Type Members

1.  case class ::[+A](head: A, next: List[A]) extends List[A] with Product with Serializable

   Annotations

   @SerialVersionUID()

2.  abstract class AbstractMap[K, +V] extends collection.AbstractMap[K, V] with Map[K, V]

   Explicit instantiation of the Map trait to reduce class file size in subclasses.

3.  abstract class AbstractSeq[+A] extends collection.AbstractSeq[A] with Seq[A]

   Explicit instantiation of the Seq trait to reduce class file size in subclasses.

4.  abstract class AbstractSet[A] extends collection.AbstractSet[A] with Set[A]

   Explicit instantiation of the Set trait to reduce class file size in subclasses.

5.  sealed abstract class ArraySeq[+A] extends AbstractSeq[A] with IndexedSeq[A] with IndexedSeqOps[A, ArraySeq, ArraySeq[A]] with StrictOptimizedSeqOps[A, ArraySeq, ArraySeq[A]]

   An immutable array.

   An immutable array.

   Supports efficient indexed access and has a small memory footprint.

6.  sealed abstract class BitSet extends AbstractSet[Int] with SortedSet[Int] with collection.BitSet with SortedSetOps[Int, SortedSet, BitSet] with BitSetOps[BitSet] with StrictOptimizedIterableOps[Int, Set, BitSet] with Serializable

   A class for immutable bitsets.

   A class for immutable bitsets.

   Bitsets are sets of non-negative integers which are represented as variable-size arrays of bits packed into 64-bit words. The memory footprint of a bitset is determined by the largest number stored in it.

   Annotations

   @SerialVersionUID()

   See also

   "Scala's Collection Library overview" section on Immutable BitSets for more information.

7.  final class ChampHashMap[K, +V] extends AbstractMap[K, V] with MapOps[K, V, ChampHashMap, ChampHashMap[K, V]] with StrictOptimizedIterableOps[(K, V), Iterable, ChampHashMap[K, V]] with Serializable

   This class implements immutable maps using a Compressed Hash-Array Mapped Prefix-tree.

   This class implements immutable maps using a Compressed Hash-Array Mapped Prefix-tree. See paper https://michael.steindorfer.name/publications/oopsla15.pdf for more details.

   K

   the type of the keys contained in this hash set.

   V

   the type of the values associated with the keys in this hash map.

   Annotations

   @SerialVersionUID()

   Version

   2.13

   Since

   2.13

8.  final class ChampHashSet[A] extends AbstractSet[A] with SetOps[A, ChampHashSet, ChampHashSet[A]] with StrictOptimizedIterableOps[A, ChampHashSet, ChampHashSet[A]] with Serializable

   This class implements immutable sets using a Compressed Hash-Array Mapped Prefix-tree.

   This class implements immutable sets using a Compressed Hash-Array Mapped Prefix-tree. See paper https://michael.steindorfer.name/publications/oopsla15.pdf for more details.

   A

   the type of the elements contained in this hash set.

   Annotations

   @SerialVersionUID()

   Version

   2.13

   Since

   2.13

9.  sealed abstract class HashMap[K, +V] extends AbstractMap[K, V] with MapOps[K, V, HashMap, HashMap[K, V]] with StrictOptimizedIterableOps[(K, V), Iterable, HashMap[K, V]] with Serializable

   This class implements immutable maps using a hash trie.

   This class implements immutable maps using a hash trie.

   Note: The builder of this hash map may return specialized representations for small maps.

   K

   the type of the keys contained in this hash map.

   V

   the type of the values associated with the keys.

   Annotations

   @SerialVersionUID()

   Version

   2.8

   Since

   2.3

   See also

   "Scala's Collection Library overview" section on Hash Tries for more information.

10.  sealed abstract class HashSet[A] extends AbstractSet[A] with SetOps[A, HashSet, HashSet[A]] with StrictOptimizedIterableOps[A, HashSet, HashSet[A]] with Serializable

    This class implements immutable sets using a hash trie.

    This class implements immutable sets using a hash trie.

    Note: The builder of this hash set may return specialized representations for small sets.

    A

    the type of the elements contained in this hash set.

