scala.collection.immutable

Type members

Classlikes

final case class ::[+A](head: A, var next: List[A]) extends List[A]
Source:
List.scala
abstract class AbstractMap[K, +V] extends AbstractMap[K, V] with Map[K, V]

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

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

Source:
Map.scala
abstract class AbstractSeq[+A] extends AbstractSeq[A] with Seq[A]

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

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

Source:
Seq.scala
abstract class AbstractSet[A] extends AbstractSet[A] with Set[A]

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

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

Source:
Set.scala
sealed abstract class ArraySeq[+A] extends AbstractSeq[A] with IndexedSeq[A] with IndexedSeqOps[A, [A] =>> ArraySeq[A], ArraySeq[A]] with StrictOptimizedSeqOps[A, [A] =>> ArraySeq[A], ArraySeq[A]] with EvidenceIterableFactoryDefaults[A, [A] =>> ArraySeq[A], [T] =>> ClassTag[T]] with Serializable

An immutable array.

An immutable array.

Supports efficient indexed access and has a small memory footprint.

Companion:
object
Source:
ArraySeq.scala

This object provides a set of operations to create ArraySeq values.

This object provides a set of operations to create ArraySeq values.

Companion:
class
Source:
ArraySeq.scala
sealed abstract class BitSet extends AbstractSet[Int] with SortedSet[Int] with SortedSetOps[Int, [A] =>> SortedSet[A], BitSet] with StrictOptimizedSortedSetOps[Int, [A] =>> SortedSet[A], BitSet] with BitSet with BitSetOps[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 lower bound of memory footprint of a bitset is determined by the largest number stored in it.

See also:

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

Companion:
object
Source:
BitSet.scala
@nowarn("cat=deprecation&msg=Implementation classes of BitSet should not be accessed directly") @SerialVersionUID(3L)

This object provides a set of operations to create immutable.BitSet values.

This object provides a set of operations to create immutable.BitSet values.

Companion:
class
Source:
BitSet.scala
final class HashMap[K, +V] extends AbstractMap[K, V] with StrictOptimizedMapOps[K, V, [K, V] =>> HashMap[K, V], HashMap[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> HashMap[K, V], [A] =>> Iterable[A]] with DefaultSerializable

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.

Type parameters:
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.

Companion:
object
Source:
HashMap.scala
object HashMap extends MapFactory[[K, V] =>> HashMap[K, V]]

This object provides a set of operations to create immutable.HashMap values.

This object provides a set of operations to create immutable.HashMap values.

Companion:
class
Source:
HashMap.scala
final class HashSet[A] extends AbstractSet[A] with StrictOptimizedSetOps[A, [A] =>> HashSet[A], HashSet[A]] with IterableFactoryDefaults[A, [A] =>> HashSet[A]] with DefaultSerializable

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.

Type parameters:
A

the type of the elements contained in this hash set.

Companion:
object
Source:
HashSet.scala
object HashSet extends IterableFactory[[A] =>> HashSet[A]]

This object provides a set of operations to create immutable.HashSet values.

This object provides a set of operations to create immutable.HashSet values.

Companion:
class
Source:
HashSet.scala
trait IndexedSeq[+A] extends Seq[A] with IndexedSeq[A] with IndexedSeqOps[A, [A] =>> IndexedSeq[A], IndexedSeq[A]] with IterableFactoryDefaults[A, [A] =>> IndexedSeq[A]]

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

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

Companion:
object
Source:
Seq.scala
object IndexedSeq extends Delegate[[A] =>> IndexedSeq[A]]
Companion:
class
Source:
Seq.scala
trait IndexedSeqOps[+A, +CC[_], +C] extends SeqOps[A, CC, C] with IndexedSeqOps[A, CC, C]

Base trait for immutable indexed Seq operations

Base trait for immutable indexed Seq operations

Source:
Seq.scala
object IntMap

A companion object for integer maps.

