Celery是Python中最流行的异步消息队列框架，支持RabbitMQ、Redis、ZoopKeeper等作为Broker，而对这些消息队列的抽象，都是通过Kombu实现的。Kombu实现了对AMQP transport和non-AMQP transports(Redis、Amazon SQS、ZoopKeeper等)的兼容。
AMQP中的各种概念，Message、Producer、Exchange、Queue、Consumer、Connection、Channel在Kombu中都相应做了实现，另外Kombu还实现了Transport，就是存储和发送消息的实体，用来区分底层消息队列是用amqp、Redis还是其它实现的。
- Message：消息，发送和消费的主体
- Producer: 消息发送者
- Consumer：消息接收者
- Exchange：交换机，消息发送者将消息发至Exchange，Exchange负责将消息分发至队列
- Queue：消息队列，存储着即将被应用消费掉的消息，Exchange负责将消息分发Queue，消费者从Queue接收消息
- Connection：对消息队列连接的抽象
- Channel：与AMQP中概念类似，可以理解成共享一个Connection的多个轻量化连接
- Transport：真实的MQ连接，区分底层消息队列的实现
对于不同的Transport的支持：
代码示例
先从官网示例代码开始:
from kombu import Connection, Exchange, Queue
media_exchange = Exchange('media', 'direct', durable=True)
video_queue = Queue('video', exchange=media_exchange, routing_key='video')
def process_media(body, message):
print body
message.ack()
# connections
with Connection('amqp://guest:guest@localhost//') as conn:
# produce
producer = conn.Producer(serializer='json')
producer.publish({'name': '/tmp/lolcat1.avi', 'size': 1301013},
exchange=media_exchange, routing_key='video',
declare=[video_queue])
# the declare above, makes sure the video queue is declared
# so that the messages can be delivered.
# It's a best practice in Kombu to have both publishers and
# consumers declare the queue. You can also declare the
# queue manually using:
# video_queue(conn).declare()
# consume
with conn.Consumer(video_queue, callbacks=[process_media]) as consumer:
# Process messages and handle events on all channels
while True:
conn.drain_events()
# Consume from several queues on the same channel:
video_queue = Queue('video', exchange=media_exchange, key='video')
image_queue = Queue('image', exchange=media_exchange, key='image')
with connection.Consumer([video_queue, image_queue],
callbacks=[process_media]) as consumer:
while True:
connection.drain_events()
基本上，各种角色都出场了。各种角色的使用都要从建立Connection开始。
Connection
获取连接很简单：
>>> from kombu import Connection
>>> connection = Connection('amqp://guest:guest@localhost:5672//')
现在的连接其实并未真正建立，只有在需要使用的时候才真正建立连接并将连接缓存：
@property
def connection(self):
"""The underlying connection object.
Warning:
This instance is transport specific, so do not
depend on the interface of this object.
"""
if not self._closed:
if not self.connected:
self.declared_entities.clear()
self._default_channel = None
self._connection = self._establish_connection()
self._closed = False
return self._connection
也可以主动连接：
>>> connection.connect()
def connect(self):
"""Establish connection to server immediately."""
self._closed = False
return self.connection
当然，连接底层是由各自使用的不同的Transport建立的：
conn = self.transport.establish_connection()
连接需要显式的关闭：
>>> connection.release()
由于Connection实现了上下文生成器：
def __enter__(self):
return self
def __exit__(self, *args):
self.release()
所以可以使用with语句，以免忘记关闭连接：
with Connection() as connection:
# work with connection
可以使用Connection直接建立Procuder和Consumer，其实就是调用了各自的创建类：
def Producer(self, channel=None, *args, **kwargs):
"""Create new :class:`kombu.Producer` instance."""
from .messaging import Producer
return Producer(channel or self, *args, **kwargs)
def Consumer(self, queues=None, channel=None, *args, **kwargs):
"""Create new :class:`kombu.Consumer` instance."""
from .messaging import Consumer
return Consumer(channel or self, queues, *args, **kwargs)
Producer
连接创建后，可以使用连接创建Producer：
producer = conn.Producer(serializer='json')
也可以直接使用Channel创建：
with connection.channel() as channel:
producer = Producer(channel, ...)