    Annotations

    @SerialVersionUID()

    Version

    2.8

    Since

    2.3

11.  trait IndexedSeq[+A] extends Seq[A] with collection.IndexedSeq[A] with IndexedSeqOps[A, IndexedSeq, IndexedSeq[A]]

    Base trait for immutable indexed sequences that have efficient apply and length

12.  trait IndexedSeqOps[+A, +CC[_], +C] extends SeqOps[A, CC, C] with collection.IndexedSeqOps[A, CC, C]

    Base trait for immutable indexed Seq operations

13.  sealed abstract class IntMap[+T] extends AbstractMap[immutable.IntMapUtils.Int, T] with MapOps[immutable.IntMapUtils.Int, T, Map, IntMap[T]] with StrictOptimizedIterableOps[(immutable.IntMapUtils.Int, T), Iterable, IntMap[T]] with Serializable

    Specialised immutable map structure for integer keys, based on Fast Mergeable Integer Maps by Okasaki and Gill.

    Specialised immutable map structure for integer keys, based on Fast Mergeable Integer Maps by Okasaki and Gill. Essentially a trie based on binary digits of the integers.

    Note: This class is as of 2.8 largely superseded by HashMap.

    T

    type of the values associated with integer keys.

    Annotations

    @SerialVersionUID()

    Since

    2.7

14.  trait Iterable[+A] extends collection.Iterable[A] with IterableOps[A, Iterable, Iterable[A]]

    A trait for collections that are guaranteed immutable.

    A trait for collections that are guaranteed immutable.

    A

    the element type of the collection

15.  sealed abstract class LazyList[+A] extends AbstractSeq[A] with LinearSeq[A] with LazyListOps[A, LazyList, LazyList[A]]

    The class LazyList implements lazy lists where elements are only evaluated when they are needed.

    The class LazyList implements lazy lists where elements are only evaluated when they are needed. Here is an example:

    import scala.math.BigInt
    object Main extends App {
    
      lazy val fibs: LazyList[BigInt] = BigInt(0) #:: BigInt(1) #:: fibs.zip(fibs.tail).map { n => n._1 + n._2 }
    
      fibs take 5 foreach println
    }
    
    // prints
    //
    // 0
    // 1
    // 1
    // 2
    // 3

    The LazyList class also employs memoization such that previously computed values are converted from LazyList elements to concrete values of type A. To illustrate, we will alter body of the fibs value above and take some more values:

    import scala.math.BigInt
    object Main extends App {
    
      lazy val fibs: LazyList[BigInt] = BigInt(0) #:: BigInt(1) #:: fibs.zip(
        fibs.tail).map(n => {
          println("Adding %d and %d".format(n._1, n._2))
          n._1 + n._2
        })
    
      fibs take 5 foreach println
      fibs take 6 foreach println
    }
    
    // prints
    //
    // 0
    // 1
    // Adding 0 and 1
    // 1
    // Adding 1 and 1
    // 2
    // Adding 1 and 2
    // 3
    
    // And then prints
    //
    // 0
    // 1
    // 1
    // 2
    // 3
    // Adding 2 and 3
    // 5

    There are a number of subtle points to the above example.

    • The definition of fibs is a val not a method. The memoization of the LazyList requires us to have somewhere to store the information and a val allows us to do that.
    • While the LazyList is actually being modified during access, this does not change the notion of its immutability. Once the values are memoized they do not change and values that have yet to be memoized still "exist", they simply haven't been realized yet.
    • One must be cautious of memoization; you can very quickly eat up large amounts of memory if you're not careful. The reason for this is that the memoization of the LazyList creates a structure much like scala.collection.immutable.List. So long as something is holding on to the head, the head holds on to the tail, and so it continues recursively. If, on the other hand, there is nothing holding on to the head (e.g. we used def to define the LazyList) then once it is no longer being used directly, it disappears.
    • Note that some operations, including drop, dropWhile, flatMap or collect may process a large number of intermediate elements before returning. These necessarily hold onto the head, since they are methods on LazyList, and a lazy list holds its own head. For computations of this sort where memoization is not desired, use Iterator when possible.

    // For example, let's build the natural numbers and do some silly iteration
    // over them.
    
