# Common Sequence 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, they won’t all be shown here. Instead, just some of the most commonly-used methods will be shown, including:

The following methods will work on all of the collections “sequence” classes, including Array, ArrayBuffer, List, Vector, etc., but these examples will use a List unless otherwise specified.

## Note: The methods don’t mutate the collection

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

## Sample lists

The following examples will use these lists:

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



This is what those 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)



## map

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 = nums.map(_ * 2)
doubles: List[Int] = List(2, 4, 6, 8, 10, 12, 14, 16, 18, 20)



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

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



However, in this lesson we’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 = names.map(_.capitalize)
capNames: List[String] = List(Joel, Ed, Chris, Maurice)

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

scala> val lessThanFive = nums.map(_ < 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]).

## filter

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)



## foreach

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

scala> names.foreach(println)
joel
ed
chris
maurice



The nums list is a little long, so you may not 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)
1
2
3



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

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

res3: Char = b



head is a great method to work with, but as a word of caution it can also throw an exception when called on an empty collection:

scala> val emptyList = List[Int]()
val emptyList: List[Int] = List()



## tail

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



Note that like head, tail will also throw an exception when called on an empty collection:

scala> emptyList.tail
java.lang.UnsupportedOperationException: tail of empty list



## 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)



## reduce

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 you can pass into it. For example, this is an add method that adds two integers together, and 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")
theSum
}


Now, given that method and this list:

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


this is what happens when you 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



That might be a little mind-blowing if you’ve never seen it before, but after a while you’ll get used to it.

Before moving on, an important part to know about reduce is that — as its name implies — it’s used to reduce a collection down to a single value.

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