Producer实例初始化的时候会检查第一个channel参数：
self.revive(self.channel)
channel = self.channel = maybe_channel(channel)
这里会检查channel是不是Connection实例，是的话会将其替换为Connection实例的default_channel属性：
def maybe_channel(channel):
"""Get channel from object.
Return the default channel if argument is a connection instance,
otherwise just return the channel given.
"""
if is_connection(channel):
return channel.default_channel
return channel
所以Producer还是与Channel联系在一起的。
Producer发送消息：
producer.publish({'name': '/tmp/lolcat1.avi', 'size': 1301013},
exchange=media_exchange, routing_key='video',
declare=[video_queue])
pulish做的事情，主要是由Channel完成的：
def _publish(self, body, priority, content_type, content_encoding,
┆ ┆ ┆ ┆headers, properties, routing_key, mandatory,
┆ ┆ ┆ ┆immediate, exchange, declare):
┆ channel = self.channel
┆ message = channel.prepare_message(
┆ ┆ body, priority, content_type,
┆ ┆ content_encoding, headers, properties,
┆ )
┆ if declare:
┆ ┆ maybe_declare = self.maybe_declare
┆ ┆ [maybe_declare(entity) for entity in declare]
┆ # handle autogenerated queue names for reply_to
┆ reply_to = properties.get('reply_to')
┆ if isinstance(reply_to, Queue):
┆ ┆ properties['reply_to'] = reply_to.name
┆ return channel.basic_publish(
┆ ┆ message,
┆ ┆ exchange=exchange, routing_key=routing_key,
┆ ┆ mandatory=mandatory, immediate=immediate,
┆ )
Channel组装消息prepare_message，并且发送消息basic_publish。
而Channel又是Transport创建的：
chan = self.transport.create_channel(self.connection)
Transport
当创建Connection时，需要传入hostname，类似于：
amqp://guest:guest@localhost:5672//
然后获取hostname的scheme，比如redis:
transport = transport or urlparse(hostname).scheme
以此来区分创建的Transport的类型。
创建过程：
self.transport_cls = transport
transport_cls = get_transport_cls(transport_cls)
def get_transport_cls(transport=None):
"""Get transport class by name.
The transport string is the full path to a transport class, e.g.::
┆ "kombu.transport.pyamqp:Transport"
If the name does not include `"."` (is not fully qualified),
the alias table will be consulted.
"""
if transport not in _transport_cache:
┆ _transport_cache[transport] = resolve_transport(transport)
return _transport_cache[transport]
transport = TRANSPORT_ALIASES[transport]
TRANSPORT_ALIASES = {
...
'redis': 'kombu.transport.redis:Transport',
...
}
以Redis为例，Transport类在/kombu/transport/redis.py文件，继承自/kombu/transport/virtual/base.py中的Transport类。
创建Channel:
channel = self.Channel(connection)
然后Channel组装消息prepare_message，并且发送消息basic_publish。
Channel
Channel实例有几个属性关联着Consumer、Queue等，virtual.Channel：
class Channel(AbstractChannel, base.StdChannel):
def __init__(self, connection, **kwargs):
self.connection = connection
self._consumers = set()
self._cycle = None
self._tag_to_queue = {}
self._active_queues = []
...
其中，_consumers是相关联的消费者标签集合，_active_queues是相关联的Queue列表，_tag_to_queue则是消费者标签与Queue的映射：
self._tag_to_queue[consumer_tag] = queue
self._consumers.add(consumer_tag)
self._active_queues.append(queue)
Channel对于不同的底层消息队列，也有不同的实现，以Redis为例：
class Channel(virtual.Channel):
"""Redis Channel."""
继承自virtual.Channel。
组装消息函数prepare_message:
def prepare_message(self, body, priority=None, content_type=None,
┆ ┆ ┆ ┆ ┆ content_encoding=None, headers=None, properties=None):
┆ """Prepare message data."""
