Add various streaming transducers #282
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satabin
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| for { | ||
| acc <- loop(left, acc) | ||
| acc <- loop(right, acc) | ||
| } yield acc |
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| for { | |
| acc <- loop(left, acc) | |
| acc <- loop(right, acc) | |
| } yield acc | |
| loop(left, acc).flatMap(loop(right, _)) |
I find the for-comprehension with re-use of acc unnecessarily hard to read and it has the tail map problem on Scala 3 IIRC.
| m.lift(from) | ||
| } | ||
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| implicit object MapTable extends Table[Map] { |
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Map <: MapOps <: PartialFunction, so we might run into ambiguous implicit here. Maybe move the partial function instance into a low priority trait to be safe?
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Not entirely sure what it does without docs, but left some small Scala-specific comments and will stay tuned for updates smile
Documentation will come. This is a first basic building block for higher-level features. More transducers to come soon, I hope, especially SSTs, which will allow for parsing. This STT can be the base for streaming query languages on tree structures.
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I decided to merge this PR without support for SST because:
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The copyless natures is ensured by using a controlled environment update language, without losing expressiveness. This execution model emits as soon as possible, and requires transducers to be total, otherwise the stream fails. This also ensures that everything is emitted up to the first error. The STT model can be used to implement query languages on tree structures and some transformations.
By abstracting the transition table type with a dedicated typeclass, one can create symbolic transducers, which can come in handy to handle infinite input alphabets.
The streaming FST are simulated and try to emit as early as possible when there is no ambiguity.
This index can be used to implement efficient lookup table in later use.
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Streaming String Transducers which can be used for matching inputs and emitting some output as soon as possible