A companion object for integer maps.

Companion:
class
Source:
IntMap.scala
sealed abstract class IntMap[+T] extends AbstractMap[Int, T] with StrictOptimizedMapOps[Int, T, [K, V] =>> Map[K, V], 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.

Type parameters:
T

type of the values associated with integer keys.

Companion:
object
Source:
IntMap.scala
trait Iterable[+A] extends Iterable[A] with IterableOps[A, [A] =>> Iterable[A], Iterable[A]] with IterableFactoryDefaults[A, [A] =>> Iterable[A]]

A trait for collections that are guaranteed immutable.

A trait for collections that are guaranteed immutable.

Type parameters:
A

the element type of the collection

Companion:
object
Source:
Iterable.scala
object Iterable extends Delegate[[A] =>> Iterable[A]]
Companion:
class
Source:
Iterable.scala
final class LazyList[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, [A] =>> LazyList[A], LazyList[A]] with IterableFactoryDefaults[A, [A] =>> LazyList[A]] with Serializable

This class implements an immutable linked list.

This class implements an immutable linked list. We call it "lazy" because it computes its elements only when they are needed.

Elements are memoized; that is, the value of each element is computed at most once.

Elements are computed in-order and are never skipped. In other words, accessing the tail causes the head to be computed first.

How lazy is a LazyList? When you have a value of type LazyList, you don't know yet whether the list is empty or not. If you learn that it is non-empty, then you also know that the head has been computed. But the tail is itself a LazyList, whose emptiness-or-not might remain undetermined.

A LazyList may be infinite. For example, LazyList.from(0) contains all of the natural numbers 0, 1, 2, and so on. For infinite sequences, some methods (such as count, sum, max or min) will not terminate.

Here is an example:

import scala.math.BigInt
object Main extends App {
  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

To illustrate, let's add some output to the definition fibs, so we see what's going on.

import scala.math.BigInt
object Main extends App {
  val fibs: LazyList[BigInt] =
    BigInt(0) #:: BigInt(1) #::
      fibs.zip(fibs.tail).map{ n =>
        println(s"Adding ${n._1} and ${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

Note that the definition of fibs uses val not def. The memoization of the LazyList requires us to have somewhere to store the information and a val allows us to do that.

Further remarks about the semantics of LazyList:

- Though the LazyList changes as it is accessed, this does not contradict its immutability. Once the values are memoized they do not change. Values that have yet to be memoized still "exist", they simply haven't been computed yet.

- One must be cautious of memoization; it can eat up memory if you're not careful. That's because memoization of the LazyList creates a structure much like scala.collection.immutable.List. As long as something is holding on to the head, the head holds on to the tail, and so on recursively. If, on the other hand, there is nothing holding on to the head (e.g. if 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.

Here's another example. Let's start with the natural numbers and iterate 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 = lazylist2.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)

- In the fibs example earlier, the fact that tail works at all is of interest. fibs has 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, so the computation would be unable to progress, as in this code:

// 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)
}

The head, the tail and whether the list is empty or not can be initially unknown. Once any of those are evaluated, they are all known, though if the tail is built with #:: or #:::, it's content still isn't evaluated. Instead, evaluating the tails content is deferred until the tails empty status, head or tail is evaluated.

Delaying the evaluation of whether a LazyList is empty or not until it's needed allows LazyList to not eagerly evaluate any elements on a call to filter.

Only when it's further evaluated (which may be never!) any of the elements gets forced.

for example:

def tailWithSideEffect: LazyList[Nothing] = {
  println("getting empty LazyList")
  LazyList.empty
}

val emptyTail = tailWithSideEffect // prints "getting empty LazyList"

val suspended = 1 #:: tailWithSideEffect // doesn't print anything
val tail = suspended.tail // although the tail is evaluated, *still* nothing is yet printed
val filtered = tail.filter(_ => false) // still nothing is printed
filtered.isEmpty // prints "getting empty LazyList"
Type parameters:
A

the type of the elements contained in this lazy list.