┆ properties = properties or {}
┆ properties.setdefault('delivery_info', {})
┆ properties.setdefault('priority', priority or self.default_priority)
┆ return {'body': body,
┆ ┆ ┆ 'content-encoding': content_encoding,
┆ ┆ ┆ 'content-type': content_type,
┆ ┆ ┆ 'headers': headers or {},
┆ ┆ ┆ 'properties': properties or {}}
基本上是为消息添加各种属性。
发送消息basic_publish方法是调用_put方法：
def _put(self, queue, message, **kwargs):
┆ """Deliver message."""
┆ pri = self._get_message_priority(message, reverse=False)
┆ with self.conn_or_acquire() as client:
┆ ┆ client.lpush(self._q_for_pri(queue, pri), dumps(message))
client是一个redis.StrictRedis连接：
def _create_client(self, asynchronous=False):
┆ if asynchronous:
┆ ┆ return self.Client(connection_pool=self.async_pool)
┆ return self.Client(connection_pool=self.pool)
self.Client = self._get_client()
def _get_client(self):
┆ if redis.VERSION < (3, 2, 0):
┆ ┆ raise VersionMismatch(
┆ ┆ ┆ 'Redis transport requires redis-py versions 3.2.0 or later. '
┆ ┆ ┆ 'You have {0.__version__}'.format(redis))
┆ return redis.StrictRedis
Redis将消息置于某个列表(lpush)中。还会根据是否异步的选项选择不同的connection_pool。
Consumer
现在消息已经被放置与队列中，那么消息又被如何使用呢？
Consumer初始化需要声明Channel和要消费的队列列表以及处理消息的回调函数列表：
with Consumer(connection, queues, callbacks=[process_media], accept=['json']):
connection.drain_events(timeout=1)
当Consumer实例被当做上下文管理器使用时，会调用consume方法：
def __enter__(self):
self.consume()
return self
consume方法代码：
def consume(self, no_ack=None):
"""Start consuming messages.
Can be called multiple times, but note that while it
will consume from new queues added since the last call,
it will not cancel consuming from removed queues (
use :meth:`cancel_by_queue`).
Arguments:
no_ack (bool): See :attr:`no_ack`.
"""
queues = list(values(self._queues))
if queues:
no_ack = self.no_ack if no_ack is None else no_ack
H, T = queues[:-1], queues[-1]
for queue in H:
self._basic_consume(queue, no_ack=no_ack, nowait=True)
self._basic_consume(T, no_ack=no_ack, nowait=False)
使用_basic_consume方法处理相关的队列列表中的每一项，其中处理最后一个Queue时设置标志nowait=False。
_basic_consume方法代码：
def _basic_consume(self, queue, consumer_tag=None,
no_ack=no_ack, nowait=True):
tag = self._active_tags.get(queue.name)
if tag is None:
tag = self._add_tag(queue, consumer_tag)
queue.consume(tag, self._receive_callback,
no_ack=no_ack, nowait=nowait)
return tag
是将消费者标签以及回调函数传给Queue的consume方法。
Queue的consume方法代码：
def consume(self, consumer_tag='', callback=None,
no_ack=None, nowait=False):
"""Start a queue consumer.
Consumers last as long as the channel they were created on, or
until the client cancels them.
Arguments:
consumer_tag (str): Unique identifier for the consumer.
The consumer tag is local to a connection, so two clients
can use the same consumer tags. If this field is empty
the server will generate a unique tag.
no_ack (bool): If enabled the broker will automatically
ack messages.
nowait (bool): Do not wait for a reply.
callback (Callable): callback called for each delivered message.
