object MonadUtil

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##: Int
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  4. final def asInstanceOf[T0]: T0
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  5. def batchedSequentialTraverse[X, M[_], S](parallelism: PositiveInt, chunkSize: PositiveInt)(xs: Seq[X])(processChunk: (Seq[X]) => M[Seq[S]])(implicit M: Parallel[M]): M[Seq[S]]

    Batched version of sequential traverse

    Batched version of sequential traverse

    Can be used to avoid overloading the database queue. Use e.g. maxDbConnections * 2 as parameter for parallelism to not overload the database queue but to make sufficient use of the existing resources.

  6. def batchedSequentialTraverse_[X, M[_]](parallelism: PositiveInt, chunkSize: PositiveInt)(xs: Seq[X])(processChunk: (Seq[X]) => M[Unit])(implicit M: Parallel[M]): M[Unit]
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  8. final def eq(arg0: AnyRef): Boolean
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  10. def foldLeftM[M[_], S, A](initialState: S, xs: Iterable[A])(step: (S, A) => M[S])(implicit monad: Monad[M]): M[S]
  11. def foldLeftM[M[_], S, A](initialState: S, iter: Iterator[A])(step: (S, A) => M[S])(implicit monad: Monad[M]): M[S]

    The caller must ensure that the underlying data structure of the iterator is immutable

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  17. final def notifyAll(): Unit
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  18. def parTraverseWithLimit[X, M[_], S](parallelism: Int)(xs: Seq[X])(processElement: (X) => M[S])(implicit M: Parallel[M]): M[Seq[S]]

    Parallel traverse with limited parallelism

  19. def parTraverseWithLimit_[X, M[_], S](parallelism: Int)(xs: Seq[X])(processElement: (X) => M[S])(implicit M: Parallel[M]): M[Unit]
  20. def repeatFlatmap[M[_], A](m: M[A], f: (A) => M[A], counter: Int)(implicit monad: Monad[M]): M[A]

    Repeatedly apply the same function to a monadic value m.

    Repeatedly apply the same function to a monadic value m. This can be used to retry until the limit counter is reached or the monad m aborts.

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  21. def sequentialTraverse[X, M[_], S](xs: Seq[X])(f: (X) => M[S])(implicit monad: Monad[M]): M[Seq[S]]
  22. def sequentialTraverseMonoid[M[_], A, B](xs: Iterator[A])(step: (A) => M[B])(implicit monad: Monad[M], monoid: Monoid[B]): M[B]

    Conceptually equivalent to sequentialTraverse(xs)(step).map(monoid.combineAll).

  23. def sequentialTraverseMonoid[M[_], A, B](xs: Iterable[A])(step: (A) => M[B])(implicit monad: Monad[M], monoid: Monoid[B]): M[B]

    Conceptually equivalent to sequentialTraverse(xs)(step).map(monoid.combineAll).

  24. def sequentialTraverse_[M[_], A](xs: Iterator[A])(step: (A) => M[_])(implicit monad: Monad[M]): M[Unit]

    The caller must ensure that the underlying data structure of the iterator is immutable

    The caller must ensure that the underlying data structure of the iterator is immutable

    Do not use Cats' .traverse_ methods as Cats does not specify whether the step runs sequentially or in parallel for future-like monads. In fact, this behaviour differs for different versions of Cats.

  25. def sequentialTraverse_[M[_], A](xs: Iterable[A])(step: (A) => M[_])(implicit monad: Monad[M]): M[Unit]

    The implementation of traverse in cats is parallel, so this provides a sequential alternative.

    The implementation of traverse in cats is parallel, so this provides a sequential alternative. The caller must ensure that the Iterable is immutable

    Do not use Cats' .traverse_ methods as Cats does not specify whether the step runs sequentially or in parallel for future-like monads. In fact, this behaviour differs for different versions of Cats.

  26. final def synchronized[T0](arg0: => T0): T0
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  28. final def wait(arg0: Long, arg1: Int): Unit
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  29. final def wait(arg0: Long): Unit
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  30. final def wait(): Unit
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