See also:

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

Companion:
object
Source:
LazyList.scala
object LazyList extends SeqFactory[[A] =>> LazyList[A]]

This object provides a set of operations to create LazyList values.

This object provides a set of operations to create LazyList values.

Companion:
class
Source:
LazyList.scala
trait LinearSeq[+A] extends Seq[A] with LinearSeq[A] with LinearSeqOps[A, [A] =>> LinearSeq[A], LinearSeq[A]] with IterableFactoryDefaults[A, [A] =>> LinearSeq[A]]

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

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

Companion:
object
Source:
Seq.scala
object LinearSeq extends Delegate[[A] =>> LinearSeq[A]]
Companion:
class
Source:
Seq.scala
trait LinearSeqOps[+A, +CC <: ([X] =>> LinearSeq[X]), +C <: LinearSeq[A] & LinearSeqOps[A, CC, C]] extends SeqOps[A, CC, C] with LinearSeqOps[A, CC, C]
Source:
Seq.scala
sealed abstract class List[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, [A] =>> List[A], List[A]] with StrictOptimizedLinearSeqOps[A, [A] =>> List[A], List[A]] with StrictOptimizedSeqOps[A, [A] =>> List[A], List[A]] with IterableFactoryDefaults[A, [A] =>> List[A]] with DefaultSerializable

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.

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
See also:

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

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.

Example:

// 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.")
}
Companion:
object
Source:
List.scala
object List extends StrictOptimizedSeqFactory[[A] =>> List[A]]

This object provides a set of operations to create List values.

This object provides a set of operations to create List values.

Companion:
class
Source:
List.scala
sealed class ListMap[K, +V] extends AbstractMap[K, V] with SeqMap[K, V] with StrictOptimizedMapOps[K, V, [K, V] =>> ListMap[K, V], ListMap[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> ListMap[K, V], [A] =>> Iterable[A]] with DefaultSerializable

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 they 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.

Type parameters:
K

the type of the keys contained in this list map

V

the type of the values associated with the keys

Companion:
object
Source:
ListMap.scala
object ListMap extends MapFactory[[K, V] =>> ListMap[K, V]]

This object provides a set of operations to create ListMap values.

This object provides a set of operations to create ListMap values.

Note that each element insertion takes O(n) time, which means that creating a list map with n elements will take O(n2) time. This makes the builder suitable only for a small number of elements.

See also:

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

Companion:
class
Source:
ListMap.scala
sealed class ListSet[A] extends AbstractSet[A] with StrictOptimizedSetOps[A, [A] =>> ListSet[A], ListSet[A]] with IterableFactoryDefaults[A, [A] =>> ListSet[A]] with DefaultSerializable

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 they 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.

Type parameters:
A

the type of the elements contained in this list set

Companion:
object
Source:
ListSet.scala
object ListSet extends IterableFactory[[A] =>> ListSet[A]]

This object provides a set of operations to create ListSet values.

This object provides a set of operations to create ListSet values.

Note that each element insertion takes O(n) time, which means that creating a list set with n elements will take O(n2) time. This makes the builder suitable only for a small number of elements.

Companion:
class
Source:
ListSet.scala
object LongMap

A companion object for long maps.

A companion object for long maps.

Companion:
class
Source:
LongMap.scala
sealed abstract class LongMap[+T] extends AbstractMap[Long, T] with StrictOptimizedMapOps[Long, T, [K, V] =>> Map[K, V], 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.

Type parameters:
T

type of the values associated with the long keys.

Companion:
object
Source:
LongMap.scala
trait Map[K, +V] extends Iterable[(K, V)] with Map[K, V] with MapOps[K, V, [K, V] =>> Map[K, V], Map[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> Map[K, V], [A] =>> Iterable[A]]

Base type of immutable Maps

Base type of immutable Maps

Companion:
object
Source:
Map.scala
object Map extends MapFactory[[K, V] =>> Map[K, V]]

This object provides a set of operations to create immutable.Map values.

