Scala 3 — Book

Collections Types

Language

This page demonstrates the common Scala 3 collections and their accompanying methods. Scala comes with a wealth of collections types, but you can go a long way by starting with just a few of them, and later using the others as needed. Similarly, each collection type has dozens of methods to make your life easier, but you can achieve a lot by starting with just a handful of them.

Therefore, this section introduces and demonstrates the most common types and methods that you’ll need to get started. When you need more flexibility, see these pages at the end of this section for more details.

Three main categories of collections

Looking at Scala collections from a high level, there are three main categories to choose from:

  • Sequences are a sequential collection of elements and may be indexed (like an array) or linear (like a linked list)
  • Maps contain a collection of key/value pairs, like a Java Map, Python dictionary, or Ruby Hash
  • Sets are an unordered collection of unique elements

All of those are basic types, and have subtypes for specific purposes, such as concurrency, caching, and streaming. In addition to those three main categories, there are other useful collection types, including ranges, stacks, and queues.

Collections hierarchy

As a brief overview, the next three figures show the hierarchy of classes and traits in the Scala collections.

This first figure shows the collections types in package scala.collection. These are all high-level abstract classes or traits, which generally have immutable and mutable implementations.

General collection hierarchy

This figure shows all collections in package scala.collection.immutable:

Immutable collection hierarchy

And this figure shows all collections in package scala.collection.mutable:

Mutable collection hierarchy

Having seen that detailed view of all the collections types, the following sections introduce some common types you’ll use on a regular basis.

Common collections

The main collections you’ll use on a regular basis are:

Collection Type Immutable Mutable Description
List   A linear (linked list), immutable sequence
Vector   An indexed, immutable sequence
LazyList   A lazy immutable linked list, its elements are computed only when they’re needed; Good for large or infinite sequences.
ArrayBuffer   The go-to type for a mutable, indexed sequence
ListBuffer   Used when you want a mutable List; typically converted to a List
Map An iterable collection that consists of pairs of keys and values.
Set An iterable collection with no duplicate elements

As shown, Map and Set come in both immutable and mutable versions.

The basics of each type are demonstrated in the following sections.

In Scala, a buffer—such as ArrayBuffer and ListBuffer—is a sequence that can grow and shrink.

A note about immutable collections

In the sections that follow, whenever the word immutable is used, it’s safe to assume that the type is intended for use in a functional programming (FP) style. With these types you don’t modify the collection; you apply functional methods to the collection to create a new result.

Choosing a sequence

When choosing a sequence—a sequential collection of elements—you have two main decisions:

  • Should the sequence be indexed (like an array), allowing rapid access to any element, or should it be implemented as a linear linked list?
  • Do you want a mutable or immutable collection?

The recommended, general-purpose, “go to” sequential collections for the combinations of mutable/immutable and indexed/linear are shown here:

Type/Category Immutable Mutable
Indexed Vector ArrayBuffer
Linear (Linked lists) List ListBuffer

For example, if you need an immutable, indexed collection, in general you should use a Vector. Conversely, if you need a mutable, indexed collection, use an ArrayBuffer.

List and Vector are often used when writing code in a functional style. ArrayBuffer is commonly used when writing code in an imperative style. ListBuffer is used when you’re mixing styles, such as building a list.

The next several sections briefly demonstrate the List, Vector, and ArrayBuffer types.

List

The List type is a linear, immutable sequence. This just means that it’s a linked-list that you can’t modify. Any time you want to add or remove List elements, you create a new List from an existing List.

Creating Lists

This is how you create an initial List:

val ints = List(1, 2, 3)
val names = List("Joel", "Chris", "Ed")

// another way to construct a List
val namesAgain = "Joel" :: "Chris" :: "Ed" :: Nil

You can also declare the List’s type, if you prefer, though it generally isn’t necessary:

val ints: List[Int] = List(1, 2, 3)
val names: List[String] = List("Joel", "Chris", "Ed")

One exception is when you have mixed types in a collection; in that case you may want to explicitly specify its type:

val things: List[Any] = List(1, "two", 3.0)
val things: List[String | Int | Double] = List(1, "two", 3.0) // with union types
val thingsAny: List[Any] = List(1, "two", 3.0)                // with any

Adding elements to a List

Because List is immutable, you can’t add new elements to it. Instead, you create a new list by prepending or appending elements to an existing List. For instance, given this List:

val a = List(1, 2, 3)

When working with a List, prepend one element with ::, and prepend another List with :::, as shown here:

val b = 0 :: a              // List(0, 1, 2, 3)
val c = List(-1, 0) ::: a   // List(-1, 0, 1, 2, 3)

You can also append elements to a List, but because List is a singly-linked list, you should generally only prepend elements to it; appending elements to it is a relatively slow operation, especially when you work with large sequences.