    // We'll start with a silly iteration
    def loop(s: String, i: Int, iter: Iterator[Int]): Unit = {
      // Stop after 200,000
      if (i < 200001) {
        if (i % 50000 == 0) println(s + i)
        loop(s, iter.next(), iter)
      }
    }
    
    // Our first LazyList definition will be a val definition
    val lazylist1: LazyList[Int] = {
      def loop(v: Int): LazyList[Int] = v #:: loop(v + 1)
      loop(0)
    }
    
    // Because lazylist1 is a val, everything that the iterator produces is held
    // by virtue of the fact that the head of the LazyList is held in lazylist1
    val it1 = lazylist1.iterator
    loop("Iterator1: ", it1.next(), it1)
    
    // We can redefine this LazyList such that all we have is the Iterator left
    // and allow the LazyList to be garbage collected as required.  Using a def
    // to provide the LazyList ensures that no val is holding onto the head as
    // is the case with lazylist1
    def lazylist2: LazyList[Int] = {
      def loop(v: Int): LazyList[Int] = v #:: loop(v + 1)
      loop(0)
    }
    val it2 = stream2.iterator
    loop("Iterator2: ", it2.next(), it2)
    
    // And, of course, we don't actually need a LazyList at all for such a simple
    // problem.  There's no reason to use a LazyList if you don't actually need
    // one.
    val it3 = new Iterator[Int] {
      var i = -1
      def hasNext = true
      def next(): Int = { i += 1; i }
    }
    loop("Iterator3: ", it3.next(), it3)

    • The fact that tail works at all is of interest. In the definition of fibs we have an initial (0, 1, LazyList(...)) so tail is deterministic. If we defined fibs such that only 0 were concretely known then the act of determining tail would require the evaluation of tail which would cause an infinite recursion and stack overflow. If we define a definition where the tail is not initially computable then we're going to have an infinite recursion:

    // The first time we try to access the tail we're going to need more
    // information which will require us to recurse, which will require us to
    // recurse, which...
    lazy val sov: LazyList[Vector[Int]] = Vector(0) #:: sov.zip(sov.tail).map { n => n._1 ++ n._2 }

    The definition of fibs above creates a larger number of objects than necessary depending on how you might want to implement it. The following implementation provides a more "cost effective" implementation due to the fact that it has a more direct route to the numbers themselves:

    lazy val fib: LazyList[Int] = {
      def loop(h: Int, n: Int): LazyList[Int] = h #:: loop(n, h + n)
      loop(1, 1)
    }

    A

    the type of the elements contained in this stream.

    Version

    1.1 08/08/03

    Since

    2.8

    See also

    "Scala's Collection Library overview" section on Streams for more information.

16.  trait LinearSeq[+A] extends Seq[A] with collection.LinearSeq[A] with LinearSeqOps[A, LinearSeq, LinearSeq[A]]

    Base trait for immutable linear sequences that have efficient head and tail

17.  trait LinearSeqOps[+A, +CC[X] <: LinearSeq[X], +C <: LinearSeq[A] with LinearSeqOps[A, CC, C]] extends SeqOps[A, CC, C] with collection.LinearSeqOps[A, CC, C]
18.  sealed abstract class List[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, List, List[A]] with StrictOptimizedSeqOps[A, List, List[A]] with Serializable

    A class for immutable linked lists representing ordered collections of elements of type A.

    A class for immutable linked lists representing ordered collections of elements of type A.

    This class comes with two implementing case classes scala.Nil and scala.:: that implement the abstract members isEmpty, head and tail.

    This class is optimal for last-in-first-out (LIFO), stack-like access patterns. If you need another access pattern, for example, random access or FIFO, consider using a collection more suited to this than List.

    Note: Despite being an immutable collection, the implementation uses mutable state internally during construction. These state changes are invisible in single-threaded code but can lead to race conditions in some multi-threaded scenarios. The state of a new collection instance may not have been "published" (in the sense of the Java Memory Model specification), so that an unsynchronized non-volatile read from another thread may observe the object in an invalid state (see scala/bug#7838 for details). Note that such a read is not guaranteed to ever see the written object at all, and should therefore not be used, regardless of this issue. The easiest workaround is to exchange values between threads through a volatile var.

    Performance

    Time: List has O(1) prepend and head/tail access. Most other operations are O(n) on the number of elements in the list. This includes the index-based lookup of elements, length, append and reverse.

