What it does
FastStream provides subscriber and publisher abstractions, Pydantic validation, dependency injection, and AsyncAPI support across supported brokers.
Why it’s interesting
Message processing has different failure and delivery semantics from HTTP. A broker abstraction helps share application patterns while broker-specific behavior still matters.
Real-world use case
Validate order events and publish confirmations from a queue consumer.
What I can learn
- 01
Broker adapter design
Compare how one publish/subscribe interface maps to broker concepts such as topics, queues, exchanges, and subjects.
- 02
AsyncAPI generation from handlers and schemas
See how Python type hints and message schemas can become machine-readable AsyncAPI descriptions for event consumers.
- 03
In-memory broker testing
Learn how an in-memory test broker exercises handlers without requiring a running Kafka cluster.
One thing to explore
Broker subscribers and AsyncAPI
Follow the faststream implementation and connect it to the concepts above.
Explore the source (opens in a new tab)10-Minute Challenge
Model an order event
Before you start: Python. Broker-specific test helpers vary; follow the current FastStream tutorial for the installed broker.
- Install FastStream and Pydantic.
- Define a Pydantic event model and inspect a broker subscriber example.
- Run the documented TestBroker example and check the returned event.
pip install faststream