Scala Cheat Sheet

Note: This is my personalised fork of lampepfl/progfun-wiki

There is an official Scala Cheat Sheat available, too.

Comparison to Java 8

Scala Classes cannot have static members. However you can use Scala Objects to get the mimic this behaviour.
Scala Traits are almost like Interfaces in Java 8. They can contain methods and field definitions.
Scala Objects are single instances. They cannot be created via new. The fields/methods/... are accessed directly. (Almost like static fields/methods/... in Java).

Evaluation Rules

Call by value: evaluates the function arguments before calling the function
Call by name: evaluates the function first, and then evaluates the arguments if need be

    def example = 2      // evaluated when called
    val example = 2      // evaluated immediately
    lazy val example = 2 // evaluated once when needed

    def square(x: Double)    // call by value
    def square(x: => Double) // call by name
    def myFct(bindings: Int*) = { ... } // bindings is a sequence of int, containing a varying # of arguments

Higher order functions

These are functions that take a function as a parameter or return functions.

    // sum() returns a function that takes two integers and returns an integer  
    def sum(f: Int => Int): (Int, Int) => Int = {  
      def sumf(a: Int, b: Int): Int = {...}  
      sumf  
    }

    // same as above. Its type is (Int => Int) => (Int, Int) => Int  
    def sum(f: Int => Int)(a: Int, b: Int): Int = { ... }

    // Called like this
    sum((x: Int) => x * x * x)          // Anonymous function, i.e. does not have a name  
    sum(x => x * x * x)                 // Same anonymous function with type inferred

    def cube(x: Int) = x * x * x  
    sum(x => x * x * x)(1, 10) // sum of cubes from 1 to 10
    sum(cube)(1, 10)           // same as above

Currying

Converting a function with multiple arguments into a function with a single argument that returns another function.

    def f(a: Int, b: Int): Int // uncurried version (type is (Int, Int) => Int)
    def f(a: Int)(b: Int): Int // curried version (type is Int => Int => Int)

Classes

    class MyClass(x: Int, y: Int) {           // Defines a new type MyClass with a constructor  
      require(y > 0, "y must be positive")    // precondition, triggering an IllegalArgumentException if not met  
      def this (x: Int) = { ... }             // auxiliary constructor   
      def nb1 = x                             // public method computed every time it is called  
      def nb2 = y  
      private def test(a: Int): Int = { ... } // private method  
      val nb3 = x + y                         // computed only once  
      override def toString =                 // overridden method  
          member1 + ", " + member2
    }

    new MyClass(1, 2) // creates a new object of type

this references the current object, assert(<condition>) issues AssertionError if condition is not met. See scala.Predef for require, assume and assert.

Operators

myObject myMethod 1 is the same as calling myObject.myMethod(1)

Operator (i.e. function) names can be alphanumeric, symbolic (e.g. x1, *, +?%&, vector_++, counter_=)

The precedence of an operator is determined by its first character, with the following increasing order of priority:

(all letters)
|
^
&
< >
= !
:
+ -
* / %
(all other special characters)

The associativity of an operator is determined by its last character: Right-associative if ending with :, Left-associative otherwise.

Note that assignment operators have lowest precedence. (Read Scala Language Specification 2.9 sections 6.12.3, 6.12.4 for more info)

Class hierarchies

    abstract class TopLevel {    // abstract class  
      def method1(x: Int): Int   // abstract method  
      def method2(x: Int): Int = { ... }  
    }

    class Level1 extends TopLevel {  
      def method1(x: Int): Int = { ... }  
      override def method2(x: Int): Int = { ...} // TopLevel's method2 needs to be explicitly overridden  
    }

    object MyObject extends TopLevel { ... } // defines a singleton object. No other instance can be created