    Space: List implements structural sharing of the tail list. This means that many operations are either zero- or constant-memory cost.

    val mainList = List(3, 2, 1)
    val with4 =    4 :: mainList  // re-uses mainList, costs one :: instance
    val with42 =   42 :: mainList // also re-uses mainList, cost one :: instance
    val shorter =  mainList.tail  // costs nothing as it uses the same 2::1::Nil instances as mainList

    Annotations

    @SerialVersionUID()

    Example:

    1. // Make a list via the companion object factory
       val days = List("Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday")
       
       // Make a list element-by-element
       val when = "AM" :: "PM" :: Nil
       
       // Pattern match
       days match {
         case firstDay :: otherDays =>
           println("The first day of the week is: " + firstDay)
         case Nil =>
           println("There don't seem to be any week days.")
       }

    Version

    2.8

    Since

    1.0

    Note

    The functional list is characterized by persistence and structural sharing, thus offering considerable performance and space consumption benefits in some scenarios if used correctly. However, note that objects having multiple references into the same functional list (that is, objects that rely on structural sharing), will be serialized and deserialized with multiple lists, one for each reference to it. I.e. structural sharing is lost after serialization/deserialization.

    See also

    "Scala's Collection Library overview" section on Lists for more information.

19.  sealed class ListMap[K, +V] extends AbstractMap[K, V] with MapOps[K, V, ListMap, ListMap[K, V]] with StrictOptimizedIterableOps[(K, V), Iterable, ListMap[K, V]] with Serializable

    This class implements immutable maps using a list-based data structure.

    This class implements immutable maps using a list-based data structure. List map iterators and traversal methods visit key-value pairs in the order whey were first inserted.

    Entries are stored internally in reversed insertion order, which means the newest key is at the head of the list. As such, methods such as head and tail are O(n), while last and init are O(1). Other operations, such as inserting or removing entries, are also O(n), which makes this collection suitable only for a small number of elements.

    Instances of ListMap represent empty maps; they can be either created by calling the constructor directly, or by applying the function ListMap.empty.

    K

    the type of the keys contained in this list map

    V

    the type of the values associated with the keys

    Annotations

    @SerialVersionUID()

    Version

    2.0, 01/01/2007

    Since

    1

20.  sealed class ListSet[A] extends AbstractSet[A] with SetOps[A, ListSet, ListSet[A]] with StrictOptimizedIterableOps[A, ListSet, ListSet[A]] with Serializable

    This class implements immutable sets using a list-based data structure.

    This class implements immutable sets using a list-based data structure. List set iterators and traversal methods visit elements in the order whey were first inserted.

    Elements are stored internally in reversed insertion order, which means the newest element is at the head of the list. As such, methods such as head and tail are O(n), while last and init are O(1). Other operations, such as inserting or removing entries, are also O(n), which makes this collection suitable only for a small number of elements.

    Instances of ListSet represent empty sets; they can be either created by calling the constructor directly, or by applying the function ListSet.empty.

    A

    the type of the elements contained in this list set

    Annotations

    @SerialVersionUID()

    Version

    1.0, 09/07/2003

    Since

    1

21.  sealed abstract class LongMap[+T] extends AbstractMap[immutable.LongMapUtils.Long, T] with MapOps[immutable.LongMapUtils.Long, T, Map, LongMap[T]] with StrictOptimizedIterableOps[(immutable.LongMapUtils.Long, T), Iterable, LongMap[T]] with Serializable

    Specialised immutable map structure for long keys, based on Fast Mergeable Long Maps by Okasaki and Gill.

    Specialised immutable map structure for long keys, based on Fast Mergeable Long Maps by Okasaki and Gill. Essentially a trie based on binary digits of the integers.

    Note: This class is as of 2.8 largely superseded by HashMap.

    T

    type of the values associated with the long keys.

    Annotations

    @SerialVersionUID()

    Since

    2.7

22.  trait Map[K, +V] extends Iterable[(K, V)] with collection.Map[K, V] with MapOps[K, V, Map, Map[K, V]]

    Base type of immutable Maps

23.  trait MapOps[K, +V, +CC[X, +Y] <: MapOps[X, Y, CC, _], +C <: MapOps[K, V, CC, C]] extends IterableOps[(K, V), Iterable, C] with collection.MapOps[K, V, CC, C]

    Base trait of immutable Maps implementations

24.  sealed class NumericRange[T] extends AbstractSeq[T] with IndexedSeq[T] with IndexedSeqOps[T, IndexedSeq, IndexedSeq[T]] with StrictOptimizedSeqOps[T, IndexedSeq, IndexedSeq[T]] with Serializable

    NumericRange is a more generic version of the Range class which works with arbitrary types.

