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Moved serialization section from README to it's own section in the user guide

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Ask Solem 2010-11-11 16:00:44 +01:00
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README.rst
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@ -4,24 +4,18 @@
:Version: 0.9.4
**THIS IS A REWRITE OF CARROT**
Carrot will be discontinued in favor of Kombu.
**ORIGINAL CARROT README BELOW**
Introduction
------------
`kombu` is an `AMQP`_ messaging queue framework. AMQP is the Advanced Message
`Kombu` is an `AMQP`_ messaging queue framework. AMQP is the Advanced Message
Queuing Protocol, an open standard protocol for message orientation, queuing,
routing, reliability and security.
The aim of `kombu` is to make messaging in Python as easy as possible by
providing a high-level interface for producing and consuming messages. At the
same time it is a goal to re-use what is already available as much as possible.
The aim of `Kombu` is to make messaging in Python as easy as possible by
providing a high-level interface for producing and consuming messages,
and provide tested and proven implementations of common messaging patterns.
`kombu` has pluggable messaging transports, so it is possible to support
`Kombu` has pluggable messaging transports, so it is possible to support
several messaging systems. Currently, there is support for `AMQP`_
(`py-amqplib`_, `pika`_), `STOMP`_ (`stompy`_). There's also an
in-memory transport for testing purposes, using the `Python queue module`_.
@ -30,7 +24,7 @@ Several AMQP message broker implementations exists, including `RabbitMQ`_,
`Apache ActiveMQ`_. You'll need to have one of these installed,
personally we've been using `RabbitMQ`_.
Before you start playing with `kombu`, you should probably read up on
Before you start playing with `Kombu`, you should probably read up on
AMQP, and you could start with the excellent article about using RabbitMQ
under Python, `Rabbits and warrens`_. For more detailed information, you can
refer to the `Wikipedia article about AMQP`_.
@ -96,7 +90,7 @@ Quick overview
`Exchange` and `Queue` are simply declarations that can be pickled
and used in configuaration files etc.
They also support operations, but to do so they need to bound
They also support operations, but to do so they need to be bound
to a channel:
.. code-block:: python
@ -116,7 +110,7 @@ to a channel:
Installation
============
You can install `kombu` either via the Python Package Index (PyPI)
You can install `Kombu` either via the Python Package Index (PyPI)
or from source.
To install using `pip`,::
@ -191,193 +185,6 @@ There are some concepts you should be familiar with before starting:
routing keys `"usd.stock"` and `"eur.stock.db"` but not
`"stock.nasdaq"`.
Examples
========
Creating a connection
---------------------
You can set up a connection by creating an instance of
`kombu.BrokerConnection`, with the appropriate options for
your broker:
>>> from kombu import BrokerConnection
>>> conn = BrokerConnection(hostname="localhost", port=5672,
... userid="guest", password="guest",
... virtual_host="/")
Receiving messages using a Consumer
-----------------------------------
First we open up a Python shell and start a message consumer.
This consumer declares a queue named `"feed"`, receiving messages with
the routing key `"importer"` from the `"feed"` exchange.
>>> from kombu import Exchange, Queue, Consumer
>>> feed_exchange = Exchange("feed", type="direct")
>>> feed_queue = Queue("feed", feed_exchange, "importer")
>>> channel = connection.channel()
>>> consumer = Consumer(channel, [feed_queue])
>>> def import_feed_callback(message_data, message)
... feed_url = message_data["import_feed"]
... print("Got feed import message for: %s" % feed_url)
... # something importing this feed url
... # import_feed(feed_url)
... message.ack()
>>> consumer.register_callback(import_feed_callback)
>>> # Consume messages in a loop
>>> while True:
... connection.drain_events(timeout=...)
Sending messages using a Producer
---------------------------------
Then we open up another Python shell to send some messages to the consumer
defined in the last section.
>>> from kombu import Exchange, Producer
>>> feed_exchange = Exchange("feed", type="direct")
>>> channel = connection.channel()
>>> producer = Producer(channel, feed_exchange)
>>> producer.publish({"import_feed": "http://cnn.com/rss/edition.rss"},
... routing_key="importer")
>>> producer.close()
Look in the first Python shell again (where consumer loop is running),
where the following text has been printed to the screen::
Got feed import message for: http://cnn.com/rss/edition.rss
Serialization of Data
-----------------------
By default every message is encoded using `JSON`_, so sending
Python data structures like dictionaries and lists works.
`YAML`_, `msgpack`_ and Python's built-in `pickle` module is also supported,
and if needed you can register any custom serialization scheme you
want to use.
.. _`JSON`: http://www.json.org/
.. _`YAML`: http://yaml.org/
.. _`msgpack`: http://msgpack.sourceforge.net/
Each option has its advantages and disadvantages.
`json` -- JSON is supported in many programming languages, is now
a standard part of Python (since 2.6), and is fairly fast to
decode using the modern Python libraries such as `cjson` or
`simplejson`.
The primary disadvantage to `JSON` is that it limits you to
the following data types: strings, unicode, floats, boolean,
dictionaries, and lists. Decimals and dates are notably missing.
Also, binary data will be transferred using base64 encoding, which
will cause the transferred data to be around 34% larger than an
encoding which supports native binary types.
However, if your data fits inside the above constraints and
you need cross-language support, the default setting of `JSON`
is probably your best choice.
`pickle` -- If you have no desire to support any language other than
Python, then using the `pickle` encoding will gain you
the support of all built-in Python data types (except class instances),
smaller messages when sending binary files, and a slight speedup
over `JSON` processing.
`yaml` -- YAML has many of the same characteristics as `json`,
except that it natively supports more data types (including dates,
recursive references, etc.)
However, the Python libraries for YAML are a good bit slower
than the libraries for JSON.
If you need a more expressive set of data types and need to maintain
cross-language compatibility, then `YAML` may be a better fit
than the above.
To instruct carrot to use an alternate serialization method,
use one of the following options.
1. Set the serialization option on a per-producer basis::
>>> producer = Producer(channel,
... exchange=exchange,
... serializer="yaml")
2. Set the serialization option per message::
>>> producer.publish(message, routing_key=rkey,
... serializer="pickle")
Note that a `Consumer` do not need the serialization method specified.
They can auto-detect the serialization method as the
content-type is sent as a message header.
Sending raw data without Serialization
---------------------------------------
In some cases, you don't need your message data to be serialized. If you
pass in a plain string or unicode object as your message, then carrot will
not waste cycles serializing/deserializing the data.
You can optionally specify a `content_type` and `content_encoding`
for the raw data:
>>> producer.send(open('~/my_picture.jpg','rb').read(),
content_type="image/jpeg",
content_encoding="binary",
routing_key=rkey)
The `Message` object returned by the `Consumer` class will have a
`content_type` and `content_encoding` attribute.
Sub-classing the messaging classes
----------------------------------
The `Consumer`, and `Producer` classes can also be sub classed. Thus you
can define the above producer and consumer like so:
>>> class FeedProducer(Producer):
... exchange = exchange
... routing_key = "importer"
...
... def import_feed(self, feed_url):
... return self.publish({"action": "import_feed",
... "feed_url": feed_url})
>>> class FeedConsumer(Consumer):
... queues = queues
...
... def receive(self, message_data, message):
... action = message_data["action"]
... if action == "import_feed":
... # something importing this feed
... # import_feed(message_data["feed_url"])
message.ack()
... else:
... raise Exception("Unknown action: %s" % action)
>>> producer = FeedProducer(channel)
>>> producer.import_feed("http://cnn.com/rss/edition.rss")
>>> producer.close()
>>> consumer = FeedConsumer(channel)
>>> while True:
... connection.drain_events()
Getting Help
============
@ -397,7 +204,7 @@ to our issue tracker at http://github.com/ask/kombu/issues/
Contributing
============
Development of `kombu` happens at Github: http://github.com/ask/kombu
Development of `Kombu` happens at Github: http://github.com/ask/kombu
You are highly encouraged to participate in the development. If you don't
like Github (for some reason) you're welcome to send regular patches.

