Not all streaming workloads involve I/O. When your source is in-memory and your transforms are pure functions, async machinery adds overhead without benefit. You're paying for coordination of "waiting" that adds no benefit.
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Comparison between barycentric (triangular) dithering and Knoll’s algorithm using an 8-colour irregular palette. Left to right: barycentric, Knoll.
The spec does not mandate buffer limits for tee(). And to be fair, the spec allows implementations to implement the actual internal mechanisms for tee()and other APIs in any way they see fit so long as the observable normative requirements of the specification are met. But if an implementation chooses to implement tee() in the specific way described by the streams specification, then tee() will come with a built-in memory management issue that is difficult to work around.
The one but not the only