To create a runnable application in Scala:

    object Hello {  
      def main(args: Array[String]) = println("Hello world")  
    }

    object Hello extends App {
      println("Hello World")
    }

Class Organization

Classes and objects are organized in packages (package myPackage).
They can be referenced through import statements (import myPackage.MyClass, import myPackage._, import myPackage.{MyClass1, MyClass2}, import myPackage.{MyClass1 => A})
They can also be directly referenced in the code with the fully qualified name (new myPackage.MyClass1)
All members of packages scala and java.lang as well as all members of the object scala.Predef are automatically imported.
Traits are similar to Java interfaces, except they can have non-abstract members:

        trait Planar { ... }
        class Square extends Shape with Planar

General object hierarchy:
scala.Any base type of all types. Has methods hashCode and toString that can be overridden
scala.AnyVal base type of all primitive types. (scala.Double, scala.Float, etc.)
scala.AnyRef base type of all reference types. (alias of java.lang.Object, supertype of java.lang.String, scala.List, any user-defined class)
scala.Null is a subtype of any scala.AnyRef (null is the only instance of type Null), and scala.Nothing is a subtype of any other type without any instance.

Type Parameters

Conceptually similar to C++ templates or Java generics. These can apply to classes, traits or functions.

    class MyClass[T](arg1: T) { ... }  
    new MyClass[Int](1)  
    new MyClass(1)   // the type is being inferred, i.e. determined based on the value arguments

It is possible to restrict the type being used, e.g.

    def myFct[T <: TopLevel](arg: T): T = { ... } // T must derive from TopLevel or be TopLevel
    def myFct[T >: Level1](arg: T): T = { ... }   // T must be a supertype of Level1
    def myFct[T >: Level1 <: Top Level](arg: T): T = { ... }

Variance

Given A <: B

If C[A] <: C[B], C is covariant

If C[A] >: C[B], C is contravariant

Otherwise C is nonvariant

    class C[+A] { ... } // C is covariant
    class C[-A] { ... } // C is contravariant
    class C[A]  { ... } // C is nonvariant

For a function, if A2 <: A1 and B1 <: B2, then A1 => B1 <: A2 => B2.

Functions must be contravariant in their argument types and covariant in their result types, e.g.

    trait Function1[-T, +U] {
      def apply(x: T): U
    } // Variance check is OK because T is contravariant and U is covariant

    class Array[+T] {
      def update(x: T)
    } // variance checks fails

Find out more about variance in lecture 4.4 and lecture 4.5

Pattern Matching

Pattern matching is used for decomposing data structures:

    unknownObject match {
      case MyClass(n) => ...
      case MyClass2(a, b) => ...
    }

Here are a few example patterns

    (someList: List[T]) match {
      case Nil => ...          // empty list
      case x :: Nil => ...     // list with only one element
      case List(x) => ...      // same as above
      case x :: xs => ...      // a list with at least one element. x is bound to the head,
                               // xs to the tail. xs could be Nil or some other list.
      case 1 :: 2 :: cs => ... // lists that starts with 1 and then 2
      case (x, y) :: ps => ... // a list where the head element is a pair
      case _ => ...            // default case if none of the above matches
    }

The last example shows that every pattern consists of sub-patterns: it only matches lists with at least one element, where that element is a pair. x and y are again patterns that could match only specific types.

Options

Pattern matching can also be used for Option values. Some functions (like Map.get) return a value of type Option[T] which is either a value of type Some[T] or the value None:

    val myMap = Map("a" -> 42, "b" -> 43)
    def getMapValue(s: String): String = {
      myMap get s match {
        case Some(nb) => "Value found: " + nb
        case None => "No value found"
      }
    }
    getMapValue("a")  // "Value found: 42"
    getMapValue("c")  // "No value found"

Most of the times when you write a pattern match on an option value, the same expression can be written more concisely using combinator methods of the Option class. For example, the function getMapValue can be written as follows:

    def getMapValue(s: String): String =
      myMap.get(s).map("Value found: " + _).getOrElse("No value found")

