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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
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原文地址：http://my.oschina.net/hochikong/blog/406472