This object provides a set of operations to create immutable.Map values.

Companion:
class
Source:
Map.scala
trait MapOps[K, +V, +CC <: ([X, Y] =>> MapOps[X, Y, CC, _]), +C <: MapOps[K, V, CC, C]] extends IterableOps[(K, V), [A] =>> Iterable[A], C] with MapOps[K, V, CC, C]

Base trait of immutable Maps implementations

Base trait of immutable Maps implementations

Source:
Map.scala
case object Nil extends List[Nothing]
Source:
List.scala
sealed class NumericRange[T](val start: T, val end: T, val step: T, val isInclusive: Boolean)(implicit num: Integral[T]) extends AbstractSeq[T] with IndexedSeq[T] with IndexedSeqOps[T, [A] =>> IndexedSeq[A], IndexedSeq[T]] with StrictOptimizedSeqOps[T, [A] =>> IndexedSeq[A], IndexedSeq[T]] with IterableFactoryDefaults[T, [A] =>> IndexedSeq[A]] 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 = Range(0, 100, 1)
val veryBig = Int.MaxValue.toLong + 1
val r2 = Range.Long(veryBig, veryBig + 100, 1)
assert(r1 sameElements r2.map(_ - veryBig))
Companion:
object
Source:
NumericRange.scala

A companion object for numeric ranges.

A companion object for numeric ranges.

Companion:
class
Source:
NumericRange.scala
sealed class Queue[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, [A] =>> Queue[A], Queue[A]] with StrictOptimizedLinearSeqOps[A, [A] =>> Queue[A], Queue[A]] with StrictOptimizedSeqOps[A, [A] =>> Queue[A], Queue[A]] with IterableFactoryDefaults[A, [A] =>> Queue[A]] with DefaultSerializable

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).

See also:

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

Companion:
object
Source:
Queue.scala
object Queue extends StrictOptimizedSeqFactory[[A] =>> Queue[A]]

This object provides a set of operations to create immutable.Queue values.

This object provides a set of operations to create immutable.Queue values.

Companion:
class
Source:
Queue.scala
sealed abstract class Range(val start: Int, val end: Int, val step: Int) extends AbstractSeq[Int] with IndexedSeq[Int] with IndexedSeqOps[Int, [A] =>> IndexedSeq[A], IndexedSeq[Int]] with StrictOptimizedSeqOps[Int, [A] =>> IndexedSeq[A], IndexedSeq[Int]] with IterableFactoryDefaults[Int, [A] =>> IndexedSeq[A]] 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.

Value parameters:
end

the end of the range. For exclusive ranges, e.g. Range(0,3) or (0 until 3), this is one step past the last one in the range. For inclusive ranges, e.g. Range.inclusive(0,3) or (0 to 3), it may be in the range if it is not skipped by the step size. To find the last element inside a non-empty range, use last instead.

start

the start of this range.

step

the step for the range.

Companion:
object
Source:
Range.scala
object Range

Companion object for ranges.

Companion object for ranges.

Companion:
class
Source:
Range.scala
trait Seq[+A] extends Iterable[A] with Seq[A] with SeqOps[A, [A] =>> Seq[A], Seq[A]] with IterableFactoryDefaults[A, [A] =>> Seq[A]]
Companion:
object
Source:
Seq.scala
object Seq extends Delegate[[A] =>> Seq[A]]

This object provides a set of operations to create immutable.Seq values.

This object provides a set of operations to create immutable.Seq values.

Companion:
class
Source:
Seq.scala
trait SeqMap[K, +V] extends Map[K, V] with SeqMap[K, V] with MapOps[K, V, [K, V] =>> SeqMap[K, V], SeqMap[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> SeqMap[K, V], [A] =>> Iterable[A]]

A generic trait for ordered immutable maps.

