
layout: page
title: Cheat Sheet

This cheat sheet originated from the forum, credits to Laurent Poulain.
We copied it and changed or added a few things.
There are certainly a lot of things that can be improved! If you would like to contribute, you have two options:
 Click the "Edit" button on this file on GitHub:
[https://github.com/lampepfl/progfunwiki/blob/ghpages/CheatSheet.md](https://github.com/lampepfl/progfunwiki/blob/ghpages/CheatSheet.md)
You can submit a pull request directly from there without checking out the git repository to your local machine.
 Fork the repository [https://github.com/lampepfl/progfunwiki](https://github.com/lampepfl/progfunwiki) and check it out locally. To preview your changes, you need [jekyll](http://jekyllrb.com/). Navigate to your checkout and invoke `jekyll serve`, then open the page [http://localhost:4000/CheatSheet.html](http://localhost:4000/CheatSheet.html).
## 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
```scala
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.
```scala
// sum takes a function that takes an integer and returns an integer then
// 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 = f(a) + f(b)
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 1 cubed and 10 cubed
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.
```scala
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)
```
To curry an existing function :
```scala
val f2: (Int, Int) => Int = f // uncurried version (type is (Int, Int) => Int)
val f3: Int => Int => Int = f2.curried // transform it to a curried version (type is Int => Int => Int)
val f4: (Int, Int) => Int = Function.uncurried(f3) // go back to the uncurried version (type is (Int, Int) => Int)
```
## Classes
```scala
class MyClass(x: Int, val y: Int,
var z: Int): // Defines a new type MyClass with a constructor
// x will not be available outside MyClass
// val will generate a getter for y
// var will generate a getter and a setter for z
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
private def test(a: Int): Int = ... // private method
val nb3 = x + y // computed only once
override def toString = // overridden method
x + ", " + y
end MyClass
new MyClass(1, 2, 3) // creates a new object of type
```
`this` references the current object, `assert()` issues `AssertionError` if condition
is not met. See [`scala.Predef`](https://www.scalalang.org/api/current/scala/Predef$.html) for `require`, `assume` and `assert`.
## End markers
When the body of a class, object, trait, method or value becomes long, visually
inspecting where it ends might become challenging.
In these situations, it is possible to explicitly signal to the reader that the body
is over using the `end` keyword with the name of the definition:
```scala
class MyClass(a: Int, b: String):
// body
end MyClass
object MyObject:
// body
end MyObject
trait MyTrait:
// body
end MyTrait
def myMethod(name: String): Unit =
println(s"Hello $name")
end myMethod
val myVal: Int =
42
end myVal
```
## 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: Rightassociative if ending with `:`, Leftassociative 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
```scala
abstract class TopLevel: // abstract class
def method1(x: Int): Int // abstract method
def method2(x: Int): Int = ...
end TopLevel
class Level1 extends TopLevel:
def method1(x: Int): Int = ...
override def method2(x: Int): Int = ... // TopLevel's method2 needs to be explicitly overridden
end Level1
object MyObject extends TopLevel:
... // defines a singleton object. No other instance can be created
```
To create a runnable application in Scala:
```scala
@main def run(args: Array[String]) =
println("Hello world")
```
or
```scala
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 nonabstract members:
```scala
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 userdefined 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.
```scala
class MyClass[T](arg1: T):
...
MyClass[Int](1)
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.
```scala
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 <: TopLevel](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
```scala
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.
```scala
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](https://class.coursera.org/progfun2012001/lecture/81)
and [lecture 4.5](https://class.coursera.org/progfun2012001/lecture/83)
## Pattern Matching
Pattern matching is used for decomposing data structures:
```scala
unknownObject match
case MyClass(n) => ...
case MyClass2(a, b) => ...
