Subscribing to a topic#
To receive messages for a topic, we need to subscribe to it. Incoming messages are queued internally. You can use the Client.messages
generator to iterate over incoming messages. This is a minimal working example that listens for messages to the temperature/#
wildcard:
import asyncio
import aiomqtt
async def main():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
async for message in client.messages:
print(message.payload)
asyncio.run(main())
Now you can use the minimal publisher example to publish a message to temperature/outside
and see it appear in the console.
Tip
You can set the Quality of Service of the subscription by passing the qos
parameter to Client.subscribe()
.
Filtering messages#
Imagine that we measure temperature and humidity on the outside and inside. We want to receive all types of measurements but handle them differently.
You can filter messages with Topic.matches()
. Similar to Client.subscribe()
, Topic.matches()
also accepts wildcards (e.g. temperature/#
):
import asyncio
import aiomqtt
async def main():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
await client.subscribe("humidity/#")
async for message in client.messages:
if message.topic.matches("humidity/inside"):
print("A:", message.payload)
if message.topic.matches("+/outside"):
print("B:", message.payload)
if message.topic.matches("temperature/#"):
print("C:", message.payload)
asyncio.run(main())
Note
In our example, messages to temperature/outside
are handled twice!
Tip
For details on the +
and #
wildcards and what topics they match, see the OASIS specification.
The message queue#
Messages are queued internally and returned sequentially from Client.messages
.
The default queue is asyncio.Queue
which returns messages on a FIFO (“first in first out”) basis. You can pass other types of asyncio queues as queue_type
to the Client
to modify the order in which messages are returned, e.g. asyncio.LifoQueue
.
You can subclass asyncio.PriorityQueue
to queue based on priority. Messages are returned ascendingly by their priority values. In the case of ties, messages with lower message identifiers are returned first.
Let’s say we measure temperature and humidity again, but we want to prioritize humidity:
import asyncio
import aiomqtt
class CustomPriorityQueue(asyncio.PriorityQueue):
def _put(self, item):
priority = 2
if item.topic.matches("humidity/#"): # Assign priority
priority = 1
super()._put((priority, item))
def _get(self):
return super()._get()[1]
async def main():
async with aiomqtt.Client(
"test.mosquitto.org", queue_type=CustomPriorityQueue
) as client:
await client.subscribe("temperature/#")
await client.subscribe("humidity/#")
async for message in client.messages:
print(message.payload)
asyncio.run(main())
Tip
By default, the size of the queue is unlimited. You can set a limit through the client’s max_queued_incoming_messages
argument. len(client.messages)
returns the current number of messages in the queue.
Processing concurrently#
Messages are queued internally and returned sequentially from Client.messages
. If a message takes a long time to handle, it blocks the handling of other messages.
You can handle messages concurrently by using multiple worker tasks like so:
import asyncio
import aiomqtt
async def work(client):
async for message in client.messages:
await asyncio.sleep(5) # Simulate some I/O-bound work
print(message.payload)
async def main():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
# Use a task group to manage and await all worker tasks
async with asyncio.TaskGroup() as tg:
for _ in range(2): # You can use more than two workers here
tg.create_task(work(client))
asyncio.run(main())
Important
Coroutines only make sense if your message handling is I/O-bound. If it’s CPU-bound, you should spawn multiple processes instead.
Listening without blocking#
When you run the minimal example for subscribing and listening for messages, you’ll notice that the program doesn’t finish. Waiting for messages through the Client.messages()
generator blocks the execution of everything that comes afterward.
In case you want to run other code after starting your listener, this is not very practical.
You can use asyncio.TaskGroup
(or asyncio.gather
for Python <3.11
) to safely run other tasks alongside the MQTT listener:
import asyncio
import aiomqtt
async def sleep(seconds):
# Some other task that needs to run concurrently
await asyncio.sleep(seconds)
print(f"Slept for {seconds} seconds!")
async def listen():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
async for message in client.messages:
print(message.payload)
async def main():
# Use a task group to manage and await all tasks
async with asyncio.TaskGroup() as tg:
tg.create_task(sleep(2))
tg.create_task(listen()) # Start the listener task
tg.create_task(sleep(3))
tg.create_task(sleep(1))
asyncio.run(main())
In case task groups are not an option (e.g. because you run aiomqtt alongside a web framework) you can start the listener in a fire-and-forget way. The idea is to use asyncio’s create_task
without awaiting the created task:
Caution
You need to be a bit careful with this approach. Exceptions raised in asyncio tasks are propagated only when we await
the task. In this case, we explicitly don’t.
You need to handle all possible exceptions inside the fire-and-forget task. Unhandled exceptions will be silently ignored until the program exits.
import asyncio
import aiomqtt
async def listen():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
async for message in client.messages:
print(message.payload)
background_tasks = set()
async def main():
loop = asyncio.get_event_loop()
# Listen for mqtt messages in an (unawaited) asyncio task
task = loop.create_task(listen())
# Save a reference to the task so it doesn't get garbage collected
background_tasks.add(task)
task.add_done_callback(background_tasks.remove)
# Infinitely do something else (e.g. handling HTTP requests)
while True:
await asyncio.sleep(1)
asyncio.run(main())
Important
You need to keep a reference to the task so it doesn’t get garbage collected mid-execution. That’s what we’re using the background_tasks
set in our example for.
Stop listening#
You might want to have a listener task running alongside other code, and then stop it when you’re done. You can use asyncio.Task.cancel()
for this:
import asyncio
import aiomqtt
async def listen():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
async for message in client.messages:
print(message.payload)
async def main():
loop = asyncio.get_event_loop()
# Listen for MQTT messages in (unawaited) asyncio task
task = loop.create_task(listen())
# Do something else for a while
await asyncio.sleep(5)
# Cancel the task
task.cancel()
# Wait for the task to be cancelled
try:
await task
except asyncio.CancelledError:
pass
asyncio.run(main())
Stop listening after timeout#
For use cases where you only want to listen to messages for a certain amount of time, we can use asyncio’s timeouts, which were introduced in Python 3.11
:
import asyncio
import aiomqtt
async def listen():
async with aiomqtt.Client("test.mosquitto.org") as client:
await client.subscribe("temperature/#")
async for message in client.messages:
print(message.payload)
async def main():
try:
# Cancel the listener task after 5 seconds
async with asyncio.timeout(5):
await listen()
# Ignore the resulting TimeoutError
except asyncio.TimeoutError:
pass
asyncio.run(main())