Common Sequential Collections Methods

A great strength of the Scala collections classes is that they come with dozens of pre-built methods. The benefit of this is that you no longer need to write custom for loops every time you need to work on a collection. (If that’s not enough of a benefit, it also means that you no longer have to read custom for loops written by other developers.)

Because there are so many methods available to you, I’m not going to show them all here. (I do that in the Scala Cookbook.) Instead, I’ll just show how to use some of the most commonly-used methods, including:

  • map
  • filter
  • foreach
  • head
  • tail
  • take, takeWhile
  • drop, dropWhile
  • find
  • reduce, fold

The methods I’ll show work on all of the sequential collections classes, including Array, ArrayBuffer, List, Vector, etc., but in these examples I’ll use a List unless otherwise specified.

Note: The methods don’t mutate the list

As a very important note, none of these methods mutate the list that they’re called on. They all work in a functional style, so they return a new list with the modified results.

Sample lists

In the following examples I’ll use these lists:

val nums = (1 to 10).toList
val names = List("joel", "ed", "chris", "maurice")

This is what these lists look like in the REPL:

scala> val nums = (1 to 10).toList
nums: List[Int] = List(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

scala> val names = List("joel", "ed", "chris", "maurice")
names: List[String] = List(joel, ed, chris, maurice)


The map method steps through each element in the existing list, applying the algorithm you supply to each element, one at a time; it then returns a new list with all of the modified elements.

Here’s an example of the map method being applied to the nums list:

scala> val doubles = * 2)
doubles: List[Int] = List(2, 4, 6, 8, 10, 12, 14, 16, 18, 20)

As I wrote in the lesson on anonymous functions, you can also write the anonymous function like this:

scala> val doubles = => i * 2)
doubles: List[Int] = List(2, 4, 6, 8, 10, 12, 14, 16, 18, 20)

However, in this lesson I’ll always use the first, shorter form.

With that background, here’s an example of the map method being applied to the nums and names lists:

scala> val capNames =
capNames: List[String] = List(Joel, Ed, Chris, Maurice)

scala> val doubles = * 2)
doubles: List[Int] = List(2, 4, 6, 8, 10, 12, 14, 16, 18, 20)

scala> val lessThanFive = < 5)
lessThanFive: List[Boolean] = List(true, true, true, true, false, false, false, false, false, false)

As that last example shows, it’s perfectly legal (and very common) to use map to return a list with a different type (List[Boolean]) from the original type (List[Int]).


The filter method creates a new, filtered list from the given list. Here are a few examples:

scala> val lessThanFive = nums.filter(_ < 5)
lessThanFive: List[Int] = List(1, 2, 3, 4)

scala> val evens = nums.filter(_ % 2 == 0)
evens: List[Int] = List(2, 4, 6, 8, 10)

scala> val shortNames = names.filter(_.length <= 4)
shortNames: List[String] = List(joel, ed)


The foreach method is used to loop over all elements in a collection. As I mentioned earlier, foreach is used for side-effects, such as printing information. Here’s an example with the names list:

scala> names.foreach(println)

The nums list is a little long, so I don’t want to print out all of those elements. But a great thing about Scala’s approach is that you can chain methods together to solve problems like this. For example, this is one way to print the first three elements from nums:

nums.filter(_ < 4).foreach(println)

The REPL shows the result:

scala> nums.filter(_ < 4).foreach(println)

The head method comes from Lisp and functional programming languages. It’s used to print the first element (the head element) of a list:

scala> nums.head
res0: Int = 1

scala> names.head
res1: String = joel

Because a String is a sequence of characters, you can also treat it like a list. This is how head works on these strings:

scala> "foo".head
res2: Char = f

scala> "bar".head
res3: Char = b


The tail method also comes from Lisp and functional programming languages. It’s used to print every element in a list after the head element. A few examples:

scala> nums.tail
res0: List[Int] = List(2, 3, 4, 5, 6, 7, 8, 9, 10)

scala> names.tail
res1: List[String] = List(ed, chris, maurice)

Just like head, tail also works on strings:

scala> "foo".tail
res2: String = oo

scala> "bar".tail
res3: String = ar

take, takeWhile

The take and takeWhile methods give you a nice way of taking the elements out of a list that you want to create a new list. This is take:

scala> nums.take(1)
res0: List[Int] = List(1)

scala> nums.take(2)
res1: List[Int] = List(1, 2)

scala> names.take(1)
res2: List[String] = List(joel)

scala> names.take(2)
res3: List[String] = List(joel, ed)

And this is takeWhile:

scala> nums.takeWhile(_ < 5)
res4: List[Int] = List(1, 2, 3, 4)

scala> names.takeWhile(_.length < 5)
res5: List[String] = List(joel, ed)

drop, dropWhile

drop and dropWhile are essentially the opposite of take and takeWhile. This is drop:

scala> nums.drop(1)
res0: List[Int] = List(2, 3, 4, 5, 6, 7, 8, 9, 10)

scala> nums.drop(5)
res1: List[Int] = List(6, 7, 8, 9, 10)

scala> names.drop(1)
res2: List[String] = List(ed, chris, maurice)

scala> names.drop(2)
res3: List[String] = List(chris, maurice)

And this is dropWhile:

scala> nums.dropWhile(_ < 5)
res4: List[Int] = List(5, 6, 7, 8, 9, 10)

scala> names.dropWhile(_ != "chris")
res5: List[String] = List(chris, maurice)


When you hear the term, “map reduce,” the “reduce” part refers to methods like reduce. It takes a function (or anonymous function) and applies that function to successive elements in the list.

The best way to explain reduce is to create a little helper method we can pass into it. For example, this is an add method that adds two integers together, but also gives us some nice debug output:

def add(x: Int, y: Int): Int = {
    val theSum = x + y
    println(s"received $x and $y, their sum is $theSum")

Now, given that method and this list:

val a = List(1,2,3,4)

this is what happens when I pass the add method into reduce:

scala> a.reduce(add)
received 1 and 2, their sum is 3
received 3 and 3, their sum is 6
received 6 and 4, their sum is 10
res0: Int = 10

As that result shows, reduce uses add to reduce the list a into a single value, in this case, the sum of the integers in the list.

Once you get used to reduce, you’ll write a “sum” algorithm like this:

scala> a.reduce(_ + _)
res0: Int = 10

Similarly, this is what a “product” algorithm looks like:

scala> a.reduce(_ * _)
res1: Int = 24

I know that might be a little mind-blowing if you’ve never seen it before, but because this is an “introduction” book, I’m going to leave it at that for now. For more details, please see the Scala Cookbook, which has over 100 pages on the Scala collections, and Functional Programming, Simplified, which has a very detailed chapter on how methods like reduce and fold work.

Before I go, the important part about reduce is that it’s used to reduce a collection down to a single value.

That’s all for now

There are literally dozens of additional methods on the Scala sequential collections classes that will keep you from ever needing to write another for loop. However, because this is a simple introduction book, I won’t cover them all. As mentioned, please see the Scala Cookbook and Functional Programming, Simplified for many more details.

results matching ""

    No results matching ""