The current package is just a wrapper for FastStream objects to make them compatible with Taskiq library.
The main goal of it - provide FastStream with a great Taskiq tasks scheduling feature.
If you already have FastStream project to interact with your Message Broker, you can add scheduling to it by installing just a taskiq-faststream
pip install taskiq-faststreamIf you starting with a clear project, you can specify taskiq-faststream broker by the following distributions:
pip install taskiq-faststream[rabbit]
# or
pip install taskiq-faststream[kafka]
# or
pip install taskiq-faststream[confluent]
# or
pip install taskiq-faststream[nats]
# or
pip install taskiq-faststream[redis]For OpenTelemetry distributed tracing support:
pip install taskiq-faststream[otel]The package gives you two classes: AppWrapper and BrokerWrapper
These are just containers for the related FastStream objects to make them taskiq-compatible
To create scheduling tasks for your broker, just wrap it to BrokerWrapper and use it like a regular taskiq Broker.
# regular FastStream code
from faststream.nats import NatsBroker
broker = NatsBroker()
@broker.subscriber("test-subject")
async def handler(msg: str):
print(msg)
# taskiq-faststream scheduling
from taskiq.schedule_sources import LabelScheduleSource
from taskiq_faststream import BrokerWrapper, StreamScheduler
# wrap FastStream object
taskiq_broker = BrokerWrapper(broker)
# create periodic task
taskiq_broker.task(
message="Hi!",
# If you are using RabbitBroker, then you need to replace subject with queue.
# If you are using KafkaBroker, then you need to replace subject with topic.
subject="test-subject",
schedule=[{
"cron": "* * * * *",
}],
)
# create scheduler object
scheduler = StreamScheduler(
broker=taskiq_broker,
sources=[LabelScheduleSource(taskiq_broker)],
)To run the scheduler, just use the following command
taskiq scheduler module:schedulerAlso, you can wrap your FastStream application the same way (allows to use lifespan events and AsyncAPI documentation):
# regular FastStream code
from faststream import FastStream
from faststream.nats import NatsBroker
broker = NatsBroker()
app = FastStream(broker)
@broker.subscriber("test-subject")
async def handler(msg: str):
print(msg)
# wrap FastStream object
from taskiq_faststream import AppWrapper
taskiq_broker = AppWrapper(app)
# Code below omitted 👇A little feature: instead of using a final message argument, you can set a message callback to collect information right before sending:
async def collect_information_to_send():
return "Message to send"
taskiq_broker.task(
message=collect_information_to_send,
...,
)Also, you can send a multiple message by one task call just using generator message callback with yield
async def collect_information_to_send():
"""Sends 10 messages per task call."""
for i in range(10):
yield i
taskiq_broker.task(
message=collect_information_to_send,
...,
)taskiq-faststream supports taskiq's OpenTelemetry middleware. To enable it, pass OpenTelemetryMiddleware when creating the broker wrapper:
from faststream.nats import NatsBroker
from taskiq_faststream import BrokerWrapper
from taskiq.middlewares.otel_middleware import OpenTelemetryMiddleware
broker = NatsBroker()
# Enable OpenTelemetry middleware
taskiq_broker = BrokerWrapper(broker, middlewares=[OpenTelemetryMiddleware()])This will automatically add OpenTelemetry middleware to track task execution, providing insights into:
- Task execution spans
- Task dependencies and call chains
- Performance metrics
- Error tracking
Make sure to configure your OpenTelemetry exporter (e.g., Jaeger, Zipkin) according to your monitoring setup.
The same applies to AppWrapper:
from faststream import FastStream
from taskiq_faststream import AppWrapper
from taskiq.middlewares.otel_middleware import OpenTelemetryMiddleware
app = FastStream(broker)
# Enable OpenTelemetry middleware
taskiq_broker = AppWrapper(app, middlewares=[OpenTelemetryMiddleware()])