A generic trait for ordered immutable maps. Concrete classes have to provide functionality for the abstract methods in SeqMap.

Note that when checking for equality SeqMap does not take into account ordering.

Type parameters:
K

the type of the keys contained in this linked map.

V

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

Companion:
object
Source:
SeqMap.scala
object SeqMap extends MapFactory[[K, V] =>> SeqMap[K, V]]
Companion:
class
Source:
SeqMap.scala
trait SeqOps[+A, +CC[_], +C] extends SeqOps[A, CC, C]
Source:
Seq.scala
trait Set[A] extends Iterable[A] with Set[A] with SetOps[A, [A] =>> Set[A], Set[A]] with IterableFactoryDefaults[A, [A] =>> Set[A]]

Base trait for immutable set collections

Base trait for immutable set collections

Companion:
object
Source:
Set.scala
object Set extends IterableFactory[[A] =>> Set[A]]

This object provides a set of operations to create immutable.Set values.

This object provides a set of operations to create immutable.Set values.

Companion:
class
Source:
Set.scala
trait SetOps[A, +CC[X], +C <: SetOps[A, CC, C]] extends SetOps[A, CC, C]

Base trait for immutable set operations

Base trait for immutable set operations

Source:
Set.scala
trait SortedMap[K, +V] extends Map[K, V] with SortedMap[K, V] with SortedMapOps[K, V, [K, V] =>> SortedMap[K, V], SortedMap[K, V]] with SortedMapFactoryDefaults[K, V, [K, V] =>> SortedMap[K, V], [A] =>> Iterable[A], [K, V] =>> Map[K, V]]

An immutable map whose key-value pairs are sorted according to an scala.math.Ordering on the keys.

An immutable map whose key-value pairs are sorted according to an scala.math.Ordering on the keys.

Allows for range queries to be performed on its keys, and implementations must guarantee that traversal happens in sorted order, according to the map's scala.math.Ordering.

Type parameters:
K

the type of the keys contained in this tree map.

V

the type of the values associated with the keys.

Example:

import scala.collection.immutable.SortedMap
// Make a SortedMap via the companion object factory
val weekdays = SortedMap(
  2 -> "Monday",
  3 -> "Tuesday",
  4 -> "Wednesday",
  5 -> "Thursday",
  6 -> "Friday"
)
// TreeMap(2 -> Monday, 3 -> Tuesday, 4 -> Wednesday, 5 -> Thursday, 6 -> Friday)
val days = weekdays ++ List(1 -> "Sunday", 7 -> "Saturday")
// TreeMap(1 -> Sunday, 2 -> Monday, 3 -> Tuesday, 4 -> Wednesday, 5 -> Thursday, 6 -> Friday, 7 -> Saturday)
val day3 = days.get(3) // Some("Tuesday")
val rangeOfDays = days.range(2, 5) // TreeMap(2 -> Monday, 3 -> Tuesday, 4 -> Wednesday)
val daysUntil2 = days.rangeUntil(2) // TreeMap(1 -> Sunday)
val daysTo2 = days.rangeTo(2) // TreeMap(1 -> Sunday, 2 -> Monday)
val daysAfter5 = days.rangeFrom(5) //  TreeMap(5 -> Thursday, 6 -> Friday, 7 -> Saturday)
Companion:
object
Source:
SortedMap.scala
object SortedMap extends Delegate[[K, V] =>> SortedMap[K, V]]
Companion:
class
Source:
SortedMap.scala
trait SortedMapOps[K, +V, +CC <: ([X, Y] =>> Map[X, Y] & SortedMapOps[X, Y, CC, _]), +C <: SortedMapOps[K, V, CC, C]] extends MapOps[K, V, [K, V] =>> Map[K, V], C] with SortedMapOps[K, V, CC, C]
trait SortedSet[A] extends Set[A] with SortedSet[A] with SortedSetOps[A, [A] =>> SortedSet[A], SortedSet[A]] with SortedSetFactoryDefaults[A, [A] =>> SortedSet[A], [A] =>> Set[A]]

Base trait for sorted sets

Base trait for sorted sets

Companion:
object
Source:
SortedSet.scala
object SortedSet extends Delegate[[A] =>> SortedSet[A]]

This object provides a set of operations to create immutable.SortedSet values.

