effect-stream

Build pull-based streaming pipelines using Effect Stream primitives like Stream, Sink, and Channel to handle backpressure semantics and ensure resource safety via scoped constructs without loading entire datasets into memory.

Yes, you can process NDJSON streams by applying schema-aware channel-based decoding and encoding to safely transform and consume sequences of values while validating data integrity.

Effect Stream supports creating streams from multiple sources including async iterables, readable streams, pagination, callback-based queues, and DOM or Node events for comprehensive data ingestion.

Manage concurrency and sharing by using merge, interleave, broadcast, and share operations to combine streams with scoped safety and deterministic or arrival-order behavior.

Apply transform and control flow operations like debounce, throttle, timeout, and error recovery directly within your Effect streaming pipeline to regulate value emission and handle failures gracefully.

Use schema-aware channel-based encoding to serialize stream data into Msgpack format, allowing you to efficiently consume and encode sequences of values within your pipeline.