```
Here are a few example patterns
```scala
(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 subpatterns: 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`:
```scala
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:
```scala
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:
```scala
val options: List[Option[Char]] = Some('a') :: None :: Some('b') :: Nil
val chars: List[Char] = options.map(o => o match {
case Some(ch) => ch
case None => 'z'
})
```
Instead of `o => o match { case ... }`, you can simply write `{case ...}`, so the above example becomes more concise:
```scala
val chars: List[Char] = options.map {
case Some(ch) => ch
case None => 'z'
}
```
## Collections
Scala defines several collection classes:
### Base Classes
 [`Iterable`](https://www.scalalang.org/api/current/scala/collection/Iterable.html) (collections you can iterate on)
 [`Seq`](https://www.scalalang.org/api/current/scala/collection/Seq.html) (ordered sequences)
 [`Set`](https://www.scalalang.org/api/current/scala/collection/Set.html)
 [`Map`](https://www.scalalang.org/api/current/scala/collection/Map.html) (lookup data structure)
### Immutable Collections
 [`List`](https://www.scalalang.org/api/current/scala/collection/immutable/List.html) (linked list, provides fast sequential access)
 [`Stream`](https://www.scalalang.org/api/current/scala/collection/immutable/Stream.html) (same as List, except that the tail is evaluated only on demand)
 [`Vector`](https://www.scalalang.org/api/current/scala/collection/immutable/Vector.html) (arraylike type, implemented as tree of blocks, provides fast random access)
 [`Range`](https://www.scalalang.org/api/current/scala/collection/immutable/Range.html) (ordered sequence of integers with equal spacing)
 [`String`](http://docs.oracle.com/javase/1.5.0/docs/api/java/lang/String.html) (Java type, implicitly converted to a character sequence, so you can treat every string like a `Seq[Char]`)
 [`Map`](https://www.scalalang.org/api/current/scala/collection/immutable/Map.html) (collection that maps keys to values)
 [`Set`](https://www.scalalang.org/api/current/scala/collection/immutable/Set.html) (collection without duplicate elements)
### Mutable Collections
Most of the immutable collections above have a mutable counterpart, e.g.:
 [`Array`](https://www.scalalang.org/api/current/scala/Array.html) (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
NOTE: For the correct code convention of using postfix or not, read [this](https://docs.scalalang.org/style/methodinvocation.html)
```scala
val fruitList = List("apples", "oranges", "pears")
// Alternative syntax for lists
val fruit = "apples" :: ("oranges" :: ("pears" :: Nil)) // parens optional, :: (pronounced cons) is rightassociative
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 splitAt n // same as (xs take n, xs drop n)
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 as 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{n1} 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 singlelevel 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 LazyLists
val xs = LazyList(1, 2, 3)
val xs = LazyList.cons(1, LazyList.cons(2, LazyList.cons(3, LazyList.empty))) // same as above
(1 to 1000).to[LazyList] // => Stream(1, ?)
x #:: xs // Same as LazyList.cons(x, xs)
// In the LazyList's cons operator, the second parameter (the tail)
// is defined as a "call by name" parameter.
// Note that x::xs always produces a List
def integers(start: Int = 0): LazyList[Int] = start #:: integers(start + 1) // infinite sequence of integers starting at "start"
integers(0) drop 10 take 100 // New lazylist starting at 10
```
## Pairs (similar for larger Tuples)
```scala
val pair = ("answer", 42) // type: (String, Int)
val (label, value) = pair // label = "answer", value = 42
pair(0) // "answer"
pair(1) // 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]`.
```scala
import math.Ordering
def msort[T](xs: List[T])(using Ordering[T]) = ...
msort(fruits)(using Ordering.String)
msort(fruits) // the compiler figures out the right ordering
```
## ForComprehensions
A forcomprehension 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
```scala
// 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
```scala
(1 to M).flatMap(x => (1 to N).map(y => (x, y)))
```
### Translation Rules
A forexpression 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; s) yield e2` is translated to `for (x < e1.withFilter(x => f); s) yield e2`
`for (x < e1; y < e2; s) yield e3` is translated to `e1.flatMap(x => for (y < e2; s) yield e3)`
Note: s is a (potentially empty) sequence of fields (generators and filters)
This means you can use a forcomprehension for your own type, as long
as you define `map`, `flatMap` and `filter`.
For more, see [lecture 6.5](https://class.coursera.org/progfun2012001/lecture/111).
### Example 2
```scala
for
i < 1 until n
j < 1 until i
if isPrime(i + j)
yield (i, j)
```
is equivalent to
```scala
for (i < 1 until n; j < 1 until i if isPrime(i + j))
yield (i, j)
```
is equivalent to
```scala
(1 until n).flatMap(i => (1 until i).filter(j => isPrime(i + j)).map(j => (i, j)))
```