Faust

About Faust

Stream processing library porting ideas from Kafka Streams to Python. Used for building high-performance and reliable real-time stream processing applications with Pythonic API.

Key Features

• 1Python-native stream processing framework built on Kafka
• 2Stateful processing with RocksDB-backed tables for aggregations
• 3Async agents defined as `@app.agent` coroutines for each topic
• 4Cron-style timers and windowed aggregations built in
• 5Type annotations on stream records enable schema validation at runtime

How Python Data Engineers Use Faust

Faust lets Python data engineers write Kafka stream processors entirely in async Python — defining an agent as a coroutine that processes messages from a topic and produces results to another. Engineers use Faust tables for stateful aggregations (e.g., running counts or session windows) that persist across restarts via RocksDB.