scala.collection.immutable (original) (raw)

Supertypes

trait Map[K, V]

trait K => V

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Known subtypes

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

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

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An immutable array.

Supports efficient indexed access and has a small memory footprint.

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Companion

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ArraySeq.scala

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Known subtypes

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

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Companion

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ArraySeq.scala

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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.

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Companion

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BitSet.scala

Supertypes

Known subtypes

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

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Companion

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BitSet.scala

Supertypes

Self type

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

the type of the keys contained in this hash set.

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

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Companion

Source

HashMap.scala

Supertypes

trait Map[K, V]

trait K => V

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

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Companion

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HashMap.scala

Supertypes

Self type

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

the type of the elements contained in this hash set.

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Companion

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HashSet.scala

Supertypes

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

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Companion

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HashSet.scala

Supertypes

Self type

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

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Companion

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Supertypes

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Supertypes

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Base trait for immutable indexed Seq operations

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A companion object for integer maps.

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Companion

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IntMap.scala

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Self type

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

type of the values associated with integer keys.

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Companion

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IntMap.scala

Supertypes

A trait for collections that are guaranteed immutable.

Type parameters

the element type of the collection

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Companion

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Iterable.scala

Supertypes

Known subtypes

trait Map[K, V]

class ::[A]

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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 <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mi>n</mi><msub><mi mathvariant="normal">.</mi><mn>1</mn></msub></mrow><mi>a</mi><mi>n</mi><mi>d</mi></mrow><annotation encoding="application/x-tex">{n._1} and </annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8444em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal">n</span><span class="mord"><span class="mord">.</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3011em;"><span style="top:-2.55em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">1</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mord mathnormal">an</span><span class="mord mathnormal">d</span></span></span></span>{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"

You may sometimes encounter an exception like the following:

java.lang.RuntimeException: "LazyList evaluation depends on its own result (self-reference); see docs for more info

This exception occurs when a LazyList is attempting to derive its next element from itself, and is attempting to read the element currently being evaluated. A trivial example of such might be

lazy val a: LazyList[Int] = 1 #:: 2 #:: a.filter(_ > 2)

When attempting to evaluate the third element of a, it will skip the first two elements and read the third, but that element is already being evaluated. This is often caused by a subtle logic error; in this case, using >= in the filter would fix the error.

Type parameters

the type of the elements contained in this lazy list.

Attributes

See also

Companion

Source

LazyList.scala

Supertypes

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

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Companion

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LazyList.scala

Supertypes

Self type

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

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Companion

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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

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See also

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

Source

List.scala

Supertypes

Known subtypes

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

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Companion

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List.scala

Supertypes

Self type

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

the type of the keys contained in this list map

the type of the values associated with the keys

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Companion

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ListMap.scala

Supertypes

trait Map[K, V]

trait K => V

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This object provides a set of operations to create Iterable 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.

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ListMap.scala

Supertypes

Self type

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

the type of the elements contained in this list set

Attributes

Companion

Source

ListSet.scala

Supertypes

This object provides a set of operations to create Iterable 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.

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Companion

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ListSet.scala

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Self type

A companion object for long maps.

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Companion

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LongMap.scala

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Self type

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

type of the values associated with the long keys.

Attributes

Companion

Source

LongMap.scala

Supertypes

Base type of immutable Maps

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Companion

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Supertypes

trait Map[K, V]

trait K => V

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Known subtypes

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

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Self type

Base trait of immutable Maps implementations

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trait MapOps[K, V, CC, C]

trait K => V

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Known subtypes

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))

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Companion

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NumericRange.scala

Supertypes

Known subtypes

Self type

A companion object for numeric ranges.

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).

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Companion

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Queue.scala

Supertypes

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

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Companion

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Queue.scala

Supertypes

Self type

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.

Attributes

Companion

Source

Range.scala

Supertypes

Known subtypes

Self type

Companion object for ranges.

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Companion

Source

Range.scala

Supertypes

Self type

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

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Supertypes

Self type

A base trait for ordered, immutable maps.

Note that the equals method for SeqMap compares key-value pairs without regard to ordering.

All behavior is defined in terms of the abstract methods in SeqMap. It is sufficient for concrete subclasses to implement those methods. Methods that return a new map, in particular removed and updated, must preserve ordering.

Type parameters

the type of the keys contained in this linked map.

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

Attributes

Companion

Source

SeqMap.scala

Supertypes

trait Map[K, V]

trait K => V

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Known subtypes

Attributes

Source

Supertypes

Known subtypes

Base trait for immutable set collections

Attributes

Companion

Source

Supertypes

Known subtypes

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

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Companion

Source

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Self type

Base trait for immutable set operations

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Known subtypes

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

the type of the keys contained in this tree map.

the type of the values associated with the keys.

Attributes

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

Source

SortedMap.scala

Supertypes

trait Map[K, V]

trait K => V

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Known subtypes

Base trait for sorted sets

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

Attributes

Companion

Source

SortedSet.scala

Supertypes

Self type

Attributes

Source

StrictOptimizedSeqOps.scala

Supertypes

trait MapOps[K, V, CC, C]

trait K => V

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Known subtypes

Trait that overrides operations to take advantage of strict builders.

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Source

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Known subtypes

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

the type of the keys contained in this tree map.

the type of the values associated with the keys.

Value parameters

ordering

the implicit ordering used to compare objects of type A.

Attributes

See also

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

Source

TreeMap.scala

Supertypes

trait Map[K, V]

trait K => V

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

Attributes

Companion

Source

TreeMap.scala

Supertypes

Self type

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

the type of the keys contained in this map.

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

Attributes

Companion

Source

TreeSeqMap.scala

Supertypes

trait Map[K, V]

trait K => V

Show all

This class implements immutable sorted sets using a tree.

Type parameters

the type of the elements contained in this tree set

Value parameters

ordering

the implicit ordering used to compare objects of type A

Attributes

See also

Companion

Source

TreeSet.scala

Supertypes

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

Attributes

Companion

Source

TreeSet.scala

Supertypes

Self type

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

Attributes

Companion

Source

Vector.scala

Supertypes

Self type

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.

Attributes

Companion

Source

Vector.scala

Supertypes

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

the type of the keys contained in this vector map.

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

Attributes

Companion