"""
if no_ack is None:
no_ack = self.no_ack
return self.channel.basic_consume(
queue=self.name,
no_ack=no_ack,
consumer_tag=consumer_tag or '',
callback=callback,
nowait=nowait,
arguments=self.consumer_arguments)
又回到了Channel，Channel的basic_consume代码：
def basic_consume(self, queue, no_ack, callback, consumer_tag, **kwargs):
"""Consume from `queue`."""
self._tag_to_queue[consumer_tag] = queue
self._active_queues.append(queue)
def _callback(raw_message):
message = self.Message(raw_message, channel=self)
if not no_ack:
self.qos.append(message, message.delivery_tag)
return callback(message)
self.connection._callbacks[queue] = _callback
self._consumers.add(consumer_tag)
self._reset_cycle()
Channel将Consumer标签，Consumer要消费的队列，以及标签与队列的映射关系都记录下来，等待循环调用。另外，还通过Transport将队列与回调函数列表的映射关系记录下来，以便于从队列中取出消息后执行回调函数。
真正的调用是下面这行代码实现的：
connection.drain_events(timeout=1)
现在来到Transport的drain_events方法：
def drain_events(self, connection, timeout=None):
time_start = monotonic()
get = self.cycle.get
polling_interval = self.polling_interval
if timeout and polling_interval and polling_interval > timeout:
polling_interval = timeout
while 1:
try:
get(self._deliver, timeout=timeout)
except Empty:
if timeout is not None and monotonic() - time_start >= timeout:
raise socket.timeout()
if polling_interval is not None:
sleep(polling_interval)
else:
break
看上去是在无限执行get(self._deliver, timeout=timeout)
get是self.cycle的一个方法，cycle是一个FairCycle实例：
self.cycle = self.Cycle(self._drain_channel, self.channels, Empty)
@python_2_unicode_compatible
class FairCycle(object):
"""Cycle between resources.
Consume from a set of resources, where each resource gets
an equal chance to be consumed from.
Arguments:
fun (Callable): Callback to call.
resources (Sequence[Any]): List of resources.
predicate (type): Exception predicate.
"""
def __init__(self, fun, resources, predicate=Exception):
self.fun = fun
self.resources = resources
self.predicate = predicate
self.pos = 0
def _next(self):
while 1:
try:
resource = self.resources[self.pos]
self.pos += 1
return resource
except IndexError:
self.pos = 0
if not self.resources:
raise self.predicate()
def get(self, callback, **kwargs):
"""Get from next resource."""
for tried in count(0): # for infinity
resource = self._next()
try:
return self.fun(resource, callback, **kwargs)
except self.predicate:
# reraise when retries exchausted.
if tried >= len(self.resources) - 1:
raise
FairCycle接受两个参数，fun是要执行的函数fun，而resources作为一个迭代器，每次提供一个item供fun调用。
此处的fun是_drain_channel，resources是channels:
def _drain_channel(self, channel, callback, timeout=None):
return channel.drain_events(callback=callback, timeout=timeout)
Transport相关联的每一个channel都要执行drain_events。
Channel的drain_events代码：
def drain_events(self, timeout=None, callback=None):
callback = callback or self.connection._deliver
if self._consumers and self.qos.can_consume():
if hasattr(self, '_get_many'):
return self._get_many(self._active_queues, timeout=timeout)
return self._poll(self.cycle, callback, timeout=timeout)
raise Empty()
_poll代码：
def _poll(self, cycle, callback, timeout=None):
"""Poll a list of queues for available messages."""
return cycle.get(callback)
又回到了FairCycle，Channel的FairCycle实例：
def _reset_cycle(self):
self._cycle = FairCycle(
self._get_and_deliver, self._active_queues, Empty)
_get_and_deliver方法从队列中取出消息，然后调用Transport传递过来的_deliver方法：
def _get_and_deliver(self, queue, callback):
message = self._get(queue)
callback(message, queue)
_deliver代码：
def _deliver(self, message, queue):
if not queue:
raise KeyError(
'Received message without destination queue: {0}'.format(
message))
try:
callback = self._callbacks[queue]
except KeyError:
logger.warning(W_NO_CONSUMERS, queue)
self._reject_inbound_message(message)
else:
callback(message)
做的事情是根据队列取出注册到此队列的回调函数列表，然后对消息执行列表中的所有回调函数。
回顾
可见，Kombu中Channel和Transport非常重要，Channel记录了队列列表、消费者列表以及两者的映射关系，而Transport记录了队列与回调函数的映射关系。Kombu对所有需要监听的队列_active_queues都查询一遍，直到查询完毕或者遇到一个可以使用的Queue，然后就获取消息，回调此队列对应的callback。