This object provides a set of operations to create immutable.SortedSet values.

Companion:
class
Source:
SortedSet.scala
trait SortedSetOps[A, +CC <: ([X] =>> SortedSet[X]), +C <: SortedSetOps[A, CC, C]] extends SetOps[A, [A] =>> Set[A], C] with SortedSetOps[A, CC, C]
trait StrictOptimizedMapOps[K, +V, +CC <: ([X, Y] =>> MapOps[X, Y, CC, _]), +C <: MapOps[K, V, CC, C]] extends MapOps[K, V, CC, C] with StrictOptimizedMapOps[K, V, CC, C] with StrictOptimizedIterableOps[(K, V), [A] =>> Iterable[A], C]
Source:
Map.scala

Trait that overrides operations to take advantage of strict builders.

Trait that overrides operations to take advantage of strict builders.

Source:
StrictOptimizedSeqOps.scala
Source:
Set.scala
trait StrictOptimizedSortedMapOps[K, +V, +CC <: ([X, Y] =>> Map[X, Y] & SortedMapOps[X, Y, CC, _]), +C <: SortedMapOps[K, V, CC, C]] extends SortedMapOps[K, V, CC, C] with StrictOptimizedSortedMapOps[K, V, CC, C] with StrictOptimizedMapOps[K, V, [K, V] =>> Map[K, V], C]
trait StrictOptimizedSortedSetOps[A, +CC <: ([X] =>> SortedSet[X]), +C <: SortedSetOps[A, CC, C]] extends SortedSetOps[A, CC, C] with StrictOptimizedSortedSetOps[A, CC, C] with StrictOptimizedSetOps[A, [A] =>> Set[A], C]
final class TreeMap[K, +V] extends AbstractMap[K, V] with SortedMap[K, V] with StrictOptimizedSortedMapOps[K, V, [K, V] =>> TreeMap[K, V], TreeMap[K, V]] with SortedMapFactoryDefaults[K, V, [K, V] =>> TreeMap[K, V], [A] =>> Iterable[A], [K, V] =>> Map[K, V]] with DefaultSerializable

An immutable SortedMap whose values are stored in a red-black tree.

An immutable SortedMap whose values are stored in a red-black tree.

This class is optimal when range queries will be performed, or when traversal in order of an ordering is desired. If you only need key lookups, and don't care in which order key-values are traversed in, consider using * scala.collection.immutable.HashMap, which will generally have better performance. If you need insertion order, consider a * scala.collection.immutable.SeqMap, which does not need to have an ordering supplied.

Type parameters:
K

the type of the keys contained in this tree map.

V

the type of the values associated with the keys.

Value parameters:
ordering

the implicit ordering used to compare objects of type A.

See also:

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

Example:

import scala.collection.immutable.TreeMap
// Make a TreeMap via the companion object factory
val weekdays = TreeMap(
  2 -> "Monday",
  3 -> "Tuesday",
  4 -> "Wednesday",
  5 -> "Thursday",
  6 -> "Friday"
)
// TreeMap(2 -> Monday, 3 -> Tuesday, 4 -> Wednesday, 5 -> Thursday, 6 -> Friday)
val days = weekdays ++ List(1 -> "Sunday", 7 -> "Saturday")
// TreeMap(1 -> Sunday, 2 -> Monday, 3 -> Tuesday, 4 -> Wednesday, 5 -> Thursday, 6 -> Friday, 7 -> Saturday)
val day3 = days.get(3) // Some("Tuesday")
val rangeOfDays = days.range(2, 5) // TreeMap(2 -> Monday, 3 -> Tuesday, 4 -> Wednesday)
val daysUntil2 = days.rangeUntil(2) // TreeMap(1 -> Sunday)
val daysTo2 = days.rangeTo(2) // TreeMap(1 -> Sunday, 2 -> Monday)
val daysAfter5 = days.rangeFrom(5) //  TreeMap(5 -> Thursday, 6 -> Friday, 7 -> Saturday)
Companion:
object
Source:
TreeMap.scala
object TreeMap extends SortedMapFactory[[K, V] =>> TreeMap[K, V]]