    NumericRange is a more generic version of the Range class which works with arbitrary types. It must be supplied with an Integral implementation of the range type.

    Factories for likely types include Range.BigInt, Range.Long, and Range.BigDecimal. Range.Int exists for completeness, but the Int-based scala.Range should be more performant.

    val r1 = new Range(0, 100, 1)
    val veryBig = Int.MaxValue.toLong + 1
    val r2 = Range.Long(veryBig, veryBig + 100, 1)
    assert(r1 sameElements r2.map(_ - veryBig))

    Annotations

    @SerialVersionUID()

25.  sealed class Queue[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, Queue, Queue[A]] with StrictOptimizedSeqOps[A, Queue, Queue[A]] with Serializable

    Queue objects implement data structures that allow to insert and retrieve elements in a first-in-first-out (FIFO) manner.

    Queue objects implement data structures that allow to insert and retrieve elements in a first-in-first-out (FIFO) manner.

    Queue is implemented as a pair of Lists, one containing the in elements and the other the out elements. Elements are added to the in list and removed from the out list. When the out list runs dry, the queue is pivoted by replacing the out list by in.reverse, and in by Nil.

    Adding items to the queue always has cost O(1). Removing items has cost O(1), except in the case where a pivot is required, in which case, a cost of O(n) is incurred, where n is the number of elements in the queue. When this happens, n remove operations with O(1) cost are guaranteed. Removing an item is on average O(1).

    Annotations

    @SerialVersionUID()

    Version

    1.0, 08/07/2003

    Since

    1

    See also

    "Scala's Collection Library overview" section on Immutable Queues for more information.

26.  sealed abstract class Range extends AbstractSeq[Int] with IndexedSeq[Int] with IndexedSeqOps[Int, IndexedSeq, IndexedSeq[Int]] with StrictOptimizedSeqOps[Int, IndexedSeq, IndexedSeq[Int]] with Serializable

    The Range class represents integer values in range [start;end) with non-zero step value step.

    The Range class represents integer values in range [start;end) with non-zero step value step. It's a special case of an indexed sequence. For example:

    val r1 = 0 until 10
    val r2 = r1.start until r1.end by r1.step + 1
    println(r2.length) // = 5

    Ranges that contain more than Int.MaxValue elements can be created, but these overfull ranges have only limited capabilities. Any method that could require a collection of over Int.MaxValue length to be created, or could be asked to index beyond Int.MaxValue elements will throw an exception. Overfull ranges can safely be reduced in size by changing the step size (e.g. by 3) or taking/dropping elements. contains, equals, and access to the ends of the range (head, last, tail, init) are also permitted on overfull ranges.

    Annotations

    @SerialVersionUID()

27.  trait Seq[+A] extends Iterable[A] with collection.Seq[A] with SeqOps[A, Seq, Seq[A]]
28.  trait SeqOps[+A, +CC[_], +C] extends collection.SeqOps[A, CC, C]

29.  trait Set[A] extends Iterable[A] with collection.Set[A] with SetOps[A, Set, Set[A]]

    Base trait for immutable set collections

30.  trait SetOps[A, +CC[X], +C <: SetOps[A, CC, C]] extends collection.SetOps[A, CC, C]

    Base trait for immutable set operations

31.  trait SortedMap[K, +V] extends Map[K, V] with collection.SortedMap[K, V] with SortedMapOps[K, V, SortedMap, SortedMap[K, V]]
32.  trait SortedMapOps[K, +V, +CC[X, +Y] <: Map[X, Y] with SortedMapOps[X, Y, CC, _], +C <: SortedMapOps[K, V, CC, C]] extends MapOps[K, V, Map, C] with collection.SortedMapOps[K, V, CC, C]
33.  trait SortedSet[A] extends Set[A] with collection.SortedSet[A] with SortedSetOps[A, SortedSet, SortedSet[A]]

    Base trait for sorted sets

34.  trait SortedSetOps[A, +CC[X] <: SortedSet[X], +C <: SortedSetOps[A, CC, C]] extends SetOps[A, Set, C] with collection.SortedSetOps[A, CC, C]

35.  trait StrictOptimizedSeqOps[+A, +CC[_], +C] extends SeqOps[A, CC, C] with collection.StrictOptimizedSeqOps[A, CC, C]

    Trait that overrides operations to take advantage of strict builders.