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docs/userguide/index.rst
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@ -10,3 +10,4 @@
connections
simple
serialization

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@ -0,0 +1,94 @@
.. _guide-serialization:
===============
Serialization
===============
.. _serializers:
Serializers
===========
By default every message is encoded using `JSON`_, so sending
Python data structures like dictionaries and lists works.
`YAML`_, `msgpack`_ and Python's built-in `pickle` module is also supported,
and if needed you can register any custom serialization scheme you
want to use.
.. _`JSON`: http://www.json.org/
.. _`YAML`: http://yaml.org/
.. _`msgpack`: http://msgpack.sourceforge.net/
Each option has its advantages and disadvantages.
`json` -- JSON is supported in many programming languages, is now
a standard part of Python (since 2.6), and is fairly fast to
decode using the modern Python libraries such as `cjson` or
`simplejson`.
The primary disadvantage to `JSON` is that it limits you to
the following data types: strings, unicode, floats, boolean,
dictionaries, and lists. Decimals and dates are notably missing.
Also, binary data will be transferred using base64 encoding, which
will cause the transferred data to be around 34% larger than an
encoding which supports native binary types.
However, if your data fits inside the above constraints and
you need cross-language support, the default setting of `JSON`
is probably your best choice.
`pickle` -- If you have no desire to support any language other than
Python, then using the `pickle` encoding will gain you
the support of all built-in Python data types (except class instances),
smaller messages when sending binary files, and a slight speedup
over `JSON` processing.
`yaml` -- YAML has many of the same characteristics as `json`,
except that it natively supports more data types (including dates,
recursive references, etc.)
However, the Python libraries for YAML are a good bit slower
than the libraries for JSON.
If you need a more expressive set of data types and need to maintain
cross-language compatibility, then `YAML` may be a better fit
than the above.
To instruct carrot to use an alternate serialization method,
use one of the following options.
1. Set the serialization option on a per-producer basis::
>>> producer = Producer(channel,
... exchange=exchange,
... serializer="yaml")
2. Set the serialization option per message::
>>> producer.publish(message, routing_key=rkey,
... serializer="pickle")
Note that a `Consumer` do not need the serialization method specified.
They can auto-detect the serialization method as the
content-type is sent as a message header.
.. _sending-raw-data:
Sending raw data without Serialization
======================================
In some cases, you don't need your message data to be serialized. If you
pass in a plain string or unicode object as your message, then carrot will
not waste cycles serializing/deserializing the data.
You can optionally specify a `content_type` and `content_encoding`
for the raw data::
>>> producer.send(open('~/my_picture.jpg','rb').read(),
content_type="image/jpeg",
content_encoding="binary",
routing_key=rkey)
The `Message` object returned by the `Consumer` class will have a
`content_type` and `content_encoding` attribute.