This object provides a set of operations to create immutable.TreeMap values.

This object provides a set of operations to create immutable.TreeMap values.

Companion:
class
Source:
TreeMap.scala
final class TreeSeqMap[K, +V] extends AbstractMap[K, V] with SeqMap[K, V] with MapOps[K, V, [K, V] =>> TreeSeqMap[K, V], TreeSeqMap[K, V]] with StrictOptimizedIterableOps[(K, V), [A] =>> Iterable[A], TreeSeqMap[K, V]] with StrictOptimizedMapOps[K, V, [K, V] =>> TreeSeqMap[K, V], TreeSeqMap[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> TreeSeqMap[K, V], [A] =>> Iterable[A]]

This class implements an immutable map that preserves order using a hash map for the key to value mapping to provide efficient lookup, and a tree for the ordering of the keys to provide efficient insertion/modification order traversal and destructuring.

This class implements an immutable map that preserves order using a hash map for the key to value mapping to provide efficient lookup, and a tree for the ordering of the keys to provide efficient insertion/modification order traversal and destructuring.

By default insertion order (TreeSeqMap.OrderBy.Insertion) is used, but modification order (TreeSeqMap.OrderBy.Modification) can be used instead if so specified at creation.

The orderingBy(orderBy: TreeSeqMap.OrderBy): TreeSeqMap[K, V] method can be used to switch to the specified ordering for the returned map.

A key can be manually refreshed (i.e. placed at the end) via the refresh(key: K): TreeSeqMap[K, V] method (regardless of the ordering in use).

Internally, an ordinal counter is increased for each insertion/modification and then the current ordinal is used as key in the tree map. After 232 insertions/modifications the entire map is copied (thus resetting the ordinal counter).

Type parameters:
K

the type of the keys contained in this map.

V

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

Companion:
object
Source:
TreeSeqMap.scala
object TreeSeqMap extends MapFactory[[K, V] =>> TreeSeqMap[K, V]]
Companion:
class
Source:
TreeSeqMap.scala
final class TreeSet[A] extends AbstractSet[A] with SortedSet[A] with SortedSetOps[A, [A] =>> TreeSet[A], TreeSet[A]] with StrictOptimizedSortedSetOps[A, [A] =>> TreeSet[A], TreeSet[A]] with SortedSetFactoryDefaults[A, [A] =>> TreeSet[A], [A] =>> Set[A]] with DefaultSerializable

This class implements immutable sorted sets using a tree.

This class implements immutable sorted sets using a tree.

Type parameters:
A

the type of the elements contained in this tree set

Value parameters:
ordering

the implicit ordering used to compare objects of type A

See also:

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

Companion:
object
Source:
TreeSet.scala
object TreeSet extends SortedIterableFactory[[A] =>> TreeSet[A]]

This object provides a set of operations to create immutable.TreeSet values.

This object provides a set of operations to create immutable.TreeSet values.

Companion:
class
Source:
TreeSet.scala
object Vector extends StrictOptimizedSeqFactory[[A] =>> Vector[A]]

This object provides a set of operations to create Vector values.

This object provides a set of operations to create Vector values.

