RabbitMQ Stream Python Client

A Python asyncio-based client for RabbitMQ Streams This is a work in progress

Install

pip install rstream

Quick start

Publishing messages:

You can publish messages with three different methods:

send: asynchronous, messages are automatically buffered internally and sent at once after a timeout expires.
batch_send: Synchronous, the user buffers the messages and sends them. This is the fastest publishing method.
send_wait: Synchronous, the caller wait till the message is confirmed. This is the slowest publishing method.

Example Using send:

import asyncio
from rstream import Producer, AMQPMessage

async def publish():
    async with Producer('localhost', username='guest', password='guest') as producer:
        await producer.create_stream('mystream')

        for i in range(100):
            amqp_message = AMQPMessage(
                body='hello: {}'.format(i),
            )
            await producer.send('mystream', amqp_message)

asyncio.run(publish())

send is not thread safe so it must be awaited.

Similarly with the send_wait:

import asyncio
from rstream import Producer, AMQPMessage

async def publish():
    async with Producer('localhost', username='guest', password='guest') as producer:
        await producer.create_stream('mystream')

        for i in range(100):
            amqp_message = AMQPMessage(
                body='hello: {}'.format(i),
            )
            await producer.send_wait('mystream', amqp_message)

asyncio.run(publish())

Eventually using batch_send:

import asyncio
from rstream import Producer, AMQPMessage

async def publish():
    async with Producer('localhost', username='guest', password='guest') as producer:
        await producer.create_stream('mystream')
        list_messages = []

        for i in range(100):
            amqp_message = AMQPMessage(
                body='hello: {}'.format(i),
            )
            list_messages.append(amqp_message)

        await producer.send_batch('mystream',  list_messages) 

asyncio.run(publish())

Publishing with confirmation

The Send method takes as parameter an handle function that will be called asynchronously when the message sent will be notified from the server to have been published.

In this case the example will work like this:

import asyncio
from rstream import Producer, AMQPMessage, ConfirmationStatus

def _on_publish_confirm_client(confirmation: ConfirmationStatus) -> None:

     if confirmation.is_confirmed == True:
        print("message id: " + str(confirmation.message_id) + " is confirmed")
     else:
         print("message id: " + str(confirmation.message_id) + " is not confirmed")


async def publish():
    async with Producer('localhost', username='guest', password='guest') as producer:
        await producer.create_stream('mystream')

        for i in range(100):
            amqp_message = AMQPMessage(
                body='hello: {}'.format(i),
            )
            await producer.send('mystream', amqp_message, on_publish_confirm=_on_publish_confirm_client) 

asyncio.run(publish())

Same is valid also for send_batch.

Please note that the publish confirmation callbacks are internally managed by the client and they are triggered in the Producer class. This means that when the Producer will terminate its scope and lifetime you will not be able to receive the remaining notifications if any. Depending on your scenario, you could add a synchronization mechanism (like an asyncio condition) to wait till all the notifications have been received or you could use an asyncio.wait to give time for the callbacks to be invoked by the client.

With send_wait instead will wait until the confirmation from the server is received.

Consuming messages:

import asyncio
import signal
from rstream import Consumer, amqp_decoder, AMQPMessage

async def consume():
    consumer = Consumer(
        host='localhost',
        port=5552,
        vhost='/',
        username='guest',
        password='guest',
    )

    loop = asyncio.get_event_loop()
    loop.add_signal_handler(signal.SIGINT, lambda: asyncio.create_task(consumer.close()))

    def on_message(msg: AMQPMessage):
        print('Got message: {}'.format(msg.body))

    await consumer.start()
    await consumer.subscribe('mystream', on_message, decoder=amqp_decoder)
    await consumer.run()

asyncio.run(consume())

Connecting with SSL:

import ssl

ssl_context = ssl.SSLContext()
ssl_context.load_cert_chain('/path/to/certificate.pem', '/path/to/key.pem')

producer = Producer(
    host='localhost',
    port=5551,
    ssl_context=ssl_context,
    username='guest',
    password='guest',
)

Load Balancer

In order to handle load balancers, you can use the load_balancer_mode parameter for producers and consumers. This will always attempt to create a connection via the load balancer, discarding connections that are inappropriate for the client type.

Producers must connect to the leader node, while consumers can connect to any, prioritizing replicas if available.

TODO

Documentation
Handle MetadataUpdate and reconnect to another broker on stream configuration changes
AsyncIterator protocol for consumer
Add frame size validation

Metadata

Release files for rstream 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for rstream 0.6.0
File	Size	Uploaded
rstream-0.6.0.tar.gz	17.2 kB	Apr 12, 2023	Details

Built distribution (wheel)

Table of built distributions (wheels) for rstream 0.6.0
File	Interpreter	ABI	Platform	Reset
rstream-0.6.0-py3-none-any.whl 20.3 kB Apr 12, 2023	Python 3	none	any	Details

Total release size: 37.5 kB

Release files / rstream-0.6.0.tar.gz

Download URL	rstream-0.6.0.tar.gz
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Uploaded via	`poetry/1.4.2 CPython/3.10.6 Linux/5.15.0-1035-azure`

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Download URL	rstream-0.6.0-py3-none-any.whl
Size	20.3 kB
Tags	Python 3
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Uploaded via	`poetry/1.4.2 CPython/3.10.6 Linux/5.15.0-1035-azure`