Tip: If you want to prepend and append elements to an immutable sequence, use Vector instead.

Because List is a linked-list, you shouldn’t try to access the elements of large lists by their index value. For instance, if you have a List with one million elements in it, accessing an element like myList(999_999) will take a relatively long time, because that request has to traverse all those elements. If you have a large collection and want to access elements by their index, use a Vector or ArrayBuffer instead.

How to remember the method names

These days IDEs help us out tremendously, but one way to remember those method names is to think that the : character represents the side that the sequence is on, so when you use +: you know that the list needs to be on the right, like this:

0 +: a

Similarly, when you use :+ you know the list needs to be on the left:

a :+ 4

There are more technical ways to think about this, but this can be a helpful way to remember the method names.

Also, a good thing about these symbolic method names is that they’re consistent. The same method names are used with other immutable sequences, such as Seq and Vector. You can also use non-symbolic method names to append and prepend elements, if you prefer.

How to loop over lists

Given a List of names:

val names = List("Joel", "Chris", "Ed")

you can print each string like this:

for (name <- names) println(name)
for name <- names do println(name)

This is what it looks like in the REPL:

scala> for (name <- names) println(name)
Joel
Chris
Ed
scala> for name <- names do println(name)
Joel
Chris
Ed

A great thing about using for loops with collections is that Scala is consistent, and the same approach works with all sequences, including Array, ArrayBuffer, List, Seq, Vector, Map, Set, etc.

A little bit of history

For those interested in a little bit of history, the Scala List is similar to the List from the Lisp programming language, which was originally specified in 1958. Indeed, in addition to creating a List like this:

val ints = List(1, 2, 3)

you can also create the exact same list this way:

val list = 1 :: 2 :: 3 :: Nil

The REPL shows how this works:

scala> val list = 1 :: 2 :: 3 :: Nil
list: List[Int] = List(1, 2, 3)

This works because a List is a singly-linked list that ends with the Nil element, and :: is a List method that works like Lisp’s “cons” operator.

Aside: The LazyList

The Scala collections also include a LazyList, which is a lazy immutable linked list. It’s called “lazy”—or non-strict—because it computes its elements only when they are needed.

You can see how lazy a LazyList is in the REPL:

val x = LazyList.range(1, Int.MaxValue)
x.take(1)      // LazyList(<not computed>)
x.take(5)      // LazyList(<not computed>)
x.map(_ + 1)   // LazyList(<not computed>)

In all of those examples, nothing happens. Indeed, nothing will happen until you force it to happen, such as by calling its foreach method:

scala> x.take(1).foreach(println)
1

For more information on the uses, benefits, and drawbacks of strict and non-strict (lazy) collections, see the “strict” and “non-strict” discussions on the The Architecture of Scala 2.13’s Collections page.

Vector

Vector is an indexed, immutable sequence. The “indexed” part of the description means that it provides random access and update in effectively constant time, so you can access Vector elements rapidly by their index value, such as accessing listOfPeople(123_456_789).

In general, except for the difference that (a) Vector is indexed and List is not, and (b) List has the :: method, the two types work the same, so we’ll quickly run through the following examples.

Here are a few ways you can create a Vector:

val nums = Vector(1, 2, 3, 4, 5)

val strings = Vector("one", "two")

case class Person(name: String)
val people = Vector(
  Person("Bert"),
  Person("Ernie"),
  Person("Grover")
)

Because Vector is immutable, you can’t add new elements to it. Instead, you create a new sequence by appending or prepending elements to an existing Vector. These examples show how to append elements to a Vector:

val a = Vector(1,2,3)         // Vector(1, 2, 3)
val b = a :+ 4                // Vector(1, 2, 3, 4)
val c = a ++ Vector(4, 5)     // Vector(1, 2, 3, 4, 5)

This is how you prepend elements:

val a = Vector(1,2,3)         // Vector(1, 2, 3)
val b = 0 +: a                // Vector(0, 1, 2, 3)
val c = Vector(-1, 0) ++: a   // Vector(-1, 0, 1, 2, 3)

In addition to fast random access and updates, Vector provides fast append and prepend times, so you can use these features as desired.

See the Collections Performance Characteristics for performance details about Vector and other collections.

