Packages

class MLStoreFunction[A] extends AnyRef

A compiled ML function specifically transmitting values from Scala to Isabelle.

The function is created by val f = MLStoreFunction(ml) where ml is ML code of type data -> a, and a is the ML type corresponding to A.

When f(data) is invoked in Scala (with data of type Data), the compiled ML function ml is applied to data (in the Isabelle process), and the resulting value is stored in the object store, and an MLValue containing the ID is returned.

An MLStoreFunction is particularly useful for writing store methods when writing an MLValue.Converter.

The behavior of an MLStoreFunction[A] is very similar to an MLFunction[Data,A] but more efficient. And the MLStoreFunction additionally does not access the store and retrieve functions of the converter that is passed as an implicit argument. This is important because we use the MLStoreFunction for writing those functions in the first place.

Source
MLValue.scala
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  1. final def !=(arg0: Any): Boolean
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  2. final def ##: Int
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  3. final def ==(arg0: Any): Boolean
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  4. def apply(data: Future[Data])(implicit isabelle: Isabelle, ec: ExecutionContext): MLValue[A]

    Like apply(Data) but data can be a future.

    Like apply(Data) but data can be a future. The returned MLValue mlVal will then internally contain that future (i.e., for example mlVal.retrieveNow will wait for data to complete first).

  5. def apply(data: Data)(implicit isabelle: Isabelle, ec: ExecutionContext): MLValue[A]

    Calls the compile ML function on data in the Isabelle process and returns an MLValue containing the result of that function.

  6. final def asInstanceOf[T0]: T0
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  7. def clone(): AnyRef
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  12. val id: Future[ID]
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  14. final def ne(arg0: AnyRef): Boolean
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  15. final def notify(): Unit
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  16. final def notifyAll(): Unit
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  17. final def synchronized[T0](arg0: => T0): T0
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  19. final def wait(arg0: Long, arg1: Int): Unit
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  20. final def wait(arg0: Long): Unit
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  21. final def wait(): Unit
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  1. def finalize(): Unit
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