Pattern Matching in Anonymous Functions

Pattern matches are also used quite often in anonymous functions:

    val pairs: List[(Char, Int)] = ('a', 2) :: ('b', 3) :: Nil
    val chars: List[Char] = pairs.map(p => p match {
      case (ch, num) => ch
    })

Instead of p => p match { case ... }, you can simply write {case ...}, so the above example becomes more concise:

    val chars: List[Char] = pairs map {
      case (ch, num) => ch
    }

Collections

Scala defines several collection classes:

Base Classes

Iterable (collections you can iterate on)
Seq (ordered sequences)
Set
Map (lookup data structure)

Immutable Collections

List (linked list, provides fast sequential access)
Stream (same as List, except that the tail is evaluated only on demand)
Vector (array-like type, implemented as tree of blocks, provides fast random access)
Range (ordered sequence of integers with equal spacing)
String (Java type, implicitly converted to a character sequence, so you can treat every string like a Seq[Char])
Map (collection that maps keys to values)
Set (collection without duplicate elements)

Mutable Collections

Array (Scala arrays are native JVM arrays at runtime, therefore they are very performant)
Scala also has mutable maps and sets; these should only be used if there are performance issues with immutable types

Examples

    val fruitList = List("apples", "oranges", "pears")
    // Alternative syntax for lists
    val fruit = "apples" :: ("oranges" :: ("pears" :: Nil)) // parens optional, :: is right-associative
    fruit.head   // "apples"
    fruit.tail   // List("oranges", "pears")
    val empty = List()
    val empty = Nil

    val nums = Vector("louis", "frank", "hiromi")
    nums(1)                     // element at index 1, returns "frank", complexity O(log(n))
    nums.updated(2, "helena")   // new vector with a different string at index 2, complexity O(log(n))

    val fruitSet = Set("apple", "banana", "pear", "banana")
    fruitSet.size    // returns 3: there are no duplicates, only one banana

    val r: Range = 1 until 5 // 1, 2, 3, 4
    val s: Range = 1 to 5    // 1, 2, 3, 4, 5
    1 to 10 by 3  // 1, 4, 7, 10
    6 to 1 by -2  // 6, 4, 2

    val s = (1 to 6).toSet
    s map (_ + 2) // adds 2 to each element of the set

    val s = "Hello World"
    s filter (c => c.isUpper) // returns "HW"; strings can be treated as Seq[Char]

    // Operations on sequences
    val xs = List(...)
    xs.length   // number of elements, complexity O(n)
    xs.last     // last element (exception if xs is empty), complexity O(n)
    xs.init     // all elements of xs but the last (exception if xs is empty), complexity O(n)
    xs take n   // first n elements of xs
    xs drop n   // the rest of the collection after taking n elements
    xs(n)       // the nth element of xs, complexity O(n)
    xs ++ ys    // concatenation, complexity O(n)
    xs.reverse  // reverse the order, complexity O(n)
    xs updated(n, x)  // same list than xs, except at index n where it contains x, complexity O(n)
    xs indexOf x      // the index of the first element equal to x (-1 otherwise)
    xs contains x     // same as xs indexOf x >= 0
    xs filter p       // returns a list of the elements that satisfy the predicate p
    xs filterNot p    // filter with negated p
    xs partition p    // same as (xs filter p, xs filterNot p)
    xs takeWhile p    // the longest prefix consisting of elements that satisfy p
    xs dropWhile p    // the remainder of the list after any leading element satisfying p have been removed
    xs span p         // same as (xs takeWhile p, xs dropWhile p)

    List(x1, ..., xn) reduceLeft op    // (...(x1 op x2) op x3) op ...) op xn
    List(x1, ..., xn).foldLeft(z)(op)  // (...( z op x1) op x2) op ...) op xn
    List(x1, ..., xn) reduceRight op   // x1 op (... (x{n-1} op xn) ...)
    List(x1, ..., xn).foldRight(z)(op) // x1 op (... (    xn op  z) ...)