Finally, you use a Vector in a for loop just like a List, ArrayBuffer, or any other sequence:

scala> val names = Vector("Joel", "Chris", "Ed")
val names: Vector[String] = Vector(Joel, Chris, Ed)

scala> for (name <- names) println(name)
Joel
Chris
Ed
scala> val names = Vector("Joel", "Chris", "Ed")
val names: Vector[String] = Vector(Joel, Chris, Ed)

scala> for name <- names do println(name)
Joel
Chris
Ed

ArrayBuffer

Use ArrayBuffer when you need a general-purpose, mutable indexed sequence in your Scala applications. It’s mutable, so you can change its elements, and also resize it. Because it’s indexed, random access of elements is fast.

Creating an ArrayBuffer

To use an ArrayBuffer, first import it:

import scala.collection.mutable.ArrayBuffer

If you need to start with an empty ArrayBuffer, just specify its type:

var strings = ArrayBuffer[String]()
var ints = ArrayBuffer[Int]()
var people = ArrayBuffer[Person]()

If you know the approximate size your ArrayBuffer eventually needs to be, you can create it with an initial size:

// ready to hold 100,000 ints
val buf = new ArrayBuffer[Int](100_000)

To create a new ArrayBuffer with initial elements, just specify its initial elements, just like a List or Vector:

val nums = ArrayBuffer(1, 2, 3)
val people = ArrayBuffer(
  Person("Bert"),
  Person("Ernie"),
  Person("Grover")
)

Adding elements to an ArrayBuffer

Append new elements to an ArrayBuffer with the += and ++= methods. Or if you prefer methods with textual names you can also use append, appendAll, insert, insertAll, prepend, and prependAll.

Here are some examples of += and ++=:

val nums = ArrayBuffer(1, 2, 3)   // ArrayBuffer(1, 2, 3)
nums += 4                         // ArrayBuffer(1, 2, 3, 4)
nums ++= List(5, 6)               // ArrayBuffer(1, 2, 3, 4, 5, 6)

Removing elements from an ArrayBuffer

ArrayBuffer is mutable, so it has methods like -=, --=, clear, remove, and more. These examples demonstrate the -= and --= methods:

val a = ArrayBuffer.range('a', 'h')   // ArrayBuffer(a, b, c, d, e, f, g)
a -= 'a'                              // ArrayBuffer(b, c, d, e, f, g)
a --= Seq('b', 'c')                   // ArrayBuffer(d, e, f, g)
a --= Set('d', 'e')                   // ArrayBuffer(f, g)

Updating ArrayBuffer elements

Update elements in an ArrayBuffer by either reassigning the desired element, or use the update method:

val a = ArrayBuffer.range(1,5)        // ArrayBuffer(1, 2, 3, 4)
a(2) = 50                             // ArrayBuffer(1, 2, 50, 4)
a.update(0, 10)                       // ArrayBuffer(10, 2, 50, 4)

Maps

A Map is an iterable collection that consists of pairs of keys and values. Scala has both mutable and immutable Map types, and this section demonstrates how to use the immutable Map.

Creating an immutable Map

Create an immutable Map like this:

val states = Map(
  "AK" -> "Alaska",
  "AL" -> "Alabama",
  "AZ" -> "Arizona"
)

Once you have a Map you can traverse its elements in a for loop like this:

for ((k, v) <- states)  println(s"key: $k, value: $v")
for (k, v) <- states do println(s"key: $k, value: $v")

The REPL shows how this works:

scala> for ((k, v) <- states)  println(s"key: $k, value: $v")
key: AK, value: Alaska
key: AL, value: Alabama
key: AZ, value: Arizona
scala> for (k, v) <- states do println(s"key: $k, value: $v")
key: AK, value: Alaska
key: AL, value: Alabama
key: AZ, value: Arizona

Accessing Map elements

Access map elements by specifying the desired key value in parentheses:

val ak = states("AK")   // ak: String = Alaska
val al = states("AL")   // al: String = Alabama

In practice, you’ll also use methods like keys, keySet, keysIterator, for loops, and higher-order functions like map to work with Map keys and values.

