Trait

vegas.DSL

DataDSL

Related Doc: package DSL

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trait DataDSL[T] extends AnyRef

T

the base builder type. Needs to be generic since this can be mixed into different places

Self Type
DataDSL[T] with T
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Abstract Value Members

  1. abstract def _data: Lens[T, Option[Data]]

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    protected[this]

Concrete 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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. def toString(): String

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  17. final def wait(): Unit

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  18. final def wait(arg0: Long, arg1: Int): Unit

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  19. final def wait(arg0: Long): Unit

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  20. def withCaseClasses(values: Seq[Product])(implicit vt: ValueTransformer): T

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    Specifies data as a Seq of case-classes.

    Specifies data as a Seq of case-classes. Each field within the case class becomes a row within the data. And each column is named after the field names within the case class.

  21. def withData(values: Seq[Map[String, Any]])(implicit vt: ValueTransformer): T

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    Specifies data as a Seq of rows, where each row is specified using a Map of column -> value pairs.

    Specifies data as a Seq of rows, where each row is specified using a Map of column -> value pairs.

    values

    A Seq of Maps, with each Map specifying the column -> value pairs of a row.

  22. def withSeqValues(values: Seq[Seq[Any]])(implicit vt: ValueTransformer): T

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    Specifies data as a Seq of Seq data (i.e Array(Array(1,2,3), Array(4,5,6)), where each inner Seq represents a row of data.

    Specifies data as a Seq of Seq data (i.e Array(Array(1,2,3), Array(4,5,6)), where each inner Seq represents a row of data. Column names within the rows are named after their array indexes (0 based). So, for example, to encode this data you'd write:

    encodeX("0", Quant). encodeY("1", Quant). encodeSize("2", Ord).

    values

    A Seq[Seq[Any]] where each inner sequence is treated as a row of data.

  23. def withURL(url: String, formatType: OptArg[DataFormatType] = NoArg): T

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    Uses data from an external source as specified by the given URL.

    Uses data from an external source as specified by the given URL.

    url

    The URL for the external data source.

    formatType

    The type of the data (i.e. DataFormat.Json, DataFormat.Csv, etc).

  24. def withValues(values: Seq[Any])(implicit vt: ValueTransformer): T

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    Specifies data as a Seq of values (i.e.

    Specifies data as a Seq of values (i.e. Array(1.2, 4.2, 5,6)). The array indices are used to create a column "x", and the array's values to create a column "y". To encode this data you'd use:

    encodeX("x", Ordinal) encodeX("y", ...)

    values

    A Seq[Any] containing the values to use.

  25. def withXY(values: Seq[(Any, Any)])(implicit vt: ValueTransformer): T

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    Specifies data as a Seq of x,y values represented by the tuple (Any, Any).

    Specifies data as a Seq of x,y values represented by the tuple (Any, Any). Each column is named "x", "y". To encode the data you'd use:

    encodeX("x", ...). encodeY("y", ...)

    values

    A Seq of (Any, Any) tuples

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