result = add.apply_async((2, 2), countdown=3)

>>> result.get()    # this takes at least 3 seconds to return

20

##任务过期（设置expires参数）##

>>> # Task expires after one minute from now.

>>> add.apply_async((10, 10), expires=60)

When a worker receives an expired task it will mark the task as REVOKED

##任务重试（设置retry参数）##

add.apply_async((2, 2), retry=True, retry_policy={

'max_retries': 3,

'interval_start': 0,

'interval_step': 0.2,

'interval_max': 0.2,

})

。Retry Policy

A retry policy is a mapping that controls how retries behave, and can contain the following keys:

。max_retries

Maximum number of retries before giving up, in this case the exception that caused the retry to fail will be raised.

A value of 0 or None means it will retry forever.

The default is to retry 3 times.

。interval_start

Defines the number of seconds (float or integer) to wait between retries. Default is 0, which means the first retry will be instantaneous.

。interval_step

On each consecutive retry this number will be added to the retry delay (float or integer). Default is 0.2.

。interval_max

Maximum number of seconds (float or integer) to wait between retries. Default is 0.2.

##序列化工具（设置serializer参数）##

有几种可用的序列化工具：JSON，pickle，YAML，msgpack

JSON虽然不错，但是对于传输二进制数据有点无力，因为基于Base64编码，数据体积变大，而且可用的数据格式有限

pickle适用于无需支持其他语言开发的组件的情况，传输二进制文件更轻量级和快速

YAML对跨语言的兼容性不错，支持更多的数据格式。但是处理它的python模块比较慢

msgpack是一种新的交换格式，功能类似JSON，不过还是too young

序列化工具的配置优先级如下

1、The serializer execution option.

2、The Task.serializer attribute

3、The CELERY_TASK_SERIALIZER setting.

e.g >>> add.apply_async((10, 10), serializer='json')

##压缩工具（设置compression）##

如果发送的消息比较大，可以考虑压缩消息

e.g >>> add.apply_async((2, 2), compression='zlib')

##不同的消息队列#

e.g add.apply_async(queue='priority.high')

e.g $ celery -A proj worker -l info -Q celery,priority.high

高级参数：

。exchange

Name of exchange (or a kombu.entity.Exchange) to send the message to.

。routing_key

Routing key used to determine.

。priority

A number between 0 and 9, where 0 is the highest priority.

Supported by: redis, beanstalk