Adding elements to a Map

Add elements to an immutable map using + and ++, remembering to assign the result to a new variable:

val a = Map(1 -> "one")    // a: Map(1 -> one)
val b = a + (2 -> "two")   // b: Map(1 -> one, 2 -> two)
val c = b ++ Seq(
  3 -> "three",
  4 -> "four"
)
// c: Map(1 -> one, 2 -> two, 3 -> three, 4 -> four)

Removing elements from a Map

Remove elements from an immutable map using - or -- and the key values to remove, remembering to assign the result to a new variable:

val a = Map(
  1 -> "one",
  2 -> "two",
  3 -> "three",
  4 -> "four"
)

val b = a - 4       // b: Map(1 -> one, 2 -> two, 3 -> three)
val c = a - 4 - 3   // c: Map(1 -> one, 2 -> two)

Updating Map elements

To update elements in an immutable map, use the updated method (or the + operator) while assigning the result to a new variable:

val a = Map(
  1 -> "one",
  2 -> "two",
  3 -> "three"
)

val b = a.updated(3, "THREE!")   // b: Map(1 -> one, 2 -> two, 3 -> THREE!)
val c = a + (2 -> "TWO...")      // c: Map(1 -> one, 2 -> TWO..., 3 -> three)

Traversing a Map

As shown earlier, this is a common way to manually traverse elements in a map using a for loop:

val states = Map(
  "AK" -> "Alaska",
  "AL" -> "Alabama",
  "AZ" -> "Arizona"
)

for ((k, v) <- states) println(s"key: $k, value: $v")
val states = Map(
  "AK" -> "Alaska",
  "AL" -> "Alabama",
  "AZ" -> "Arizona"
)

for (k, v) <- states do println(s"key: $k, value: $v")

That being said, there are many ways to work with the keys and values in a map. Common Map methods include foreach, map, keys, and values.

Scala has many more specialized Map types, including CollisionProofHashMap, HashMap, LinkedHashMap, ListMap, SortedMap, TreeMap, WeakHashMap, and more.

Working with Sets

The Scala Set is an iterable collection with no duplicate elements.

Scala has both mutable and immutable Set types. This section demonstrates the immutable Set.

Creating a Set

Create new empty sets like this:

val nums = Set[Int]()
val letters = Set[Char]()

Create sets with initial data like this:

val nums = Set(1, 2, 3, 3, 3)           // Set(1, 2, 3)
val letters = Set('a', 'b', 'c', 'c')   // Set('a', 'b', 'c')

Adding elements to a Set

Add elements to an immutable Set using + and ++, remembering to assign the result to a new variable:

val a = Set(1, 2)                // Set(1, 2)
val b = a + 3                    // Set(1, 2, 3)
val c = b ++ Seq(4, 1, 5, 5)     // HashSet(5, 1, 2, 3, 4)

Notice that when you attempt to add duplicate elements, they’re quietly dropped.

Also notice that the order of iteration of the elements is arbitrary.

Deleting elements from a Set

Remove elements from an immutable set using - and --, again assigning the result to a new variable:

val a = Set(1, 2, 3, 4, 5)   // HashSet(5, 1, 2, 3, 4)
val b = a - 5                // HashSet(1, 2, 3, 4)
val c = b -- Seq(3, 4)       // HashSet(1, 2)

Range

The Scala Range is often used to populate data structures and to iterate over for loops. These REPL examples demonstrate how to create ranges:

1 to 5         // Range(1, 2, 3, 4, 5)
1 until 5      // Range(1, 2, 3, 4)
1 to 10 by 2   // Range(1, 3, 5, 7, 9)
'a' to 'c'     // NumericRange(a, b, c)

You can use ranges to populate collections:

val x = (1 to 5).toList     // List(1, 2, 3, 4, 5)
val x = (1 to 5).toBuffer   // ArrayBuffer(1, 2, 3, 4, 5)

They’re also used in for loops:

scala> for (i <- 1 to 3) println(i)
1
2
3
scala> for i <- 1 to 3 do println(i)
1
2
3

There are also range methods on :

Vector.range(1, 5)       // Vector(1, 2, 3, 4)
List.range(1, 10, 2)     // List(1, 3, 5, 7, 9)
Set.range(1, 10)         // HashSet(5, 1, 6, 9, 2, 7, 3, 8, 4)

When you’re running tests, ranges are also useful for generating test collections:

val evens = (0 to 10 by 2).toList     // List(0, 2, 4, 6, 8, 10)
val odds = (1 to 10 by 2).toList      // List(1, 3, 5, 7, 9)
val doubles = (1 to 5).map(_ * 2.0)   // Vector(2.0, 4.0, 6.0, 8.0, 10.0)

// create a Map
val map = (1 to 3).map(e => (e,s"$e")).toMap
    // map: Map[Int, String] = Map(1 -> "1", 2 -> "2", 3 -> "3")

More details

When you need more information about specialized collections, see the following resources:

Contributors to this page: