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quasar.main

Prettify

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object Prettify

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Type Members

  1. sealed abstract class Aligned[A] extends AnyRef

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  2. final case class FieldSeg(name: slamdata.Predef.String) extends Segment with Product with Serializable

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  3. final case class IndexSeg(index: slamdata.Predef.Int) extends Segment with Product with Serializable

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  4. final case class Path(segs: slamdata.Predef.List[Segment]) extends Product with Serializable

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  5. sealed abstract class Segment extends slamdata.Predef.Product with slamdata.Predef.Serializable

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Value Members

  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. object Aligned

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  5. object Path extends Serializable

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  8. def columnNames(rows: slamdata.Predef.List[Data]): slamdata.Predef.List[Path]

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  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. def flatten(data: Data): slamdata.Predef.ListMap[Path, Data]

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  13. final def getClass(): Class[_]

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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  16. final def ne(arg0: AnyRef): Boolean

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def parse(str: slamdata.Predef.String): slamdata.Predef.Option[Data]

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  20. def render(data: Data): Aligned[slamdata.Predef.String]

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    Render any atomic Data value to a String that should either be left-aligned (Str values), or right-aligned (all others).

  21. def renderStream[F[_]](src: Process[F, Data], n: Refined[slamdata.Predef.Int, Positive]): Process[F, slamdata.Predef.List[slamdata.Predef.String]]

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    Render an unbounded series of values to a series of rows, all with the same columns, which are discovered by pre-processing the first n (>= 1) values.

    Render an unbounded series of values to a series of rows, all with the same columns, which are discovered by pre-processing the first n (>= 1) values. That means we never have more than n values in memory, and for the common case where all values have the same fields, a small value of n (even 1) is sufficient. However, if elements contain variable-length arrays/sets and/or objects with varying fields, then values are more likely to be omitted.

    • The first row is the names of the columns, based on the first n values.
    • Each row contains the "pretty" String values for each of the corresponding fields, if present.
    • If new fields appear after the first n rows, they're ignored.
  22. def renderTable(rows: slamdata.Predef.List[Data]): slamdata.Predef.List[slamdata.Predef.String]

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    Render a list of non-atomic values to a table:

    Render a list of non-atomic values to a table:

    • Str values are left-aligned; all other values are right-aligned
    • There is a column for every field/index, at any depth, that appears in any value.
    • The table is formatted as in GitHub-flavored MarkDown.
  23. def renderValues(src: slamdata.Predef.List[Data]): slamdata.Predef.List[slamdata.Predef.List[slamdata.Predef.String]]

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    Pure version of renderStream.

  24. final def synchronized[T0](arg0: ⇒ T0): T0

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  25. def toString(): String

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  26. def unflatten(values: slamdata.Predef.ListMap[Path, Data]): Data

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  27. final def wait(): Unit

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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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