36.  type StringOps = collection.StringOps
37.  type StringView = collection.StringView
38.  final class TreeMap[K, +V] extends AbstractMap[K, V] with SortedMap[K, V] with SortedMapOps[K, V, TreeMap, TreeMap[K, V]] with StrictOptimizedIterableOps[(K, V), Iterable, TreeMap[K, V]] with Serializable

    This class implements immutable maps using a tree.

    This class implements immutable maps using a tree.

    K

    the type of the keys contained in this tree map.

    V

    the type of the values associated with the keys.

    Annotations

    @SerialVersionUID()

    Version

    1.1, 03/05/2004

    Since

    1

    See also

    "Scala's Collection Library overview" section on Red-Black Trees for more information.

39.  final class TreeSet[A] extends AbstractSet[A] with SortedSet[A] with SortedSetOps[A, TreeSet, TreeSet[A]] with StrictOptimizedIterableOps[A, Set, TreeSet[A]] with StrictOptimizedSortedSetOps[A, TreeSet, TreeSet[A]] with Serializable

    This class implements immutable sorted sets using a tree.

    This class implements immutable sorted sets using a tree.

    A

    the type of the elements contained in this tree set

    Annotations

    @SerialVersionUID()

    Version

    2.0, 02/01/2007

    Since

    1

    See also

    "Scala's Collection Library overview" section on Red-Black Trees for more information.

40.  final class Vector[+A] extends AbstractSeq[A] with IndexedSeq[A] with IndexedSeqOps[A, Vector, Vector[A]] with StrictOptimizedSeqOps[A, Vector, Vector[A]] with VectorPointer[A] with Serializable

    Vector is a general-purpose, immutable data structure.

    Vector is a general-purpose, immutable data structure. It provides random access and updates in effectively constant time, as well as very fast append and prepend. Because vectors strike a good balance between fast random selections and fast random functional updates, they are currently the default implementation of immutable indexed sequences. It is backed by a little endian bit-mapped vector trie with a branching factor of 32. Locality is very good, but not contiguous, which is good for very large sequences.

    Note: Despite being an immutable collection, the implementation uses mutable state internally during construction. These state changes are invisible in single-threaded code but can lead to race conditions in some multi-threaded scenarios. The state of a new collection instance may not have been "published" (in the sense of the Java Memory Model specification), so that an unsynchronized non-volatile read from another thread may observe the object in an invalid state (see scala/bug#7838 for details). Note that such a read is not guaranteed to ever see the written object at all, and should therefore not be used, regardless of this issue. The easiest workaround is to exchange values between threads through a volatile var.

    A

    the element type

    Annotations

    @SerialVersionUID()

    See also

    "Scala's Collection Library overview" section on Vectors for more information.

41.  final class VectorBuilder[A] extends ReusableBuilder[A, Vector[A]] with VectorPointer[A]

    A class to build instances of Vector.

    A class to build instances of Vector. This builder is reusable.

42.  class VectorIterator[+A] extends AbstractIterator[A] with VectorPointer[A]
43.  final class WrappedString extends AbstractSeq[Char] with IndexedSeq[Char] with IndexedSeqOps[Char, IndexedSeq, WrappedString]

    This class serves as a wrapper augmenting Strings with all the operations found in indexed sequences.

    This class serves as a wrapper augmenting Strings with all the operations found in indexed sequences.

    The difference between this class and StringOps is that calling transformer methods such as filter and map will yield an object of type WrappedString rather than a String.

    Since

    2.8

44.  sealed abstract class Stream[+A] extends AbstractSeq[A] with LinearSeq[A] with LazyListOps[A, Stream, Stream[A]]

    Annotations

    @deprecated

    Deprecated

    (Since version 2.13.0) Use LazyList (which has a lazy head and tail) instead of Stream (which has a lazy tail only)

45.  type Traversable[+X] = Iterable[X]

    Annotations

    @deprecated

    Deprecated

    (Since version 2.13.0) Use Iterable instead of Traversable