Companion:
class
Source:
Vector.scala
sealed abstract class Vector[+A] extends AbstractSeq[A] with IndexedSeq[A] with IndexedSeqOps[A, [A] =>> Vector[A], Vector[A]] with StrictOptimizedSeqOps[A, [A] =>> Vector[A], Vector[A]] with IterableFactoryDefaults[A, [A] =>> Vector[A]] with DefaultSerializable

Vector is a general-purpose, immutable data structure.

Vector is a general-purpose, immutable data structure. It provides random access and updates in O(log n) time, as well as very fast append/prepend/tail/init (amortized O(1), worst case O(log n)). 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.

Vectors are implemented by radix-balanced finger trees of width 32. There is a separate subclass for each level (0 to 6, with 0 being the empty vector and 6 a tree with a maximum width of 64 at the top level).

Tree balancing: - Only the first dimension of an array may have a size < WIDTH - In a data (central) array the first dimension may be up to WIDTH-2 long, in prefix1 and suffix1 up to WIDTH, and in other prefix and suffix arrays up to WIDTH-1 - prefix1 and suffix1 are never empty - Balancing does not cross the main data array (i.e. prepending never touches the suffix and appending never touches the prefix). The level is increased/decreased when the affected side plus main data is already full/empty - All arrays are left-aligned and truncated

In addition to the data slices (prefix1, prefix2, ..., dataN, ..., suffix2, suffix1) we store a running count of elements after each prefix for more efficient indexing without having to dereference all prefix arrays.

Companion:
object
Source:
Vector.scala
final class VectorBuilder[A] extends ReusableBuilder[A, Vector[A]]
final class VectorMap[K, +V] extends AbstractMap[K, V] with SeqMap[K, V] with StrictOptimizedMapOps[K, V, [K, V] =>> VectorMap[K, V], VectorMap[K, V]] with MapFactoryDefaults[K, V, [K, V] =>> VectorMap[K, V], [A] =>> Iterable[A]]

This class implements immutable maps using a vector/map-based data structure, which preserves insertion order.

This class implements immutable maps using a vector/map-based data structure, which preserves insertion order.

Unlike ListMap, VectorMap has amortized effectively constant lookup at the expense of using extra memory and generally lower performance for other operations

Type parameters:
K

the type of the keys contained in this vector map.

V

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

Companion:
object
Source:
VectorMap.scala
object VectorMap extends MapFactory[[K, V] =>> VectorMap[K, V]]
Companion:
class
Source:
VectorMap.scala
final class WrappedString(self: String) extends AbstractSeq[Char] with IndexedSeq[Char] with IndexedSeqOps[Char, [A] =>> IndexedSeq[A], WrappedString] with Serializable

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.

Value parameters:
self

a string contained within this wrapped string

Companion:
object
Source:
WrappedString.scala

A companion object for wrapped strings.

A companion object for wrapped strings.

Companion:
class
Source:
WrappedString.scala

Deprecated classlikes

@deprecated("Use LazyList (which is fully lazy) instead of Stream (which has a lazy tail only)", "2.13.0") @SerialVersionUID(3L)
sealed abstract class Stream[+A] extends AbstractSeq[A] with LinearSeq[A] with LinearSeqOps[A, [A] =>> Stream[A], Stream[A]] with IterableFactoryDefaults[A, [A] =>> Stream[A]] with Serializable
Companion:
object
Deprecated
Source:
Stream.scala
@deprecated("Use LazyList (which is fully lazy) instead of Stream (which has a lazy tail only)", "2.13.0") @SerialVersionUID(3L)
object Stream extends SeqFactory[[A] =>> Stream[A]]
Companion:
class
Deprecated
Source:
Stream.scala

Deprecated types

@deprecated("Use Map instead of DefaultMap", "2.13.0")
type DefaultMap[K, +V] = Map[K, V]
Deprecated
Source:
package.scala
@deprecated("Use Iterable instead of Traversable", "2.13.0")
Deprecated
Source:
package.scala

Value members

Deprecated fields

@deprecated("Use Iterable instead of Traversable", "2.13.0")
Deprecated
Source:
package.scala