    xs exists p    // true if there is at least one element for which predicate p is true
    xs forall p    // true if p(x) is true for all elements
    xs zip ys      // returns a list of pairs which groups elements with same index together
    xs unzip       // opposite of zip: returns a pair of two lists
    xs.flatMap f   // applies the function to all elements and concatenates the result
    xs.sum         // sum of elements of the numeric collection
    xs.product     // product of elements of the numeric collection
    xs.max         // maximum of collection
    xs.min         // minimum of collection
    xs.flatten     // flattens a collection of collection into a single-level collection
    xs groupBy f   // returns a map which points to a list of elements
    xs distinct    // sequence of distinct entries (removes duplicates)

    x +: xs  // creates a new collection with leading element x
    xs :+ x  // creates a new collection with trailing element x

    // Operations on maps
    val myMap = Map("I" -> 1, "V" -> 5, "X" -> 10)  // create a map
    myMap("I")      // => 1  
    myMap("A")      // => java.util.NoSuchElementException  
    myMap get "A"   // => None
    myMap get "I"   // => Some(1)
    myMap.updated("V", 15)  // returns a new map where "V" maps to 15 (entry is updated)
                            // if the key ("V" here) does not exist, a new entry is added

    // Operations on Streams
    val xs = Stream(1, 2, 3)
    val xs = Stream.cons(1, Stream.cons(2, Stream.cons(3, Stream.empty))) // same as above
    (1 to 1000).toStream // => Stream(1, ?)
    x #:: xs // Same as Stream.cons(x, xs)
             // In the Stream's cons operator, the second parameter (the tail)
             // is defined as a "call by name" parameter.
             // Note that x::xs always produces a List

Pairs (similar for larger Tuples)

    val pair = ("answer", 42)   // type: (String, Int)
    val (label, value) = pair   // label = "answer", value = 42  
    pair._1 // "answer"  
    pair._2 // 42

Ordering

There is already a class in the standard library that represents orderings: scala.math.Ordering[T] which contains comparison functions such as lt() and gt() for standard types. Types with a single natural ordering should inherit from the trait scala.math.Ordered[T].

    import math.Ordering  

    def msort[T](xs: List[T])(implicit ord: Ordering) = { ...}  
    msort(fruits)(Ordering.String)  
    msort(fruits)   // the compiler figures out the right ordering

For-Comprehensions

A for-comprehension is syntactic sugar for map, flatMap and filter operations on collections.

The general form is for (s) yield e

s is a sequence of generators and filters
p <- e is a generator
if f is a filter
If there are several generators (equivalent of a nested loop), the last generator varies faster than the first
You can use { s } instead of ( s ) if you want to use multiple lines without requiring semicolons
e is an element of the resulting collection

Example 1

    // list all combinations of numbers x and y where x is drawn from
    // 1 to M and y is drawn from 1 to N
    for (x <- 1 to M; y <- 1 to N)
      yield (x,y)

is equivalent to

    (1 to M) flatMap (x => (1 to N) map (y => (x, y)))

Translation Rules

A for-expression looks like a traditional for loop but works differently internally

for (x <- e1) yield e2 is translated to e1.map(x => e2)

for (x <- e1 if f) yield e2 is translated to for (x <- e1.filter(x => f)) yield e2

for (x <- e1; y <- e2) yield e3 is translated to e1.flatMap(x => for (y <- e2) yield e3)

This means you can use a for-comprehension for your own type, as long as you define map, flatMap and filter.

For more, see lecture 6.5.

Example 2

    for {  
      i <- 1 until n  
      j <- 1 until i  
      if isPrime(i + j)  
    } yield (i, j)

is equivalent to

    for (i <- 1 until n; j <- 1 until i if isPrime(i + j))
        yield (i, j)

is equivalent to

    (1 until n).flatMap(i => (1 until i).filter(j => isPrime(i + j)).map(j => (i, j)))