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Stream Processing
Python Stream Processing
★ 4.5
Python ETL for Real-Time Data
★ 4.3
pip install faust-streamingpip install pathwaypip install faust-streamingpip install pathwayFaust 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.
Python data engineers use Pathway to write streaming pipelines in pure Python without learning a separate API — the DataFrame-like operators (filter, join, groupby, reduce) work identically on both batch files and live Kafka streams. Pathway is particularly suited for real-time feature engineering pipelines that need to update model inputs as new events arrive.
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